So hello everybody, welcome to today's meeting of Medical Doctors for COVID Ethics International.
This group was founded by Dr. Stephen Frost over three years ago with a desire to pursue
truth, ethics, justice, freedom and health.
Stephen has stood up against government and power over the years and has been a whistleblower
and activist.
His medical specialty is radiology.
I'm Charles Covess, the moderator of this group.
I'm Australasian passion provocateur.
We have plenty of passionate people in these meetings.
I practiced law for 20 years before changing career 31 years ago.
And over the last 13 years, I've helped parents and lawyers to strategize remedies for vaccine
damage and damage from bad medical advice.
The numbers now show clearly that it is bad medical advice that is the number one cause
of death in the USA.
I don't know what it is in Australia where I'm located.
I'm also the CEO of an industrial hemp company.
We comprise lots of professions here and we're from all around the world.
If this is your first time here, welcome and feel free to introduce yourself on the chat
and where you're from.
Many of us thought that vaccines were okay.
Now many of us proudly say, yes, we are passionate anti-vaxxers and I number myself among those,
even though my five children are vaccinated.
The number to remember for Australia, UK, America, very similar.
When I was a kid, I only got three or four vaccines in the first four or five years of
life in Australia.
We have a no jab, no pay, no play principle.
If you don't give the jab to your children, vaccines to your children, then you give no
government benefits and they can't play in kindergarten.
The number of vaccines that a child has to have injected into them in Australia is 43
in the first four years of life.
43.
No safety and efficacy tests have been done on that mad regime.
Those 43 antigens are made up of 15 different vaccines pumped into children with amazing
frequency.
If you publish a newsletter or a podcast or you have a radio or TV show or you've written
a book, put the links into the chat so we can follow you, promote you and find you.
I'm on TNT radio.
TNT radio is a place where there's no political correctness.
There's no censorship.
There's no wokeness.
Most of us understand we're in the middle of World War III and that the medical science
battle is only one of 12 battle fronts of this latest World War.
There's no time to be tired.
We are some four years into what I consider will be a seven year war.
We've got three more years to go, at least.
Get ready for the fight.
Most of us understand the development of science and science is never settled.
This meeting runs for two and a half hours after which for those with the time, Tom Rodman
runs a video telegram meeting.
Tom puts the links into the chat if you're able to join.
We will listen to our guest presenter today, Andrew Paquette, for as long as Andrew wishes
to speak.
And then we have Q&A.
Stephen Frost, by long established tradition, asks the first questions for 15 minutes.
This is a free speech environment with appropriate moderating.
Please understand that free speech is free speech except for ad hominem attacks.
No attacking people.
If you attack people and you're participating, you run a big risk of being removed from the
meeting.
If you're offended by anything, be offended.
We are lovingly not interested.
We reject the offense industry that requires nobody to say anything that may offend another.
We come with an attitude and perspective of love, not fear.
Fear is the opposite of love.
Fear squashes you.
Love, on the other hand, expands you.
Fear imprisons you.
We're all about freedom here.
So you come to these meetings to be reminded to not have your life driven by fear.
These twice weekly meetings are not just talk fests.
An extraordinary range of activities and actions and initiatives have been generated from linkages
made by attendees in these meetings.
If you have a solution or a product or links or resources that will help people put the
details into the chat, the meeting is recorded and is uploaded onto the Rumble channel.
And now a quick reminder about Reiner Fulmick in the German jail in a corrupt German legal
process.
Celia Farber, one of our presenters in her Substruct this morning, shared the news of
how corrupt the German legal system is in the case of a 14-year-old girl who was raped
by nine men.
It's extraordinary.
And Reiner Fulmick is in the hands of that same corrupt German system.
And we need to speak out about it.
I speak about it at the start of each of these meetings and in my TNT radio program.
All of you spread the word.
We need to put pressure on the German government, just like ongoing pressure was put on the
US government, UK government, Australian government about the case of Julian Assange.
And it's worth noting at the start of this meeting that Julian Assange is now no longer
in prison in the UK.
He did a plea deal.
So now welcome to our guest presenter, Andrew Paquette.
And we thank you, Andrew, for giving us your time, wisdom and insights.
His detailed CV is on the show notes, but we'll ask Jerome Corsi if you would kindly
introduce Andrew before Andrew presents to us.
And thank you, Stephen Frost, again, for creating this group and for organizing Andrew to be
with us today.
Over to you, Jerome.
Well, thank you very much, Charles.
It's a real pleasure and honor to bring Andrew onto this forum.
Andrew, I just got word today that the article I've written on Andrew's work identifying
an algorithm in the New York State Voters Database will be published in American Thinker.
So very next week, we'll probably have an article on the research you're going to preview
today. Now, Andrew's got a very interesting background.
He has a PhD from King's College London, education, and his dissertation was on
spirit, spatial visualization, visualization and professional competence, the development
of proficiency among digital artists.
Andrew's specialty is really computer art and computer games.
Very advanced in terms of his digital capabilities.
And he's got a wide background, including working in comic books with comic book companies
like Marvel and DC, Harris Comics.
He also does produce cartoon training manuals for the U.S.
Army. He's currently doing that right now.
And he's had a series of professional appointments and publications.
His dissertation was published by Springer Verlong in London, a very prestigious publishing
house, and he's had several of his publications picked up by Springer Verlong, also an
introduction to computer graphics, his second edition in 2013.
He's published in a number of scientific journals, including his most recent article on the
New York algorithm and the voter rolls, which we're going to study today.
He's going to present to us today, which was published in 2023 in the Journal of
Information Warfare, volume 22, number two.
So he has had a wide range of experience, has a is not his background is not cryptography.
But like many of the people who have done extremely well in cryptography, he has very
advanced technical skills that have to do with visualization, the ability to do
computer graphics at a very, very advanced mathematical level.
He's obviously been accomplished with not only in his profession, but also in his
publications. And he's come upon, I think, one of the fundamental understandings of why
the voting records, certainly in the United States and very probably around the world,
are intentionally subject to fraud.
So I think this is an extremely important presentation and one that can be internationally
game changing in its implications.
And I have some conflicts today.
I have to leave the meeting at 3.30.
I'll be back at 4.30 to participate in the questions and answers.
Andrew has done a very, very effective deck of slides and he's going to go through it.
So with that introduction, it's a real honor and pleasure to introduce Andrew and Andrew.
The show is yours now for as long as you care to do the presentation, followed by Q&A.
Andrew. OK, thank you very much.
Now, just so everyone knows, I do have a low bandwidth problem today, so it's possible
that my mic will drop out every once in a while.
For that reason, I'm going to stop my camera and I'm going to share my screen with you.
And while I do that, I also want to say something has something to do with your mission here,
because in some of my earliest presentations,
I wound up being in contact with the Children's Health Defense Fund,
John F. Kennedy, Robert F.
Kennedy, Jr.'s group.
And I had a conversation with their attorney and
forget the title of the other woman I spoke with.
And they said to me that they felt that my discoveries in the
New York state's voter rolls concerned them a great deal because the voter rolls
controlled the elections and the elections control the politicians who were making
policy that was contrary to their interests.
So it was it's kind of interesting to, again, be speaking to people who have the
anti vaccination stance because it's all related.
OK, so can you see my screen?
Yep. OK, so let me move this off to the side.
All right. So this image, this 3D graphic that I threw together,
just so you guys have an idea of what we're talking about.
The way I look at the voter rolls is kind of like you're walking along the road and you run
across a steering column lying on the road.
You know, it's design. You don't see a car.
You don't know what it's used for. You don't know why it's there.
That's what the algorithms in the voter rolls are like.
They pose a number of questions with no obvious answers.
However, one thing is obvious, and that is it's designed and it does have a purpose.
What that purpose is, is something that we're going to explore.
So let me go to the next slide and let's start off with what voter rolls are for.
OK, so it's pretty simple.
We want to know that all the voters are qualified.
So what that means is before you can be registered, you have to present
evidence that you're a qualified voter, meaning you're 18 years or older,
meaning that you live in the jurisdiction you're registering in and you are a U.S. citizen.
OK, there are a couple of other procedural requirements, but those are the main ones.
You're 18 years old or older, you're a U.S. citizen and you live where you say you live.
So to prove that, what you have to do is you have to bring proof of identity,
proof of address and proof of citizenship.
And sometimes the proof of identity is the equivalent of proof of citizenship.
But that's why we have the voter roll is to is to prove these things.
It also helps with fraud prevention because you can do post-election audit
by comparing the number of people who voted or who are recorded as having voted
in the voter rolls with the number of ballots that are cast.
If there's not a match, you know you have a problem.
They also help with election management because they give a list of names
and addresses of people that can be contacted if necessary for administrative reasons.
However, for these things to work, they have to be accurate, current and transparent.
And these are all very important items because unfortunately in America anyway,
they fail on well, at least two of these.
The New York voter rolls that I've looked at, as well as rolls in other states
that I've looked at, are demonstrably inaccurate and not in small numbers
and very, very large numbers.
As far as currency is concerned, for the most part, they appear to be current.
However, if I don't know if it counts as current, if what you're looking at is a bunch
of records that are illegally present in the rolls.
So if you have something that was illegally deposited yesterday,
you could say that's current, and yet it's also illegal at the same time.
The transparency is interesting because this creates a problem.
So if somebody wants to do something nefarious in the voter rolls,
they have to account for the fact that the voter rolls are public.
Therefore, whatever it is that they do has to somehow be concealed from public disclosure,
even though the records by law must be publicly disclosed.
And this is where the difference between cryptography and steganography comes in.
Now, on the off chance, some of the people on this call aren't aware of the difference.
Cryptography, the result of cryptography is a cipher that is readily recognized.
We'll be patient while he comes back.
Low bandwidth, I'm sure.
Yep. He will come back as a cipher.
So if you look at, for instance, any, can you hear me?
We know we missed a piece there where you were just talking about
transparency, if you'll repeat that.
OK, thank you. So the thing is about transparency.
Anyone who wants to do something nefarious with the voter rolls has a problem there.
And the reason is that if they do it, it will be publicly disclosed
because the law requires that the voter rolls be publicly disclosed.
So whatever they do has to somehow be something they can hide.
They have to have a way to make it covert.
And this is where the difference between cryptography and steganography comes into play.
Now, I'm assuming that maybe a couple of people don't know the difference
between cryptography and steganography.
So I'll just say it this way.
Steganography is where you hide the fact that there is a cipher.
OK, so you don't even know there's something to decode.
And cryptography is where you you in cipher information,
but you do it in such a way that it's very clear that it's been encoded.
So if you look at something from World War Two, where they use the Enigma machines
to encode German transmissions, it's obvious that they're encoded when you look at it.
It's it's it's nonsense, but it has structure and that's readily apparent.
However, steganography, like, for instance, if you watch most modern movies,
they have embedded in the images copyright information.
So while you're watching the movie, you don't see this and you're not aware that it's even there.
So what you'd have to do with the voter rolls, because they're transparent,
is you would have to conceal what you've done somehow in a way
that doesn't interfere with the fact that the information is publicly disclosed.
And that's the direction we're going to head here in this talk.
So let's go to the next slide.
So we have a couple of laws here that are going to be violated
when people fool around with the with the voter rolls. OK.
But chief among them is that the states must maintain accurate
and current voter registration rules.
Now, when other people talk about laws in relation to the voter rolls,
they normally don't talk about this particular provision as being all that important.
They talk about the importance of voters themselves
not going in and individually making a false registration.
The idea of the election boards doing something at a systematic
or a systemic level is ordinarily not contemplated.
But this here deals with the systemic level. OK.
So if the states aren't maintaining accurate and current voter registration rules,
they're violating the National Voter Registration Act.
And let's see.
And next, we're going to go to the Help America Vote Act, also known as HAVA.
In this case, they're requiring that there's a unique identifier for each voter.
This is important because this has been violated quite a lot of times in New York,
which means that the state board of elections is actually in violation
of this law many times over.
I'll get to the numbers in just a minute.
So here we have the eligibility issue, and eligibility is quite important.
So what they do is they say that the voter registration
application form is literally an affidavit.
And this is why it must be hand signed by the voter who's registering.
This is extremely important because if you have fake records in the rolls,
as I believe there are,
where would the paperwork be for those fake records
and who would have signed for those fake records?
Now, I happen to have found about two million records
while I was engaged in work with a group known as New York Citizens Audit.
And these records are are basically fake.
They're illegal records.
So, for instance, there's a person who has 25 different state ID numbers,
which allows 25 absentee ballots to be sent to him every single election.
Which allows him to vote in 25 different jurisdictions simultaneously,
which grossly violates the law.
So the thing is, I was wondering
how many of those are going to have a signature, right?
Do they even have documents that support all of these excess records?
We've got two million records, and it seemed to me that the test for
whether this was an innocent mistake
or it was something that was intentionally illegal
is going to be what the paperwork looks like.
So I asked. So here is an example of that.
Now, I've masked off a lot of the data, so you're not going to be able to tell
who this is. But what this is,
is a voter information report for two different records.
Now, if you look at the county ID here on the left,
you see it ends in 072 and you see right next to it on the right,
there's another one that ends in 074.
So these are different county IDs.
Now, that's actually OK if the person moves from one county to another.
But in this case, if you look at the residential address zip code, it's identical.
So and I happen to know that the full address is exactly identical.
So this is actually already illegal at the county ID level, but it gets worse.
If you look at the state ID, it ends in 1837 on one side
and on the other, it ends in 8056.
So these are different state IDs.
And that allows for multiple mail in ballots to be mailed to this person.
And by the way, this person has three records, not two.
I just felt it was easier to see two than to look at all three.
So we have two different records for the same person with the same birthdate,
with the same address.
If you look at the registration dates, February 7th, 2020 and February 8th, 2020.
So these are a day apart.
And I can tell you that the third record, I forget if it's the seventh
or the eighth, but it's on one of these same two days.
So somehow this person got three records within about 25 hours of each other
with different ID numbers, three different ID numbers.
And if you look at the signature and this is where it gets very interesting
and I've blocked off half the signature so you don't see the last name.
But this is identical.
Every pixel is identical.
So if you look, there's like this very tiny dot right near
where my cursor is on the right.
And if I go over to the left, you see that same dot is right there.
And if you look at the end of the R here, those dots are all exactly the same.
If I.
We've lost him again, we'll wait.
Charles, could this been going on in Australia?
No, that's quite quite different.
You're back. Oh, sorry.
Yeah, but there might be a variation on it, which you.
No, it's it's a it's quite a different system, Steven, but it's a great.
It's a the question is how how much beyond fraud is ours?
What the AEC, the Australian Electoral Commission.
Is Andrew back?
No, he hasn't gone, but we can't hear him going.
He's got his bandwidth problems.
He's picked the wrong band, Steven, he's picked a con.
And there you are, Andrew.
No, I can't hear you.
He's picked a symphony orchestra, Steven, when a when a quartet would have done.
And.
Or actually a big just tell me when you can hear me.
I will will do it.
There's a text he puts me in the chance just.
When we get him, we'll tell you, but we can't hear you yet, Andrew.
We would tell you when we can hear you, Andrew, but we can't hear you.
Steven, I love it when computer experts have computer problems.
Makes me feel less incompetent.
Yeah, I must admit, it's a bandwidth problem.
You know that, Andrew.
So.
Andrew's keeping us informed in the chat, everybody.
This is a bandwidth problem started 10 days ago.
Well.
Started 10 days ago wasn't actually a bandwidth.
There wasn't a problem previous to that, no.
Yeah, he says, I'm sorry if I was paranoid, I'd say it was a CIA.
Uh.
It was.
It was perfect.
In dozens of previous zoom meetings, says Andrew.
Well.
And as soon as Andrew meets Jerome low bandwidth.
Haha.
They are, of course,
they're going to meet each other on a regular basis.
Aha, there you are.
Corsi, you're very powerful.
He's gone too.
He's had to go to his meeting.
Try dialing in, Andrew.
I can move the slides forward.
So prior to 10 days ago, he had no problem with his bandwidth.
Is that right?
Correct.
And I've got the slide deck so I can show the slide deck.
Oh, you need the number.
Tom, can you put the number in the chat, please?
Tom Rodman.
That Andrew calls in.
Andrew's in New York, I think.
Well, where are you, Andrew?
What state?
I think New York.
Well, Tom has put the New York.
Yep.
Tom, put the New York number in if you can dig it out
of the list on the invite.
Here it is, Andrew.
Stop your sharing.
And then I will share the slides.
OK, Andrew, I've got the slides there.
And I can go through here.
Andrew's calling in on his phone.
Sorry.
Da da da da.
What's the meeting ID, Tom?
Andrew needs the meeting ID.
Meeting ID, I suppose, passcode.
Yeah, we're sending it to you, Andrew.
OK, Ulrike has put it in there now.
OK, I'm going to go through it.
OK, Ulrike has put it in there.
9352118786.
Say it again, Charles.
It's on the chat.
OK, what's the password?
Passcode 211230.
Thanks, Tom.
211230.
We'll edit all this out in the recording, everybody.
So now in the chat, you've got the code, Tom,
sorry, Andrew, and the passcode.
Not for the first time we've had problems like this, Charles,
but there's always this plausible deniability,
which they always build in.
You're never quite sure.
Yeah, Andrew can hear us through the process.
Yeah, that's true, Stephen.
We can't hear you yet, Andrew, on your phone for some reason.
We can't hear you.
We can't hear you yet, Andrew, on your phone for some reason.
That's strange, Tom.
Why would Andrew...
Yeah, exactly.
Do you see a new person joining on a phone?
That would be him?
No, we can't.
We would be hearing him.
I mean, he'd have to come in as a separate entry,
and then we could look and see if his phone was muted or not.
Well, Andrew's phone is the phone number there,
845-303-0624, that looks muted.
So, just say he needs to unmute himself, you mean, Charles?
Yeah, but he doesn't know how.
He doesn't know how to unmute.
Oh, sorry.
Star 6.
Star 6, Andrew?
OK, can you hear me now?
Yep, can hear you.
Excellent, Tom.
For crying out loud.
What a pain.
OK, sorry, guys.
Can I share my screen again?
Or you're sharing yours so we can see this.
All right, fine.
OK, so the main thing that's important about this particular
slide is that we have several laws that govern how the database
is handled, OK?
And it says that if it's not accurate, it's not current,
then it violates these two laws.
And this is very important because they definitely have been
violated.
So let's go to the next slide.
I'm assuming you have, yeah, there we go.
OK, we already talked about this.
Let's get to that signature slide.
So that's the next one.
And there we go.
OK, so what's important about this, the requests went through a
group called New York Citizens Audit.
And I think it was somewhere in the neighborhood of about 10
counties reacted with a group of records.
Now, we didn't ask for all of the records because we anticipated
they would balk at sending hundreds of thousands of these
signature files.
So what we did was I selected what I consider to be a
strategically friendly county, which is the one we got these
two signatures from, and then gave a very, made a very limited
request.
So I only asked for a very limited number of signatures.
So I only asked for records that were clones that were within
the same county and were registered within a 10 day
period.
So they sent us all of those files and all of them were like
this, every single one of them.
So then we, after that, we brought in the request to other
counties.
There are 62 counties in New York State.
And we received records from about 20 of those counties,
notably the worst offenders, like, for instance, New York City
where they have, I think it's the neighborhood of about a
million of these types of cloned records, they didn't respond.
So we never got any records from New York City.
Mainly the places we got the records from were the more
honest counties.
But all of them looked like this.
Every single one that I have seen, they have these
photographically identical signatures.
And that's whether there's one clone or two clones or three
clones.
They're all like this.
So I showed them the state police special investigations
unit.
I showed them to district attorney, which I don't know if
the equivalent is in Australia and England, but it's the type
of prosecutor.
I showed them to sheriff.
They all accept.
These are forgeries.
They are illegal.
And they need to be investigated.
Interestingly enough, at the state police, the guy who was
in charge of that unit who told me this was very important and
has to go further, sent it to the FBI, and then he got
arrested.
So I showed them to the police.
And they all accepted.
So I showed them to the next slide, please.
Okay.
So as far as errors go, there are errors in just about every
field I checked.
So we've got names that are spelled wrong, date of birth,
registration dates that are wrong, addresses, voter history
status, that is, say, whether they're active, inactive or
purged.
And then, of course, there's the presence of illegal records.
And many of the illegal records have some of the types of errors
that I mentioned above.
And there's a lot of other errors in addition to these that
I'm not mentioning.
In addition to the fact that we see this information, which
should be immutable, changing between versions of the database.
So we've got different versions of the database where people's
date of birth is altered.
Their registration dates are changed.
Their addresses are changed in ways that make it apparent it
has nothing to do with an actual address change.
And the voter histories are changing as well.
So there are a lot of very strange things going on in the
database that make it appear that they're not actually
registered.
And so there's a lot of very strange things going on in the
database that make it quite clearly inaccurate.
And the thing about that that's quite fascinating is that what
this means for the most part is they can't be using any normal
form of data validation.
Data validation is something that you encounter when you go
to a kiosk on the web, for instance, to buy something.
So if you want to rent a movie or buy something at the Amazon
.com or something, you can go to Amazon.com and click on the
link at the top of the screen.
So you're going to need to get in.
So the data validation is something that you can encounter
when you go to a kiosk on the web, for instance, to buy
something.
So if you want to rent a movie or buy something at Amazon.com
Amazon.com or something, you have to enter your name, your address, your credit card information,
as well as information regarding using OneAbide, etc. But if you enter data that's invalid,
like for instance, if you type in a postcode that doesn't match where you live or the address that
you provide, or you give a phone number that's non-functional for some reason, it will not allow
the application to be processed. So it'll give you an error message. It'll tell you that the
information is invalid and it asks you to re-enter the data. If something like that was
implemented in New York's photo rolls, none of the problems I found would be there. It would be able
to catch absolutely every single one of them. For instance, these cloned records like I've just been
talking about here, the problem with those is there is an existing record. So this is like,
I had gone to the Board of Elections, registered to vote, and then come back later and tried to do
it again. So when I come back on that second occasion, what their system should do is pull
my name and date of birth and address to see if there's an existing registration that matches
that information. And if there is, then it should not allow that registration application to be
processed. And this, by the way, this exact circumstance is contemplated in the law,
is described in the law, which says that the County Board of Elections must check for existing
registrations before processing new applications. That alone would have prevented the majority of
the clones that I found having been created. Now there are clones that could have been created
anyway. For instance, when the name is spelled slightly wrong or the date of birth is a little
different because then that data doesn't match. However, the law also specifies that even if
it looks like it's a good registration where nothing matches, they still have to take it
another step by checking what's called the social security number and the driver's license number.
And only then are they allowed to process it. Now the thing is that at that level, all of these
state registrations would have been captured, which means that at a systemic level, the Board
of Elections are not performing this task. If they were performing this task, the data I'm seeing in
the voter rolls would be impossible. It could never have been created. And this affects almost 10%,
actually, I think a little bit more than 10% of all the records, which is quite significant when
it comes to elections that are decided by, in some cases, a few dozen votes. Okay, let's go to the
next slide, please. All right. So one of the more interesting artifacts that I've found in the
voter rolls are discrepant voter histories. So what this is, is when we have the County
Board of Elections, we have the State Board of Elections. So the counties are the local
boards where the data is essentially collected and organized and then shipped to the State Board
of Elections and then they collect it. Now, under the law in New York, the only entity that has the
authority to create, alter, change, or delete records is the County Board of Elections. And
the reason is because they're the source of all the data. So if the state was deleting records
or changing records, there's no infrastructure to allow that data to go back to the counties to
correct their records. So if something like that needs to be done, the county has to do it and then
it should go to the state in the corrected form so that the state database is always synchronized
with whatever the most current version of the county database is. So what we see is, and I'm
just going to use New York City as an example because they're large and they have the largest
number of errors, a discrepancy of about 254,000 votes that occur in the county voter histories
but do not appear in the state voter histories for the same people. So if you look at a voter
ID number, let's just say voter ID number one, and that represents John Doe. So and it says he
voted in the 2020 election. But then you go to the State Board of Elections voter rolls and you look
up voter number one and it says it's John Doe, it does not say he voted in 2020. So this information
from the county rolls is not being transmitted to the state or the information after being
transmitted to the state is being deleted by the state, which would be illegal. So that's a problem.
Now the number of votes involved is huge, 254,000 votes. Now you're looking at this slide and you're
thinking I don't see the number 254,000 up there anyway, anywhere rather. The reason you don't see
that number there is because they've done something very, very strange. I call this the bus problem.
Okay, now for those of you who aren't familiar with the way New York counties are organized,
what we generically call New York City is actually five counties. It's Bronx, Queens, Queens,
New York, and Richmond counties. But they're treated as if they're one county as far as the
Board of Elections is concerned. So each of those counties has a discrepancy of about 50,000. It's
a little less in some and a little more in others, but the total is 254,000 votes. Okay, so what they've
done is they set it up in such a way that if you compare the voter ID numbers, you can see that it's
missing the 250,000 votes. But if you look at the number of votes recorded by the county and compare
it to the state, it comes very close. So that's what we're seeing here in the top. Okay, so on the
top row on the right, you see the certified count of votes. This is what's going into the state
certification process for certifying the vote. So 788,262 votes were certified as it happens in
count. If you look at the precinct count, so this is where the count originated, you see the count is
slightly higher than that. It's not enough to make a huge difference, but it is different. That all
by itself is problematic because this means that somewhere between the precinct and the
state level, about a thousand votes went missing. Okay, actually it's more than a thousand votes.
It's like it's more like 16 or 17 hundred votes. Anyway, so that tells you there's a problem,
but it's not a huge problem. But now you look at the state voter roll count of voters who voted,
and that's a significant difference. That's 737,986 is the difference from 50,000 or so.
And then you look at the county record and it says 739,885, which is really close. That's just,
it looks like it's 1899 is the difference between those two. So it's not much.
But here's the problem. If you compare ID numbers, the difference is actually, and this is by the way,
this is for one county. This looks like it's Queen County. So the difference for Queen County is
actually 55,000 based on ID numbers. But when you look at the actual number of votes,
how does that happen? This is what I call the bus problem. So the bus problem, imagine this,
you have a bus that has 20 passengers, it crashes and eight passengers are killed.
However, when the number of survivors are counted, there are 19 survivors. So how do you take eight
people out of a bus that has 20 people and end up with 19 people? The answer to that is that more
people got on the bus after those eight people were killed. So that's what they're doing here
in the voter rolls. They have effectively taken votes away from one set of ID numbers, but they've
added them back in with another set of ID numbers. Now, why they would do this is a little mysterious
to me, except for the fact that they're adding and subtracting the votes from different counties. So
it looks like they're shifting the numbers so that they can reach the number of certified votes
that they say were certified, despite the fact that those votes are coming from different counties,
which obviously I would think invalidates the purpose. So let's go on to, and by the way,
if I was unclear about that, please ask questions. I always found this particularly
interesting that they did one of the trickier things I've ever seen. And it took me some time to
get my head wrapped around it. But that's what the left-hand image is meant to show you. So if you
look at this, we've got 10 records and on one side you have four missing from the state and you've
got on the other side of two missing from the county, but they're making it up with votes from
the other side. So what I found when I looked at these is that in every case, the missing vote
was connected to a cloned record. So if John Doe has two records, record one and two, and at the
county level it says he voted with ID number one, at the state level it says he voted with ID number
two, but not with number one. And meanwhile, I have no record of a county registration for this
person for ID number two. I only have the state record of that. So this is quite an interesting
problem that definitely needs to be investigated. Now, by the way, the reason I'm showing you this
stuff before I get into the other, because I want you to be aware of and comfortable with the idea
that there are problems worthy of investigation sitting in the... Can you hear me? I can't hear
anyone. Yeah, yeah. Hello? Yeah, we can hear you. Okay. Okay. Okay. So you've heard me talking about
about the bus problem, right? Now, Andrew, now we've got, you need to, we'll get feedback because
we're also getting your microphone working. So if you're on your computer, so reduce the input on
your computer. So how about now? Yeah, can you hear me now? Yep. Okay, good. So I'm going to stick
with the phone because I don't know if the mic's going to go out on me again. Okay. So anyway, so
this is interesting, but the reason I'm telling you about it is because I want you to know that
there are problems in the voter rolls because this gets to why the algorithm is needed. So let's go
to the next slide, please. All right. So purged records are kind of interesting because the way
you purge a record is you have a dropdown menu that has the words active, inactive, and purged on
or in the more recent version of the database, AI or Q. All you have to do to purge a record is
bring up that dropdown menu and select purge. And if you want to make that record active again,
you just select active and it's done. So leaving the record in the database as a purge record is
not a particularly effective safety measure because it can always be changed back to active.
And then after it's been used to count a fake vote, it can then be purged again,
and no one will know it was ever used that way. We have two million records that actually lack
a purge date, which means that you can't retrospectively know whether a vote was
legal or not. Because if your purge date is before your record is having voted, then that
vote is invalid. But if it's after, then it's valid. So not having a purge date means it's
impossible to assess or to audit this particular, to audit votes that are associated with records
that have purged without a purge date. So that's very important. And interestingly, there also are
about two million clones. And one thing about the clones that's interesting is that about a half
million of those are actually not in the voter rolls, but I know they were in the voter rolls
and I know who they belong to originally because of the algorithm I discovered. If it wasn't for
the algorithm, I would never know that those numbers had ever been assigned to anyone and
I certainly wouldn't have a way to figure out who they originally belong to. But I actually can do
that now. So let's go to the next slide. Okay, so let me just show you what a clone looks like.
I'm going to show you a little bit more about this now against the algorithm. So if you look here on
the left, and by the way, I've blocked out the names and address and so on information, but this
is the same person. It's identical names, identical birth dates, and identical addresses. So if you
look at what's called the short ID, that's the state ID, you see that it's almost consecutive.
So the first two are consecutive and then there's a run that looks like six numbers that are
consecutive and then another run of numbers that are consecutive. And you notice the registration
dates all the same. And oh, actually I left the date of birth in there so you can see that's all
the same too. But this is all the same person and this is what a clone looks like. We do have people
who have like 18 records or 21 or 25. Most clones are actually just two records or three records,
but there are I think a few hundred that look like this. So now that you know what this looks
like, let's look at how many there are and where they appear. This is interesting. So go to the
next slide please. Okay, so if you look at this by year, you see that the percentage of clones
to new registration goes up rapidly year over year. In fact, prior to about 1990, there were
in most years zero clones. So you would look at 1950s if you wanted to, all the way up to 1990s.
I recall that there were a couple that might have had like two clones or three clones,
maybe even as many as five, but nothing really significant. But in 1990, you get 514 clones,
which you know that doesn't seem too bad in the context of 6,000 registrations, but it's
certainly not good compared to having no clones in prior years. And then if you look at that number,
it keeps on going up. Okay, now election years, it goes up even more. So 1992, 1996, you see bumps
for every four years, it goes up by a lot more. But if you look down at the bottom, take a look
at 2020, now you're getting 178,755 clones. That is really significant. That's actually almost as
many total registrations as we had in 1990. And yet in this case, that's all clones.
Okay, can you hear me? Hello? Yep. Okay. Yeah. So this is now a lot of clones. And if you look at
the percentages, right, you're going from 0.25% in 1990, all the way up to 17.36% in 2022. And if
you look at the percentages from on the, you know, just on the bottom, just look at those year over
year, it consistently increases every single year. Okay. So from my perspective, what I'm seeing here
is I'm seeing the value of electronic voter registration. In other words, it's not very
good because it seems to be making a problem that didn't exist and making it worse every single year.
So this is not a good thing. All right, let's go to the next slide, please. All right. Now,
what I was wondering when I found all these records was how on earth would you make use of them? Okay.
The thing is, when I was going through the records, there's 21 million records in New York, right?
It's very difficult to find anything in that database just because there are so many records.
You could be looking right at something that's problematic and not know it because the thing
that makes it problematic is another record that's 2 million numbers away. So the way they're mixed in
makes it very, very hard to find what you want if you're a bad guy. So if what you've done is you've
created essentially random fake registrations and scattered them in the voter roll, in order to use
them, you would have to have a way to find them again. Okay. And this problem or this idea bothered
me a lot because as soon as I found these, I was thinking if there's no way to find these again,
then this has to be some kind of an accident. Okay. So it's going to be some day that this is
legitimate somehow. It's an error. It shouldn't be there. It's illegal. So it needs to be fixed,
but it's not intentional. At least that's the way I was thinking at the time.
So I wanted to keep my eyes open for something that would tag the record. Now, I was literally
expecting a tag of some kind. So I was thinking that they would alter somehow
one of the data fields in a consistent way that would allow me to detect cloned records.
And now I figured I probably didn't find all of the cloned records because obviously I don't know
what they know. So the likelihood is that I found a lot of them and I probably have a few false
positives in there. I wouldn't know which ones are which without talking to the people involved, but
involved. But my guess was I had probably found 75 to 80% of all of the bad records. So it seemed
to me I could use the bad records as a way to find the tagging mechanism. Now, when I looked at
the data field and asked myself, so which of these data fields is the most logical to use as a tagging
field, I settled on the ID numbers. And the reason is because the ID numbers are unique, or at least
they're supposed to be unique. The names are. You can have a number of John Smiths, for instance, or
my name, Andrew Paquette. I know of several Andrew Paquettes in America and a couple in Canada.
One of the Americans, by the way, is apparently a career criminal. A friend of mine in California
sends me newspaper articles about this guy every single time he steals a car.
So you can have the same name. You can also have the same birthday. You could even have the same
name and birth date, or the same address. Every time you add another layer, the complexity becomes
a little bit less likely to happen, or to happen in volume. But it's possible. But the ID numbers
should be completely unique. So I decided to look at the ID numbers. And the first problem is that
the state ID number, which is the more important one, is eight digits for everyone. And as far as
I could tell, they appeared to be completely randomized. What the programmers were looking at
is, as you can probably see, it's very difficult to find. The reason was that, from his point of view,
if you did put a tag in there, somebody was bound to find it. And so that would not work.
So it turns out there was something there. They did find it, but it wasn't a tag. It was something
far more clever than that. So can you please go to the next slide?
So I'm actually moving along with you. Okay. So actually, I already talked about this in the
sentence. So let me go farther. Okay. So what I found was algorithms that associated the
county ID number with the state ID number by using a very specific counter, as in the
algorithm that causes numbers to be associated in a specific and reversible way. So that association
is something that can be extracted for the purposes of identifying special records. But because
they're not actually altering the numbers, no one using the database would have any idea that this
association was made. It's kind of like making a bunch of secret narratives. So it's like,
kind of takes the database for all the voters in Australia, let's just say, and assigns each of the
women to a certain man as a marriage, right? It records this secretly and doesn't tell them
that in their database, these people are married. But the way they do it is something that they can
reverse. So they can always know who's married to who based on their database and that information
is something that they can use to identify those people uniquely. So they did something like that
in New York's federal and there are four algorithms. So I've made a chart here or an
illustration just to illustrate what they look like because they hit them very well by
dividing the state space into partition. So if you look at the way this is laid out, the county ID
are on the x-axis and the state IDs are on the y-axis. Okay. And we have four patterns.
We've got the button shingle metronome and spiral. Now I call these spiral metronome section
in range and the rest of it is out of range. And the reason I describe it that way is because the
in range numbers are ordered. They have a very specific, highly disciplined, mathematically
precise order to them and they're deterministic and reversible. The out of range territory has a
pseudo random quality that may be deterministic, but I, if it is, I haven't figured it out how yet.
I can see them and I can see that there are different patterns, but I haven't been able to
solve those algorithms yet just because they have the pseudo random quality here.
But the point is by mixing the four algorithms this way and in such a way that only people who
understand the algorithms would be able to identify numbers that's belonging to,
say, the shingle versus the tartan or the metronome, is that it actually creates the equivalent of
flat so that you would not be able to see that there are any algorithms. So for instance, if I
asked for all of the ID numbers for Clinton County, New York, it would include numbers that use
all of these algorithms. And since they're all mixed together in the county, I would have no way
to detect any one of these algorithms because they're only visible if I see all of the counties
together. So this partitioning of the number space was the first problem I had to deal with.
But once I did that, and let's go to the next slide so I can show you what it looks like.
Are we changing slides?
Seconds, Andrew.
Yeah, can you change the slide, please, to the next one? Thank you. Okay, so now we're looking at
what the spiral subject partitions look like. So you may recall in the previous slide I told you
there are four algorithms. The primary algorithm that I've been dealing with is the spiral.
And if you look at the image on the right, that shows how the counties are broken down. So what
it does is it gives a certain range of numbers to each of these counties. I'm using a three character
set of letters to identify each one. So it looks like it's in any county, Wyoming County,
County of New York, etc. And on the left, you see the actual number ranges that are assigned
to those counties. Now, they had another layer of optimization added here. New York State has
assigned what's called a county code to each county. And this code is based on an alphabetized
list of the county. So Albany County, which is the highest in the alphabetized list,
is county number one. And Allegheny, which is the next in the alphabetized list is county two.
Yates, which is last, is county number 62. But if you put the numbers assigned to these counties
in SVO ID order, which you see here in the looks like the fifth and the sixth columns,
it scrambles the county code. So if you look at the county codes on the left, they're in
basically a random order. I don't believe it's really random, but I haven't figured out what the
order is. So I'm just saying it's scrambled for the time being. But that, by the way,
prevented me from seeing these ranges for, I think it took me about a week to see that this
was going on because I was expecting that Allegheny would follow Albany and Bronx would follow
Allegheny and so on. So I was looking for numbers that weren't there because they had scrambled this
list. So let's take a look at what the spiral actually looks like in the database. Please go
to the next slide. Okay. So what we have here on the left is a list of numbers that have been
sorted by looks like the county ID number. Okay. So if you look at the county ID numbers,
although they're not consecutive, they are sequential. Okay. And this is because they're
missing county IDs. But if you look at the gap between the state ID numbers, you notice there are
a bunch of 11 and then there's 12. Now the way this looks, and I've done a lot of research on this,
so off the top of my head, I kind of tend to forget which view it is where they're every 10th row and
which view is every 11th row. I think in this case we're looking at every 10th row. But basically
what's going on here is they have scrambled these numbers in such a way that they're assigning to a
consecutive list of CID numbers, a list of SBO ID numbers that are consistently 11 units apart. And
then on the 11th number is going to be 12 units apart. And every 100th, it's going to be 111 and
every 1000th between 1100 and 1100 and every 10,000th of the 11,000 111, et cetera. So that's
what these rep units come in. Now the reason every 10th record has a rep unit plus one is because
that's making space for a rep unit from a higher order. So in this case it would be for a rep unit
in the 111s for instance. And when you get to the higher order rep unit, you start seeing 12
in the middle of the block of 10, but they always appear in exactly the same position. So if it's 100,
it appears in the 9th position and if it's 1000, it appears in the 4th position and if it's 10,000,
it appears in the 3rd position. And if it's 100,000, you get a 100 and a 10,000 in the same block
or something like that. Now what this looks like if you look at the CID numbers is the image on the
right. And this is why I call it a spiral. So what they've done is they divide the numbers into
powers of 10. So in this particular case, 11 corresponds to literally the number 10. But
111 corresponds to 100 and 111 corresponds to 1000, etc. So if you look at the CID numbers that are
assigned to each of those columns, you see that they make a spiral pattern. So the lowest number
is zero and then the next highest number is 10,000. You notice, look at the little arrow here,
you go 7,377 to 7,387 and it goes down to 7,203 and then you go to the next row, which is 1000.
And now all of a sudden, the next number isn't at the top anymore, it's at the bottom. There's a
reason for this, but I'm going to skip that detail because there's a lot of women can talk like that.
The numbers continue consecutively until 7,383 and then that cycles back up to the top of the row
and then goes consecutively until it hits this number. And then it continues doing that,
making essentially a spiral pattern in the number. So that's one calling the spiral.
Next slide.
And there we go. Okay. And they do another thing. This differs county by county. So not every county
does this. And I'm actually showing you two transformations. Some counties do one, some
counties do the other, some counties do both, and some counties do neither. And there are actually
a couple of counties that are... Okay, Albert. Although I'm not the moderator, so it's up to him.
And some counties actually do transformations that are unique to those counties. I'm not going
to show those because they're not as generic as these two. So this is a CID transformation. So
what they've done here is they've taken the CID numbers, which if you look at, let's see, it's
count one, two, three, four. Okay. And you look at them, they don't appear to be in order. But if
you look at the short ID, those are in consecutive order. Okay. So if you sort by short ID, you derive
what the county sort order is. Okay. So let's just look at this 149777. Okay. That's the third item
down, right? Right under it is 14978 and then 149783. Right? So you've got a six-digit number
followed by a five-digit followed by a six-digit. Okay. So these are going up and down by an order
of magnitude. Right? So those don't appear to be related. But then, wait a minute, let's look here
at this 1055 to highlight it. And then you go down 10 and 11, you get a 105500. So these numbers are
actually very closely related. Look at this, the 1498 and then 14980 and then 149807. What they've
done is they've decimalized these numbers. Okay. So I've gone ahead and I decimalized the numbers.
You look at them sorted by decimalization and you see now these are in perfect order because by adding
a decimal point to the left of each of these, which by the way is an improper way to decimalize
these numbers. Okay. Because it actually changes the values of the numbers. For instance, a 10,
a thousand and a million all have the same value when they're decimalized. They're all going to be
0.1. And by doing that, a million will actually sort before two. And two is obviously a smaller
number, but when it's decimalized, it's the other way around. So what they do is they decimalize
the CID numbers and then they sort them that way. And then they apply those numbers or map them
through the SBO ID numbers after they've gone through the spiral algorithm. So in that way,
they're actually obfuscating the numbers at both of those levels. Now on the right, what we see are
a bunch of numbers from New York County. And what they did is they used an alpha transformation. So
their CID numbers have some of them anyway, have an alpha component. When I say some of them anyway,
I want to say that it's about 30 or 40% of all of their numbers have an alpha character. Okay.
So if you go ahead and sort these by state ID number, which you see here, these are all
consecutive numbers here in this middle row. And then you look at the CID numbers, you'll see
that the alpha that starts the number changes every time. Just like you see these numbers being
interlaced with the string that starts with 1055 on the other side. Okay. So it's the same kind
of transformation, but it's being done using letters. Now, the thing that makes this so tricky
is that not all of their numbers have an alpha character in them. Okay. So with that, now if they
did, it would be a totally different story because then what would happen is you go ahead and sort
these and it would sort all the A's and then all the B's and then all the C's separately from each
other. Right. But because they're mixed, what happens is you have these alpha numeric
numbers that are sort of kind of in the middle of everything else. There is absolutely no way
with any tool I am familiar with to do this. You can't reproduce this. It's impossible. The
only way to get this is to write code that specifically adds these alpha characters to
these numbers and puts them in this order. It has to have been done intentionally like that.
And there's literally no way to reproduce this order other than, well, okay, there is a way. It's
by sorting by short ID, but you can't do it by sorting the CID numbers. You have to sort the
state ID numbers. And the only reason that works is because of the algorithm they use to assign
these things. So in my opinion, this was very tedious. Now, again, in some cases, what they did
is they did both of these things. So you have both the CID number being decimalized and you have an
alpha characteristic in addition to that. And let's look at something else that you might find
interesting. I don't know if any of you guys noticed this while I was bothering on, but the
registration dates, take a look at those. These are all January 1st. Now, I don't know about you, but
in America, January 1st is the day when most federal buildings are closed.
Now, I have had a very poor explanation for this by actually, it wasn't given to me directly,
but it was something I heard them say as an explanation in a state board of elections,
and they made it public. But they explained this as young drivers who, when they got the driver's
license, they became what's called pre-registered. So they're not able to vote legally, but their
information center system is automatically activated on their birthday. So if they happen
to have been born on January 1st, then it would look like they've been registered on January 1st.
However, this applied to about somewhat less than 5,000 people who actually had a birthday
of January 1st. But there were almost a million people who had a January 1st registration date
in the database. So this only applied to about 0.05% of the full database. This is not a very
good explanation for where I come from. Okay, so let's go to the next slide.
Yep. Okay, I hope you guys continue when I take a drink of water so they can help.
So what they do is they're stacking the deck, and then they use the shift type, or essentially,
to do what they're doing here. So this block of numbers that you see on the left is my solution
to the algorithm, and it works. So this is how they do it. If you have this, and you have the
formulas that I put in each one of those cells, you would be able to predict how they're going
to map all the numbers to each other. Okay? So what they do is they start with the minimum and
maximum values for the range for that county. Now, if you recall, and I'm not going to make you go
back to it because it'll be complicated directing me that way, but I gave you the list that showed
the ranges. SBO ID number X to SBO ID number Y is, for instance, Allegheny County. Okay? So they had
to hard code what those ranges were going to be. Okay? And then what they had to do is they had to
calculate how many numbers were in that range. Okay? So that calculation is pretty easy. It's
maximum minus minimum plus one because it's inclusive. These are actual things, numbers.
And then what they had to do is they assign one to the minimum value, which is going in a zero
column. Now that that number is assigned, it's no longer available. So the range has to be adjusted.
So it goes from range 969351 to 969350. Okay? Now what they do is they go to the highest rep unit.
Notice they go from the minimum to the maximum. Okay? So in this particular example, the highest
rep unit is 111,111, which goes in the 100,000 power column. Okay? So now what they have to do
is see how many times that rep unit fits in this adjusted range, which in this case is eight. So
now they subtract that eight from this and they get this new adjusted range. And they keep on
doing that all the way down until they've assigned all the numbers to one of these columns. Okay?
And then what they do once they've assigned these numbers is they shift the numbers. Okay? But the
first step, I'm going to show you the shift in just a second, is stacking the deck. And the way
they stack the deck is by making these columns. So in this case, one, two, three, four, five,
six, seven columns. So this is like a seven player game of poker. Okay? Where each one of these
columns represents a player. So what they're doing is they're placing the equivalent of cards,
that is to say group of numbers, that are going to each one of these players. And so all the
cards that are 111,111 numbers apart are going to go to the player in the 100,000 position. And in
the same way, all the numbers that are 10 apart are going to go, or rather 11 apart, are going to
the player in the 10 position. Okay? So that's stacking the deck. But they actually make it a
little bit more complicated in the way they interlace these numbers. So we just go to the next
slide. Okay. Oh, wait. There it is. All right. So this is the Caesar cipher at the top. It's
known as the shift cipher, which is one of the easiest forms of cipher you could use. And pretty
much everybody learns this on day one of cipher school, or at least that's my guess, considering
what I've read on the internet. So what they do is they have the full alphabet, A through Z.
They shift it to three characters. Now, of course, you can shift it to any number of characters, but
the traditional Caesar cipher, you shift it to three. And this pushes the X, Y, Z out of place.
So you put those at the beginning, and now you map them. So the A is now equal to X, B is equal to Y,
C to Z, et cetera, all the way down. So that's what a shift cipher is. So what they do with all
those columns is, you see here that, now in this case, I'm using a group of numbers that doesn't
have enough numbers to go to 100,000. So it starts with 10,000 here. Okay. So what they do is they
shift all of the numbers by three quarters of a rep unit, which is, in the case of 10,000,
I'm blanking on it for a minute there, 8,333. And then 1,833, and then 838, and then one. Okay.
But they've also got something else hard-coded into the system, and that is that the last number
in each of these rows has to be in rank order a three-quarter rep unit. So if you go back to the,
let's go back to the previous question for a second. Okay. So now I have to go back there.
All right. So if you look at each one of these columns, if you look all the way to the top row
where it says min, okay, so for the 100,000 columns, that number is the minimum number plus,
in this case, I think it's 83,333, and then the 10,000 columns plus 8,333, et cetera. Okay.
But this is important. If you go down, you see this AID, you see the AID all in caps, you see
a first and then high and then low and then last, right? Okay. So that is related to what I was just
showing you. The AID is the algorithm ID because the algorithm actually creates an ID in order to
do the sorting process. And the reason I know that is because they've hard-coded it that the last
number in each of these columns has to be one of these three-quarter rep units. Okay. So, and that
is after it hits nine. Okay. So in this case, the 100,000 row or column rather is not cut because
there aren't enough numbers, but once you hit the 10,000 column, they are. So this is cut at 83.
This means the 83rd number. So you count from zero, one, and then you count eight more numbers here.
It's nine. And then the number after nine, notice, is 10. That's eight cut low. And then you go down
to the bottom and that's 83. And then it cycles back up to the top where the 84th number is the
first number in this column, goes down to 96. And from there, you see the spiral. Now it goes to 97,
which is the low cut on the next column, it goes to 833, et cetera. Okay. And notice how these
three-quarter rep units keep going up all the way across. So that's the shift part of the Cypher.
So let's go to the next slide, please. Is this one missing ID numbers with spiral or this one?
Yep. Okay. Nope. Nope. Nope. There we go. Okay. So now I hope you kind of understand how this works.
It's actually got a few details I'm not talking about again, because
the details I'm giving you are complicated enough. I don't want to make it worse. So in
this particular case, I'm able to do something because of my knowledge of the spiral that I
should not be able to do. Okay. I can tell based on your ID number, what numbers have been deleted
from the database and who they originally belonged to. Okay. Now, if I was somebody working for the
county or the state, and I wanted to know that information, but I didn't know anything about
the algorithm, it would be impossible to do. And if I tried to use the method that I'm using,
again, without knowledge of the algorithm, it would also be impossible. And the reason is because the
spiral shingles, metronome and tartan patterns are all intermingled. So I wouldn't be able to
recreate the original sort order of the numbers that's required to find the missing CID numbers,
because I have discovered that all of the missing records are cloned. Okay. So what I can do is
this. So I go ahead and I work out the solution to a county's records, right? And I'm doing that
using the method I showed you before. What that does is it gives me an opportunity to calculate
what the numbers should be. And then I compare them to the numbers that are actually there.
And that tells me when I'm missing numbers. Now, you could say, and you'd be right,
well, you could find out which ones are missing as long as you know the range for that county,
because all the numbers are assigned, right? Well, I would say to you, no, I don't know that all the
numbers are assigned at that level. All I know is that there are those numbers are assigned to that
county, not whether they were assigned. What tells me they were assigned is the ID number.
So once I've got this arranged, what I've done is I've gone ahead and I've created these black bars,
highlighted columns where I have calculated that there should be a state ID, but there isn't one.
Okay. But I do notice that when I look at the actual state ID, the numbering continues
in the way I predict based on my projections, right? So then what I do is I take a look at what
the CID number was supposed to be. Okay. So in this case, there's no SBO ID number, but I see that
the difference between the two CID numbers that bracket it is this number in the middle. So in
this case, it's 1,086, it jumps to 1,088. So obviously it's missing 1,087. So I looked up
the ID number 1,087 for that county and I find who is associated with that number. And at that
point, the person on the other side can say, well, that's not a deleted number. What it is,
is it's a number that's been assigned to a different person, just as illegal.
But the thing is I also have the benefit of having seen multiple databases and I know for sure that
these, what they've done here is they've taken another SBO ID number, actually the missing SBO
ID number that is associated with this CID number and another SBO ID number. And they've gone ahead
and deleted this SBO ID number leaving the other one. Okay. And that tells me that these are all
clones. So this could be their way of covering up the former existence of clones. But the problem
is once they do this, they're deleting the evidence of whatever crime might've been committed with
that ID number. Now, of course, this is assuming crime was committed, but I think it's
plausible at the very least. So for instance, if this missing record was used to vote illegally,
okay. And then they delete the number, but they leave the rest of the record now associated with
a different number. And that new record doesn't reflect the voter history that is now missing.
Then you would have lost all your evidence. Yes. Did you want to say something?
No, keep going.
Okay. I'll just say that was just me. All right. So this is kind of interesting that I can use my
knowledge of the algorithm to learn something about people in the database that should be
unknowable based on their number alone. Okay. So let's go to the next slide, please.
Okay. So this is what the AID looks like and how it's organized. I really want to explain all this.
Okay. So if you look at the AID number, they have all these like critical points that are important.
Right? So you've got your number one, number eight, and 75. Each one of these corresponds to
a distance to the minimum SBO ID number. That's quite interesting. So the first AID is one unit
away from the minimum number. And then you've got the eighth one is nine away and 10 is 11,
et cetera, et cetera. And actually I could see a mistake here. The 75 is actually 83 apart, not 82.
There was a missing record when I made this. So I wasn't aware of that. But anyway, the point is
that the AID is hard coded into the algorithm. The spiral is proven to exist. There is absolutely
no chance whatsoever that this could accidentally find its way into the state voter rolls for 59
counties. And by the way, I say 59, not 62 because three counties use a different algorithm, which
we'll get to in a little bit. But the point is here that these can be used for tracking data.
Is that AID is effectively a third ID number. And that ID number is not going to be known to
anybody at the county or the state level who doesn't know anything about the algorithm. And
everyone I've talked to at those levels has no idea what the algorithm is even there. And one guy
actually has expressed skepticism to which I just replied, look, you'll find it. And by the way,
just in case you guys are curious, I shared my findings with other researchers, at least two of
whom have independently verified this with their own data. So I asked them, I said, look, I'm not
going to send you the version of the voter rolls that was obtained for my research. You get your own
copy. Okay. So a lady in North Carolina or South Carolina, I forget which, North or South, it was
one of those. She requested the voter rolls directly from the state and got them and was able
to reproduce exactly my findings in Schenectady County. And another researcher in Florida did the
same thing. So we're talking multiple different versions of the voter rolls all show this.
So it's there. Now, the thing is, this does not tag each record with the fact that it's cloned. I
have been completely unable to find a clear and convincing link between having a specific number
and being a counterfeit record. However, it does provide a very clear and convincing new ID number
and that ID number can be used to access all the records. So what better way to track records,
to do it completely covertly than by giving all of the records, good and bad, a new ID number that
nobody knows is there. Okay. So then what you can do is you can have your unauthorized copy of the
database and you can go ahead and use these new ID numbers to track everything. And that way,
you know, which are good and bad and the information, which is good and bad is never present on the
publicly available system. Google is actually done. Is that I can't prove that for sure unless I have
access to that other database, presuming it exists. And if you're all meeting my defense
guys, you probably have a couple of times on that. So if you would please go to the next slide.
Okay. So by the way, pardon the frequent sips of water. I went swimming every time my body
is inundated with chlorine. I need to drink a lot of water. Okay. So now what we're looking at is
one of the side effects of the shingle algorithm. The shingle algorithm is, I would say, probably
the most suspicious of the four algorithms. Now, if you look at the image or the scatter plot on
the left, you're looking at the out of range active record. Okay. The SPO ID number is on the
Y axis. The CID number is on the X axis. This is how to normally do it. So if I don't say anything,
just assume that's the case. So what you should see here is when you look at the active records,
all of the numbers are vertically aligned. If you look at the next image on the right,
and this is just purged records, and this looks like almost 2.5 million records versus almost
6 million on the other side, this is only purged records. So what you see here are the same columnar
structure that you see in the active records, but you also see a bunch of horizontal lines.
Those horizontal lines are the shingle algorithm. Okay. Now, this is a very poor representation of
it because we're looking at, as I said, about 2.5 million records represented by, what, a couple
hundred dots. I'll show you the structure in another slide in a minute. But what's going on
is that this particular algorithm creates very specific shapes that I can use to extract the
numbers so I know that they belong to the shingle as opposed to the tartan, which is these more
vertical lines. Okay. But the point I wanted to make with this particular slide is that the
numbers tell me that they're purged. Okay. So all of these horizontal records are 100% purged,
and they are also 100% of the shingle algorithm, which means that whoever assigned those numbers
using the shingle algorithm knew they were purged at the time they created the numbers.
Why would you do that? Because a purged record is ineligible to vote and must be removed from the
database after it's been there for two years, and all these records are quite old. There's no legal
reason or legitimate reason that I've been able to come up with for doing this. However, there is
a spectacular reason for doing this if you have nefarious intent, and that is that these become
basically a shelf of usable registration numbers for when you want them. And then what you can do
is you can go ahead and make them active, use them to vote, and then go ahead and deactivate
them after the election certified, and then they go back to looking like they're not doing anything,
but in fact they actually have been used. And coincidentally, a lot of these, and I say a lot
because I don't remember the exact number, but it's significant, are also numbers that have no
purge date. It's significant enough that I would say there's a causal relationship there somehow.
So this is kind of interesting. So let's look at what the structure of the shingle is. So let's
go to the next slide please. Okay, great. So on the left we're seeing what a normal sequential
assignment of numbers would look like, right? So if the numbers on the x-axis are CID numbers,
and then the vertical axis are SPID numbers, and they're assigned on a first come first serve basis,
you're going to get a graph that looks just like this. It's going to be a 45 degree angle ascending
line, okay? This is because the numbers are going up in both directions, right? So you get a request
for a voter registration number, and you get the next available number. That's the line you get.
Now you might have some gaps in the line, because let's just say you're
Stoke-Harris County, and Brooklyn or Kings County goes ahead and sends in a bunch of new registrations
in the middle of them dealing with your request. What's going to happen is if you look at only
Stoke-Harris records, you're going to see a gap, because those numbers would have been assigned to
Kings County, and then you go back to your numbers. But it doesn't really matter that there's a gap.
What matters is that they are still going to continue to ascend. They're never going to go
backwards in time, okay? But the actual shingle algorithm does what we see in these upper two
images on the right. It creates this zigzag pattern. Now the interesting thing, and then it just keeps
on overlapping itself. Now the thing that's interesting about this is that the numbers go
up and down, okay? So if you look at the first number, right? That's already higher
than later numbers in the sense that you see this number one, and you see 11, and it's a 21.
The 11 has a lower SBOID number than the one, okay? So as far as the county is concerned,
they're actually counting backwards here, and they do this over and over again with large
volumes of numbers. And if you look at the blue chart on the bottom right, okay? What you see is
what the shingle algorithm looks like and the Torton algorithm together. So these sort of
scattered numbers you see on the left, they're very sparsely arranged, and then the kind of block
of a column on the right, those are actually part of the same pattern. It's just that the pattern
on the left is less well developed. But in between, you have the shingle. And if you zoom in on the
shingle, it looks like these zigzag patterns that I just showed you. But the pattern made by the
Torton is more like a bunch of arcs. It's defined by three to five dots. So we have here two different
algorithms that were, by the way, assigned at the same time, okay? So that's what the shingle looks
like. So let's go to the next one. This is a metronome. Okay, so the way the metronome works
is it assigns the first number at one extreme of the CID range and then shoots all the way over
to the other extreme of the CID range and then keeps going back and forth, dropping numbers as
it goes in a semi-random pattern. Now, by the time it's done, what you get is a scatter plot like
this one you see on the right, which is almost all black, okay? It appears to be the equivalent of
a 2D computer graphics flood fill program. So this is, by the way, the first time in my life
I ever saw a scatter plot that looked like a flood fill, but that's exactly what this does.
And the interesting thing about the metronome is that it's assigned to counting 15, 30, and 60. So
that's 15 times 2 is 30 times 2 is 60. I don't know what the significance of that is, but based
on everything else I found, I do believe it is significant somehow. But the point again in this
case is that we have multiple algorithms operating in the same space, ostensibly for the same
purposes and also assigned at approximately the same time. So let's go to the next slide, please.
Okay, so this is the Tartan algorithm. Now, you might notice this is red and blue. The red dots
are the suspicious records and the blue dots are the records that, as far as we could tell,
were good. So this should tell you there are a lot of suspicious records. And in fact, the largest
number of cloned records are found in the Tartan region. So this is where you're going to find a
person who's got 18 records assigned on the same day with different ID numbers. So the fact that
these algorithms are present in the roles is a concern to me and I think should be a concern to
any authority who are responsible for maintaining these databases. I mean, clearly on the basis of
the presence of the cloned or counterfeit records and the presence of the forged signatures, or if
you want to put it another way, mechanically duplicated signatures, that all by itself
recommends a pretty serious investigation. But the algorithms are a different order of problem
because the algorithms allow external manipulation of the records themselves in a way that is almost
impossible to discover. And actually, I would say that without access to somebody else's computer
who's responsible for this, it would be undiscoverable what they're doing. All I can see
by deciphering the algorithms is I can see that something is happening. And I can kind of get an
idea of what's going on and what it's related to, but to say exactly what they've done is really
hard to do. So let's go to the next slide, please. Next slide.
Are you still there, whoever you are? Yes, I'm still here. Can you see that? I'm showing.
Can you advance? Can you advance the slide, please? Well, I'm advancing. Why were these
algorithms used is what I've got on the screen now. Okay, I should see on my screen, I'm seeing the
tartan. I should see other states. Good. Now other states is on the screen. Yeah, there we go.
Okay, so in Hawaii, what they do, they have a 32 digit UUID, which is essentially unbreakable. A
friend of mine in Pennsylvania discovered that they had tagged about 10% of their records,
interesting number, with a 12 digit algebraic sequence. So what they did is they took the last
12 digits of a little over 100,000 records. There's only a million registered voters in Hawaii.
And they replaced those 12 digits with the same 12 digit sequence on each of those records. So
what happens is if you're somebody who's working at the county clerk's office in Hawaii,
and you run across one of these numbers, it's going to look like all the rest of the numbers.
It looks completely consistent. You would have to have maybe 100 or 200 of these numbers right in
front of you. And you'd have to be scrutinizing those numbers very carefully in order to see
what they had done. It's easier to see when you put the numbers really close to each other, but
that's the thing is that what they did counts on the fact that they're going to be separated
because they're in different counties and they've got different last names and so on. So it's very
unlikely that anyone working their database is actually going to see this 12 digit tag that they
added to the end of those records. Now in Hawaii, they didn't give as much information in their
voter rolls as I have in New York. So I was unable to ascertain whether they were clones or not,
because they didn't have birth date information. But those records are suspicious and worthy of
investigation because that tag can be used literally to tell the difference between that
and good records. In New Jersey, what they did, they actually did use the cipher algorithm.
And this one I thought was more devious than the one in New York, but I figured it out a little
faster. But what they did is they have an 11 digit number and they broke it into three components
where they took the first component and put it in the middle and they took the second component
and put it at the end. And then they converted the middle component into a hex value and then
they turned the entire number into a hex value and then that's how you got the
number that it really was. So that was very complicated and I think I actually misstated
part of that. But that's the idea is that they're scrambling the position of the numbers and
they're using hexadecimal values in place of what they actually had. And then Ohio and North
Carolina, what you're looking at right now is a scatter plot of Mahoning County. Actually,
it's a partial scatter plot that shows a pattern that is very similar to the Tartan in some respect.
And North Carolina has something else that's also similar to New York's Tartan pattern. But
interestingly enough, in other counties in Ohio, they don't use this algorithm. They have
something else that looks exactly like that normally ascending line that I showed you earlier.
But this particular county is one of their larger counties where it would be easier to
fraud because you have that many more voters that you could mix the take those in with.
So let's go to the next slide, please.
Yep. Why were these algorithms used?
Next slide. Yeah, yeah, I'm not seeing it on the screen, but that's the slide I want.
That's up there. I presume others can see that.
I see other states.
I've moved from other states. There was other states and now come to why were these used.
Yeah, that's true.
Can you click?
Who's right? Am I? Are you? There you go. Now I see it. Okay.
I think it's your bandwidth problem, Andrew.
Oh, okay. So the thing is, is that there are no privacy concerns whatsoever. Now, normally when
you mask numbers or you encrypt them, you do it because for security or privacy. And in both cases,
what you're doing is you're either changing the numbers to something else. Like I've got a friend
who works for an insurance company and every time they send data out, they mask the ID numbers. And
he calls it masking, but based on what he said, they're actually encrypting them. So they're
turning them to a different number. But in this case, we're looking at public records that by law
must be made available to the public for examination and review. So there's no privacy concern. Also,
the type of manipulation that I'm seeing doesn't change any of the data at all. Therefore, there's
no security impact. So that is to say that the ID number that I see in the role associated with
any given person is the ID number that's associated with that person. So they don't actually gain
anything security wise by doing this. And the same thing goes for privacy. And it doesn't improve
efficiency. And the reason it doesn't, I'm thinking of the spiral right now, is because
the specific nature of the algorithm has a concentration of effect in the, you know,
less than 10% of the records. So if you want efficient search, usually what you're going to
do is you're going to divide the records in half and then divide those in half. So basically,
you make a decision tree where is it inside A or B. If A, then divide again. And then when you divide
that, it's like, is it in the A side or the B side? And you keep on going until you find it.
But when you divide it this way, where you're breaking it up based on powers of 10,
you're going to have to divide many more times to find the record you want because you're dividing
10 to 90 or 1 to 90 or 1 to 900 or something like that. So you're actually retarding the
speed of use. And on top of that, you're destroying normal relationships that might help people who
are using the database understand what they're looking at. So for instance, a very simple example
is if the registration date corresponds somehow to the number, people could look at a number and
say, oh yeah, that number is from the range of numbers that were assigned in the 1960s,
the 1980s. And they would be able to derive knowledge of the records just by looking at
the number. They could actually answer questions and save them time searching. So what they've
done by introducing these algorithms, it doesn't help the privacy, it doesn't help security,
and it makes it less efficient. So none of these things are good. And on top of that,
it actually adds data because the algorithm creates another ID. So this is another thing to
keep track of, multiplied by 21 million records, which is also a very bad thing.
So I'm wondering why were they used? Now you may think, well, it's pretty obvious,
they're using it for fraud. Well, I like to say it this way. I like to say, I don't know why they're
using it. I know it certainly can be used for fraud, but I haven't been able to prove that they
are using it for fraud. Nevertheless, I think there is very, very strong evidence here to justify,
at the very least of position, it's probable that these were invented and implemented for the
purpose of fraud. But at the very least that an investigation should take place to find out,
for sure, one way or the other. I do think it is completely fair to say that it is not reasonable
to assume that they're legitimate. Okay, so let's go to the last slide, which is just me asking if
there are any questions. And that's great. I'll stop the sharing now, Andrew.
That's fine. I'll put on my camera. Oh, my camera's already on. There you are.
It looks like it's not pointing at me. Wow, it's all stretched or something. All right. Well,
let's answer the questions then. So I'm available for that.
Very good. Well, traditionally, Steven asks questions. And Steven, show us your screen.
Steven, show us your screen. Yeah, sorry. Yeah, I'm here.
Show us your face. Yeah, sure. Yes.
Hello, Andrew. Hello.
Thank you for speaking to us. So first thing, I was very interested, well, I was interested to see
that you got your PhD, at least at King's College London. Is that right?
Yes. So did you? Can you hear me? Yes.
Your first degree was in what, Andrew? Oh, I don't have one. I'm one of those
special people who just skipped that. I left High School when I was 14.
Oh, my PhD is in education. I studied the development of expertise in
CG art. And the primary reason was I wanted to contest the presumption that a certain
amount of time is required to develop experience or expertise rather, because I had observed
many people at a young age or with very little experience becoming experts rather
rapidly. So I wanted to study how that process occurs. And I found that it happens when people
encounter keynotes and then understand them. And that can happen basically at any age with any
level of experience. When they encounter what did you say, Andrew?
I'm sorry, what did you say? When they encounter what? I didn't catch, was it keynotes you said?
A keynode, N-O-D-E. So for instance, in computer graphics, a keynode is understanding topological
relationships between geometric elements. Many CG artists do not ever learn how to do that.
But the ones who do develop this topological awareness is what I call it,
are the ones who tend to excel and become experts.
Let's see. So as much of an interest, how did you come into contact with King's College London?
You were born in America, were you?
Well, yeah, I was teaching at a school in the Netherlands, the Enhanteve,
which was a university of tourism. But then they created a game development program and hired me
to be their first director of the visual arts program. So I created the visual arts program
there. Now at the time, I had gone to college in the United States and I was studying at art school,
but without a degree. And that's just because I started getting hired and I was working.
When I was in the Netherlands, they said that was a problem. I needed to have a degree. So
I wound up writing a couple of books on computer graphics, which they used as my thesis to grant
me a degree. But then they wanted to get hired. So no, no, this was the school I was teaching at.
This is the school I was teaching at. So then they wanted me to get a higher degree
and I started applying for programs in the Netherlands. And I was hoping to go directly
into a PhD program, skipping a master's because by that time I had years of professional experience.
I'd written a couple of books on computer graphics and I was considered an expert by people in the
field. And eventually I discovered that none of the Dutch schools wanted to accept somebody who
spoke English and not Dutch. So I decided to try English colleges instead and I got accepted at
several. It was King's, Northampton and I believe it was Essex. And which was the last one?
I think it was Essex. I remember they were like in the southwest of the UK. I forget exactly where.
I see. Okay.
But King's was my preference and I'd already received acceptances from the other two. So when
I went for my interview at King's, I told them I have to answer the other guys tomorrow. So if you
make me an offer, I'll accept it because you're my preference. But if I don't hear from you soon,
I'm going to have to go with one of the other ones. So they accepted the proposal and I went
from there. But that was a lot of work. It was much more than I expected. I assumed that because
I was already an expert in the field and had written a couple of books that it would be easy.
But it turns out a research degree at King's College is something they don't play games with.
Is it something about the end?
It's not something they play games with at King's College.
I see.
Sorry.
I looked at some pieces written by other people at other colleges and I realized when I read them
that they would have not been passed at King's College. They would have failed.
No.
In fact, actually I would have failed them.
You know what? I'm having a very hard time hearing you.
Sorry. Hearing me at all or?
I'm hearing you but there's considerable loss of audio. So it's like fractions of your words.
I'm sorry. So anyway, with regard to that, Andrew, I'll try and speak clearly. Does that help?
So far, yes. Continue.
So those three places you mentioned, the three universities you mentioned,
the three universities you mentioned, King's College London is world class. The other two
aren't. So well, Essex is known for one or two things and Northampton may be full. But it's not,
you know, they're not in the same classes. King's College London. So that's what...
No, they're not.
Yeah. And the funny thing is I wasn't aware of the rankings of these schools when I applied.
And I didn't really care because as far as I was concerned, I was satisfying a requirement for my
job because my boss told me that due to a new law passed in or regulation passed by the Ministry
of Education in the Netherlands, I actually had to get a PhD to retain tenure. So I had tenure there.
And so I was going to go with whatever school accepted me. But then my boss told me, you know,
King's is actually better than those other schools. So you should go to them. So that's what I did.
Excellent. And fair play to King's for taking you when you hadn't got a primary degree. They took a
chance in their, you know, in their world, they'd be taking a chance, but they backed the right horse,
it seems. So what you did in your PhD at King's, when do you think... Could you have done... You
talked about very young people being very skilled at the kind of things that you're skilled in.
You know, when you look back to that, could you have done that when you were much younger
or I don't know how old you were at King's College, but I'm just interested.
I think I started at King's when I was in my late 40s. I'm 59 now. I might have even been 50.
But in any event, yeah, I think I could have done it when I was younger. And that's the thing is
that these key nodes, you have to be introduced to them. And this is something I'd seen in my
own career, where I've actually had several careers, and I've learned multiple disciplines,
and I've discovered that the way to quickly achieve my goal is to first find someone who knows the
answers to the questions that I have to have answered. So I look for a mentor, and then I
start asking questions and doing work and getting feedback until I figure it out. And then once I
have that, then I'm essentially an expert from that point forward. So when I got into comic books,
for instance, the key node was that comic books is not about drawing. Comic books is about
storytelling and knowing what to draw on the page. So I happened to run into a comic book writer in
Hollywood who told me his frustration with artists who think it's all about drawing and how it's all
about figuring out the camera angles and what to put in front of the camera. And as soon as I got
that figured out, I started working in the business. It's like that for pretty much everything.
Interesting. Yeah. So, and then you met Jerome Corsi or Dr. Corsi a couple of weeks ago,
did you? And that's when your problems began, as far as being censored was concerned or not.
Well, as far as my bandwidth is concerned, yes. I had never had low bandwidth problems. And then
all of a sudden, right around the time I met Jerome, now, of course, I'm not sure when it
happened because there was a gap of some months between the conversation with him on Zoom and
prior conversations on Zoom with other people. But I had never had a low bandwidth problem
until the conversations with him. And ever since then, every conversation I've had with anybody
has had. I'm sure, Stephen, it was monitored and they're suppressing him. They don't want,
they don't want what Andrew knows out and they're probably not happy that I'm working with them.
I understand that. Yeah. Well, that's what I was suggesting. But so, and that you only met each
other two weeks ago, is that right? It's a little bit more than that.
It's very, within the last month, in June, we met, we met in June, I can't remember the exact time,
but in June we met. And I got past Stephen's work, someone, the law firm in Akron, that Stephen,
this whole group, there's a group involved called United Sovereign Americans. And that's
the two women, a woman named Marley and a guy named Harry who runs that. And they brought Andrew in
and they had problems with Andrew. Marley is a particularly difficult person. It seems like to
me that Marley and Andrew did not get along. And Thomas Connors from the Mendelssohn firm sent me
Andrew's paper and he said, would you please figure out for me if this guy knows what he's
talking about? Well, I have a background, a mathematical background is very extensive and
I have a background in cryptography. And so I started into the paper that he wrote and published
in that journal. And I quickly understood what he was saying. And I really got into it very deeply.
And then I've called Andrew, we had a couple of conversations about it.
And Andrew demonstrated some of it for me. And I became absolutely convinced that he was right.
And so I communicated this to the Mendelssohn law firm. And actually, we've had kind of a conflict
with the United Sovereigns of America because they are going in a different direction.
And I decided with Andrew that I want to do the same thing I did with HSBC Bank. In other words,
I want to write a series of articles. First one was accepted by American thinker today.
And it will be published the next few days. And then we're going to write a series of articles
in which we present to the American people saying, why are there algorithms in the voter database?
And I believe one of my skills is being able to make an argument that is maybe difficult,
simple enough for the average person to understand. And so here, you know, the one of the
two or three lines I've been working on is that Andrew did a very good job today. I'm sure
having looked at the deck, I unfortunately couldn't hear the whole presentation. I'll
review it later. But I'm saying that there just should not be this number kind of sequence
imposed upon a database. And the number, the schemes involved here are National Security
Agency quality encryption schemes. As he says, they're not really specifically encryption schemes.
They're much more this denography. But you can't tell that they're there until you kind of an expert
way to detect them and figure it out. And Andrew figured it out. And when he figured it out, he must
have spent, he must have spent enormous time doing it. Probably spent a lot of sleepless nights,
got paid probably nothing to do it. But he conquered it and mastered it.
I figured I was and he got it, but he figured it out. And so then I'm saying to what next thing
I'm going to say to the American public is that and to world public, we have databases for credit
cards for banks, for mortgage companies that are remarkably validated databases and work so that if
you miss a month paying your credit card bill, you're going to get called and qualified to talk to.
If you miss it for a sequence of months, like six months, they'll send it to collection and
collection is going to hound you until you pay something. These are very effective systems.
But yet the voting systems in the United States, and I think worldwide, are intentionally
not validated, are intentionally full of errors, are intentionally full of records that are a mess
because they are all subject and they are designed for fraud. And the voting systems that we're
allowing to go are like mail-in ballots are inherently schemes that are subject to fraud.
And so therefore, we have created data systems for voting that are dysfunctional
because we don't intend to conduct fair elections.
But we're not going to say that this election was false or that election was false or that Trump won
2020 because then we're getting into problems of saying that I think the genius of what
Andrew found is that not only can you vote false votes, but you can certify them
so that a false vote requests a mail-in ballot. That mail-in ballot is printed with that number
and voted. When you look at it, that vote was requested and it voted so it's certified.
You don't know that it was false because you can't get that deeply into the record. All you know is
it matched. And what bothered me in 2020 was you could obviously see all the mail-in ballots
coming in and being counted in the middle of the night, but yet these elections were certified.
And I couldn't figure out how they were getting certified. And Andrew showed me they were getting
certified because the false records were identified in the deck where whoever was the card shark
knew where the marked cards were and could vote the marked cards in the number they needed at
any time they needed them. And so therefore it explained to me how mail-in voting fraud could be
done and certified. Okay, but again, we're going to just raise these questions because it's much
more powerful to say to the American people, like with HSBC, why are they running all these millions
of dollars through these accounts and closing them and that account had your social security
number and your name. You were formerly a customer of the bank. You closed your account. You didn't
know this. Why is that happening? Raising these questions is enough to make the people mad about
the system. And eventually some of the regulators have to pay attention because you've called into
question and undermine the integrity of the entire voting system throughout the United States and
maybe throughout the world. And that's my goal. And Andrew can validate it. And it's very similar.
John Cruz had the data from HSBC. He had the data. Andrew's got the data. And I'm going to
communicate the data with Andrew, like I did with John Cruz. And pretty soon we'll have regulators
at the Department of Homeland Security or others. I'm sure we already have them interested. And
they're already concerned about what we're going to do. So you're talking about, you've got new
evidence against HSBC or is this the evidence? No, I'm just using that as an allergy. I did it
then. I'm going to repeat that today. It's my MO, my modus operandi to get this communicated.
And when I found Andrew, I found the guy with whom I can do it. Just like when I found John Cruz,
I found the guy with whom I could do it. I knew they were laundering money. You can't run
a drug organization without a bank and the security agencies, the intelligence agencies,
and the finance treasuries run all the bank systems. And so they're in on it.
And I knew that I've known that studying into other materials going back into the opium trade
in the 1800s in Great Britain was running them in China. And HSBC was originally part of the opium
trades and they were doing it fraudulently then. So they were still involved. And I know that the
intelligence agencies are involved in the voting and they know this is going on. They don't want
it exposed. And again, rather than going public and saying, I can prove that, we're just going
to ask a lot of questions. Why would this be? Why would this be? Why could you use this to do this?
So how did the questions turn into HSBC being fined in the US in 2012? I think it was
$1.9 billion for money laundering, which you exposed together with Cruz.
And now, of course, they're asking their customers. They're saying that they have to
know what the customers are spending their money on. And I know this is happening.
The banks are the criminals, typically. The people who commit the kind of fraud that they are doing
with all these rules and regulations that bank officers, if somebody takes out more than $10,000
in cash, you've got to file a report. Those are just control measures. Those are just totalitarian
measures. Those aren't the people committing real money laundering in banks. The governments
are the criminals. The governments are doing the money laundering. So you begin to get to realize
that we're fighting in the war in Ukraine. The CIA was involved with the Bidens, the money laundering
in Ukraine. What we want in Ukraine is we want to preserve the corruption because they've got the
best money laundering scheme I've ever seen. They run things through Cyprus and they get rid of
trillions of dollars that disappear. And so you don't want to lose that asset.
So we fight the war. Keep that money laundering asset going for the intelligence agencies.
And so one of my themes in life is to expose to people just like Jack Kennedy being killed by
the deep state that we are living in a Truman show that the intelligence agencies are running
and they're evil. The voting is another example. So we're not going to hold.
The people who are going to win elections are the people that CIA want to win the elections.
Donald Trump was an exception and that squeaked by. They weren't prepared for that one. They
thought they had him beat. But the point was that we now have enough. Why do they pay $1.9 billion?
dollars. Even Aldous Huxley said this. I've written about this in the book on the
Anti-Globalist Alliance. These totalitarian schemes these governments build, and they're
very close to having this transhuman totalitarian system in place, can only be beaten when people
refuse to participate. That's the only tactic you can use to beat them. We're not sending our kids
to a public school about transgenderism. And so once the people say we're done with public schools,
public schools collapse. We're done with watching network news. We're done with
buying Budweiser beer. We're done with watching the BBC. We're done with buying Budweiser beer
of a transgender is going to be the guy who's the spokesperson. We're not going to do it anymore.
And we're done with going to a pediatric department in a hospital in the NHS in the UK,
which flies the gay flag in the welcoming area for the children.
That's right. And so then the governments have got to do something. And they blew the whistle on HB8.
Nobody went to jail, but they did pay the fine. And it's still going on. But it's another
brick in the wall to remove, to expose how they operate.
Now, I don't want to dominate the conversation because there's others with questions. I
want others to answer the questions. But this is-
Can I just ask Andrew, Jerome, what is the importance, Andrew, in your mind? What could
be the importance of what you've found? So I'm not saying what have you proved, because maybe
you haven't proved anything, but that doesn't mean to say that you're not correct.
I just wonder- Yeah, as far as I'm concerned,
what I can show and what I think is important is that the voter rolls are being manipulated
covertly in ways that even the people who are responsible for managing the voter rolls don't
understand. And that has to be problematic for voters for whom the voter rolls are meant to be
a safeguard against fraud. So what I am seeing here is a way to hide what's happening. So anytime
you have something that obfuscates, which should be transparency, you have what should be a
untrustworthy system. And it should be treated as such, basically discarded for that reason,
just as I discarded CNN when I discovered how biased they were. So if nothing else,
I would like to think that these findings lead to the discarding and possible regeneration of
more honest systems. Discarding what we have and rebuilding it.
Doesn't this point to a wider problem of super elites, if you like, who can be hired to
to manipulate systems on behalf of corrupt individuals who understand the potential of
the system? But the point is that you can't regulate them. So Andrew, the point is you can't
regulate them, it seems. Mere human beings can't regulate this stuff because it's so complicated.
So if you've got someone acting nefariously in a very complicated world, it's extremely difficult
to nail them down. Except by thinking in big, big steps, if you understand me. So
you're never going to get there trying to prove it on your own. But you could actually prove it
by default, if you like, by hypothesizing correctly. And Jerome is very good at that. And I'm kind of
reasonably good. So do you understand what I'm getting at?
Yeah, I think I do. The thing is, these computer systems are so complicated that anybody
who is nefarious, who gets involved, the potential for wrongdoing is so great that actually
nobody can detect it. So therefore we need to get rid of the damn computer systems.
So it's very convenient to have the computer systems. Yeah, exactly. So people need to understand.
Yeah, I agree completely. Well, the problem with computers is they multiply the possibilities of
fraud. You know, the funny thing about this, I'll just tell you an insight I had when I was something
like seven or eight years old and I first learned about election. I was thinking, given the number
of people in America, and given the number of people who have to manage those elections,
it is almost certain that there are tremendous opportunities to create fraud there.
And I have never thought that we should trust our elections just on that basis alone, because
as far as I could tell, the numbers alone argue against a trustworthy system, because the more
moving parts there are, the more opportunities there are to get in the cracks and gum it up somehow.
But also the wider potential for things that are very complicated, Andrew, which most people can't
really understand, you know, that gives potential for, as I was saying, multiplying the possibilities
for fraud. And for that reason, and for also, you know, if computers take over our lives,
like mobile phones and social media, so people, young people in particular, spending loads and
loads of time on the, and they're taking, their humanity has been taken away from them
by the thing that they actually love and are addicted to in the true sense of addiction.
And any other addiction would be regarded, you know, as dangerous, but not the mobile
phones and not the social media, and because everybody else is doing it, you know. And so
people need to draw the right conclusions, I think, and they're not thinking of the wider
implications of these computers, you know, and, oh, but people say, they're so wonderful,
you can find out this and you can find out that, it's so convenient, you know. Yeah,
but if it's going to lead to the destruction of human species, then it's not worth it, is it?
And we need to really think about this. Yeah, I agree with all of that. And on a philosophical
level, I'll tell you one of the things I discovered when I moved to Europe that kind of shocked me,
and I think is analogous to what we're seeing here, and that is that when I moved to the
Netherlands, they have a completely different way of planning their town. So as a result,
I could ride a bicycle to work and to get groceries and to literally do anything I wanted to do
from my house. And so I didn't own a car for 12 years and didn't really need one. A couple
times I rented one, but that was very, you know, far between. But the thing is that if I tried to
live the same way in America, there are only a couple of towns in America where that would even
be possible. For the most part, the infrastructure doesn't exist to, for instance, do farming the
way they did there to gather the vegetables and fruits and bring them to the people in the
marketplace and then to buy them and eat them and find their way into restaurants and so on. But
so the lack of infrastructure problem that I see right now that's analogous to our situation with
elections is we don't have an alternative way of thinking about elections. At this moment,
we are acculturated to believe that we have to have computers because they're so complex,
because there's so many people involved and it's just impossible to do it any other way.
When France, by the way, proved us wrong on that assumption just recently by counting all their
votes overnight and doing it on paper and by hand, and actually every other country does the same
thing. Our culture right now is designed around computers. If all of our computers failed
simultaneously, we'd have a lot of power plants and other types of industries that would immediately
stop functioning until they removed the computers from their systems, which all by itself I consider
to be an incredibly risky thing to do to make yourself dependent like that. But that's exactly
what our society has done. So we are actually right now in essentially the same situation that
a heroin addict finds themselves in where not taking the heroin actually causes physical
symptoms that are very unpleasant. So for that reason, it's very hard for them to get over
that addiction. And in this case, I'll just give an example from my own life. I'm watching,
I was a subscriber to Netflix and I was watching the programming become increasingly vulgar.
The profanity became very common. Pretty much every show was full of it, then every character
was full of it, and then the subject matter was obviously very biased in a lot of ways, et cetera.
And eventually I opted out and canceled my subscription and I went to Disney, which I thought
would be safer. And then Disney started doing the same thing. And then I canceled that and went to
Amazon where I could at least look at old movies and TV shows. And then I noticed all of the bias
in the old ones. I was really surprised to see how many were pushing the gay agenda, for instance,
as far back as the 1960s. It's really kind of a shock to see that. And I realized that for other
people who maybe feel a little less strongly than I do, it's really hard to let go of those kinds of
things. That those are the things that keep their minds in these very narrow tunnels of
that don't give them any room to see the wider world outside of what they're getting.
Absolutely. So I would use different words, Andrew. I think that human beings are a huge
disappointment to me over the past four and a half years because it's made me realize that
they have a predilection, a very dangerous predilection for dangerous cults.
Anyway, yeah, well, you actually I'll tell you something else that happened when I moved to the
Netherlands. At that time in 2006, there was an issue going on in Israel with a soldier that had
been kidnapped by Hezbollah. And they had been named Galeid Shalit, I think was his name. And
they demanded his return for I think it was something like a year or two, it was some long
time. And the other side refused to do it. So Israel gave them a warning, if you don't do it
by such and such a date, which I think was a 30 day warning, we're going to attack you. And they
didn't do it. And then they gave them a little bit more time. And they still didn't give him the guy.
So they went in and started blowing the heck out of Lebanon. And so it was right then that I moved
to the Netherlands, and I was watching CNN, and saw a program on this subject. And they had some
sort of press representative for the Israeli government and another one for the Israeli
government and another one for the Palestinian organization. They gave the Israeli guy, I think
it was, I timed this out with my, with a not a stopwatch, but my computer, I think it was like 35
or 40 seconds, during which he was basically attacked. They were saying, how dare you attack
a sovereign nation? And why did you do this horrible thing? And why are you committing murder
against all these innocent civilians? And the Israeli guy was like, what are you talking about?
That's not what's going on at all. And then they cut to the other guy from the Palestinian side and
gave him 12 minutes. And they were asking him all these softball questions like, how does it feel to
be the victim of this horrible tyranny imposed on you by the Israeli people? And so anyway,
I'm watching this and I was thinking, oh my gosh, I can't trust the media at all. I had never seen
CNN like that. And in Europe, it was actually more biased than it is here, if you can believe that.
But that's how it was. And it was really shocking. The thing is, though, that that revelation that I
had is something that I wouldn't have had if I hadn't moved to the Netherlands. And today,
I probably wouldn't have had it at all, because today America and the Netherlands are probably
the same as far as CNN is concerned. So it's tough. This has to happen on an individual basis.
So Andrew, I want to let the others ask a question. One last question. Do you think it's possible
that the present worship of computers by so many human beings and computers and mobile phones and
social media and all the rest of it, you know, this kind of non-human world,
do you think it's possible that the worship of computers in the largest
is going to bring us down, the human species down?
I think it's possible. I think it's possible, especially now that we have drones and AI.
Sure. Drones actually are, I think, one of the scariest inventions I've ever
heard of. And, you know, when they were first created, I remember one of my colleagues at work
coming in with a little helicopter, a drone helicopter. And at the time, I was thinking
it was cool. But then I saw drone robot dogs being deployed in, I want to say Iraq, some place in the
Middle East. And they were shooting at targets that they'd identified as hostile. But as I watched
those things, it looked like little robot dogs running around in a street crowded with civilians.
I was thinking, oh my gosh, this is incredibly dangerous because now there's no risk of loss of
life to the people running these robots and tremendous risk to the other side. Just very
frightening. Yeah, I agree with you. Yeah, I think it could bring down humanity.
So essentially, and you could say in the wider sense, he could say in the way human beings
are in danger from other human beings, hubris and lack of humility.
I would look at it just a slightly different way. As far as I'm concerned, the computers may be a
tool, but the real problem, and this might sound a little cuckoo to you guys, but as far as I'm
concerned, is atheism. Because I'm looking at people turning away from God and moral principles, and
that all by itself led to everything else. That's my opinion. And I started out as an atheist,
by the way, just so you know. Sure, there's no fear of accountability from God in the future.
Yeah, well, and also the preposterous arrogance of thinking that since God doesn't exist from
their point of view, that we are God, and we can make it. Exactly. Yes, well put. Very brilliant.
Thank you, Andrew, so much for coming on and for your brilliant insights, especially that last one.
Thank you so much. So Albert, I don't know where Charles is. He's in, it's early in Australia, so
Albert is from VAERS, and I think he might need you, Andrew. Okay. Hi, Andrew. My name is Albert
Benavides. I'm the creator of VAERSAware.com. My background is just medical billing for multiple
decades, and at one point I was a HMO claims auditor, and I think I was a very, very, very
you know, at one point I was a HMO claims auditor, and I think a lot of what I had to do
auditing for fraud in medical systems had a lot of similarities of what you just presented today.
And like one of the things when you presented your record, like the record that said,
you know, the status was duplicate or active, and I think you used a word, you're using a word clone,
like when I see this clone record in my head, I'm thinking, I'm correlating that. I'm like, man,
in medical billing we would call that a duplicate. Like you made reference, you know, like around
here, you know, doctors offices, the duplicate record is the bane of their existence. It's like
there's everybody has like 50 Maria Hernandez's, you know, so these duplicates. Is that what you
meant when you're, when you refer to these clone records? They're in effect kind of like, no,
I'm not. And no, and I specifically use the word clone because I'm aware of what a duplicate is,
and a clone is not a duplicate. Okay. And this is also because the nomenclature in New York
only allows for the one term, which means it encompasses both types of records, which doesn't
make any sense because they can't be distinguished. It's like calling us humans, but not distinguishing
by sex means we can't differentiate between men and women. And in this case, it means you can't
differentiate between legal and illegal. So in New York, a duplicate record will have different
county ID numbers, but the same state ID numbers. And this is allowed because the, you can move from
one county to another, provided of course, that the old county ID number is made inactive by
purging it. But the thing is, is that because you have the same state ID that goes with you wherever
you go, you can vote and other people can vote with confidence that people aren't getting an
opportunity to vote more than one. But a clone is where they take all of your identity information
and create another record that is exactly the same as the original one, except for one thing.
They give it another ID number. And so as far as the system is concerned, it's another human being,
which means it's another valid record to which they can send a absentee mail in ballot. And one
thing I didn't mention in my presentation, but I'll just mention right now is one thing I know is
in one particular case, and by the way, I didn't check too many of these because they're very
difficult to check. This is the kind of thing where other people have to get in their cars and
drive someplace and ask questions to find the answers. But one guy who had 25 registrations,
he had marked his voter registration document so that he was asking to have absentee ballots sent
to him, but they were being sent to a rental mailbox in a shopping center. So he had 25 IDs
in 25 counties, but he was getting 25 ballots, mail in ballots sent to a mailbox in another county.
That kind of thing can't be done with cloned records. I'm sorry with duplicate records,
but it can be done with cloned records. Does that make sense?
Yeah, absolutely. I was wondering if these election records and transactions, and as it's
flying through space from one database, from one computer to another computer, are they covered
under the HIPAA covered transactions?
You know, it's interesting you asked that. That was something I wanted to explore with
Marley at United Sovereign Americans, but that just got dropped through the cracks at some point.
But it seems to me that HIPAA's... What was that?
Oh, go ahead. Go ahead. I'm sorry. I interrupted.
Yeah, it seemed to me that the HIPAA requirements would have prevented the kind of problems that
we're seeing. And having actually committed these errors or having these errors committed
to the voter rolls would be considered a violation of HIPAA. But the thing is, HIPAA has to do with
patient privacy more than anything else. And in this case, the records are all public,
so it wouldn't necessarily apply to them. However, the standards of HIPAA, it seems to me,
are normal standards for database management. And on that level, they become relevant to the New
York voter rolls. Make sense? Yeah. One of the P's in the word in the acronym HIPAA is portability.
And that's kind of where I had my niche working for, you know, in my medical... I could say
medical billing, but I actually, for a good part, I worked at a laboratory for a good 10 years. And
I learned a lot of my electronic data interchange chops during that time. And, you know, with this
health information, you know, we're receiving reimbursements. So it crosses over and it
overlaps with a lot of the financial data, you know? So that's why this standard called ANSI
5010, with the acronym for ANSI, is American National Standards Institute, 5010 language,
ASC X-12 format. It's just the structure of how data is moving through the system and like the
rules. So then we're talking about these loops and segments and headers and trailers and packets of
information traveling, you know, on the information highway, like even kind of like when we get into
our own cars and we drive down the highway and we have a license plate on the front of our car and
in the back of our car, we now become that packet of information on the highway with a header and a
trailer. And a lot of that has to do with, you know, this encryption thing to keep things private
or, you know, stuff like that. So I put a link in there in the comments up above and it was called
the Washington Publishing Institute or something like that. And it's all the ANSI codes. And I was
wondering if you ever dove into that or familiar with that or you already know about that. But
those were like, gives you all the codes like the rules. I'll have to look to see. It sounds like
something I did look at, but I have looked into so many things now that it's kind of hard to know for
sure. One thing I will tell you, and I'm not going to say too much on this because I've got a
a friend that I have been consulting ever since I first discovered the algorithm
because I wanted his insights due to his interactions with very large databases because
he works at a huge company and a senior physician. And I wanted to compare what I was finding with
normal for him, but he likes privacy. So I don't want to go too far with this. But the,
but he his industry works with the government and he often has to deal with internal fraud
investigators. And the way it works is people on his team will flag something or he'll have an
idea for how to find something to flag and he'll ask his team to look for it. And once they've
found the flags, they'll go ahead and send it to their fraud team. And then they investigate.
He's developed tools for improving the security of their product because they have a very large
fraud problem where they can lose as much as several hundred million dollars
in a year or two fraud. So policing that is very important to them.
What he was telling me is that even some of the more minor things that I've discovered
would have been a major red alarm situation at his company that it would, they would drop
everything to fix it and find out exactly what happened, who did it, why it happened, et cetera,
and fire everybody responsible and then get it dealt with. But when it came down to the
the algorithms and some of the, and the port signatures and so on, he said at that point,
there are lawyers would be involved and they'd be sending people to jail. And he said there's
absolutely no question in his mind whatsoever exactly what the outcome would be.
Given his level at the company, he would be in a position to actually make that happen. So
that's my impression. But he's the one who mentioned HIPAA to me the first time. And I
started looking into it and realized that standard actually looks like something that would be
applicable here. But as far as the ANSI standard that you're talking about, I just clicked on your
link. And I think I'm not going to be able to concentrate on reading this while I'm trying
to answer questions. So I'm going to have to defer and answer later. I'm sorry.
No, later. Keep my number. We got the same passions, I think. And I'm glad to help you
any way I can for anything I know. But what makes me slightly unique in this little group here is
I'm an HMO claims auditor, medical data guy by profession, looking for fraud. So it's kind of
similar. But I was really, as technical as your presentation was, it was fascinating to me because
it's like my bells and whistles go off in my head. And I can't explain why. But it's just like,
yeah, yeah, I get that. Your algorithms, your spiral and your jingle, I was like, yeah, yeah,
but anyways, thank you. Well, I've got no problem. And thank you. And you too. Yeah, my impression
is that there are a lot of similarities between the type of findings I've made in New York's
voter rolls and what I've seen of fraud in the healthcare industry. So for instance, when you
have a cartel by a street and then go ahead and populate one half of it with a bunch of paid for
doctors and the other side with a bunch of homeless shelters that you encourage homeless people to go
into, and then you give them prescriptions from the doctors on the other side of the street for
drugs. And then you go ahead and build the insurance company for the drugs that you're actually not
delivering. Instead, you're giving them these addictive things, which is why they live on the
other side of the street. You have to create all these identities and you wind up doing essentially
what you did in the voter rolls here. That sounds familiar to you? Yeah, we had the same kind of
frauds even in lab, you know, and maybe these buzzwords might ring a bell to you, but we had,
you know, requisition forms. And then we had accession numbers. So when the request was made,
and then the accession got into our system. And, you know, at the fourth largest lab in the country,
there's, you know, there's like a hundred draw stations all over the nation,
people trying to enter in a record at all at once at the same time. So like, like down to the femto
second, the system would, would issue that internally an accession number. And a part of my
keeping trying to keep track of all these things, it's like, you have to figure out, you could kind
of figure out based on the timestamps with the accession numbers and the requisition numbers,
you know, when, because we realized like, hey, you know, call back to this draw station in Los
Angeles, we think that somebody is snatching like big gaps of, of, of recs of requisition,
like blank ones, because you're requesting new ones way too fast. And it's not matching
the volume of accession numbers that you're generating. So the, so we found a scam and we
found a scam in there, you know, like, oh yeah, one of our employees was stealing a whole bunch.
You just remind me of something that I didn't say. And I want to mention
is that to date, many of the, the, much of the research that's been conducted into the election
has concentrated on things that the other side can, to an extent, plausibly deny as
innocent or accidental somehow, or a glitch that's, you know, not anyone's fault. What the algorithm
does is show that it's all intentional. And that's something that's really hard to get around. You,
you just can't say that this alien algorithm that doesn't belong in the voter roll database
has no legitimate purpose for being there, could have possibly been a unintended artifact of some
other process. And that I think is actually a very important point. Oh, and I see a hand. Am I supposed
to, no, I'm not picking, the moderator's picking the wrong answers. Okay, go ahead.
Right on, Andrew. Thank you so much. Yep, no problem.
So that's really important point you made just then, Andrew. Next question from Diana Marie
Henry. Well, Diana. Thank you very much. I really, I'm horrified, of course,
but I think that, you know, I understand there's, there's great potential here for informing the
public, especially with the help of Jerome Corsi. But I wonder if you've also considered
Judicial Watch as a place to contact. They've had a lot of success, of course,
clean up their voter rolls. Yeah, let me just, let me just tell you something about my personality.
My nature, I don't go out and try to contact people. They contact me and I'm generally willing
to talk to them, but I usually don't like going out and networking, especially when I have to make
a living, which I'm not doing very well right now. So that's, that's my primary focus. However,
when I was working with New York Citizens Audit, I was interested in Judicial Watch
and I did talk about it with Marlee Hornick. And she did contact them. And as I remember the response,
and at the risk of being diplomatic, rather undiplomatic, actually, I think I remember Marlee
saying that Tom Fitton wouldn't take her calls for quite a while. And then finally, when he did,
he basically blew her off. But one thing I will say about Judicial Watch that is kind of interesting
is they came out with a lawsuit against New York City for having voter registrations that
needed to be removed. And they settled that case when New York City's Board of Elections
agreed to remove the records. So I saw the settlement agreement, which is published
on Judicial Watch's site, and they gave a number of records that were removed as of a certain date.
And I realized when I looked at that, that I had a voter roll database before and after that date.
So I could tell if they were actually removed or not. I suspected they hadn't been. And I checked
and I found, in fact, that they hadn't been. And that information, I tried to get to Tom Fitton.
I don't know if he ever got it, but I wrote an article about it for Red Voice Media.
And I talked about it quite a bit. It's time. And I think I may even have mentioned it. I'm
not totally sure about this in my Caesar Cipher article as well. But he never seemed to react to
that. But my impression was that although some records were purged, they were either
instantly replaced with more clones or they never deleted the records they said they deleted.
And yet, Fitton was claiming that as a group victory. So I don't really count it as a victory
when the people on the other side don't do what they say they did. And when by saying it, they
are committing a fraud against the court, which that's my opinion of what happened. I suppose
it's possible that there's some data out there that would make me change my mind. But at the
moment, that's my opinion. So that's my answer about Tom Fitton. Sorry. Otherwise, I like them.
I think they're great. It wasn't necessarily about Tom Fitton. I sent you some information
about their investigative reporter with whom I was attached. I was not in touch with Tom Fitton.
But I have double checked on Judicial Watch's agreement and then
they were, I guess, maybe deceived or didn't follow up. Anyway, thank you.
Yeah, I think they were deceived and then they either didn't. And I think they didn't follow up.
Why they didn't follow up. Maybe they felt it wasn't worth it because they got part of what they
wanted. I have no idea why. But I always thought that the fact that the settlement agreement appears
to be false and false by the county board of elections in New York City was much more
interesting than the lawsuit itself. And I've always been disappointed that that particular
story never went anywhere. Thank you. Thank you. No problem. Thank you.
So one outrage replaced succeeded by another. Amazing.
Oh, yes. Yes. By the way, Stephen, I do have a hard time hearing you. So
until you were into your fourth or fifth word, I hadn't heard a thing.
I don't understand that. No. Yeah. Okay. Sorry about that. So Peter Underwood is next.
That's okay. He's in South Africa.
Thank you. Yeah, I'm in South Africa. Hello, Andrew. Thank you so much for a wonderful
presentation. I'd really like to ask you, well, I get the impression on these meetings and everything
else I do. Researching all this area. I've written a book too about the global financial system,
which was sparked by the Cyprus bank robbery in 2013. I'm getting the impression, I think,
that Jerome said it struck a chord with me because it's dear to my heart. I got the
impression that we don't think we're going to win against this, that these guys own basically the
world or certainly the Western world. And he made the point that the best way or the best defense
is to not play the game, not comply and move away. Get out of the system. How do you feel about that?
I tend to agree, but I also feel that God has a role to play in this and that against God,
nothing can withstand God's will. So if God decides to help us out, then it really doesn't
matter what's going on on the other side, we're going to win. And on the other hand, I also feel
the same way. If he wants to punish us somehow and let us all run this course, then that's going to
happen no matter what we do. So we can only, but the thing is we can only behave righteously and
hope for the best as far as I'm concerned. I agree, Andrew. I really agree. Ephesians 6
tells us to take up the armor of God and I'm with you 100% with that regard.
We did face total extinction during the flood, so there's no guarantee either way, I suppose.
So I'd just like to ask you. Go on.
Oh, I'm sorry. There's some kind of a delay on this, which is making it difficult to talk
far over you. It's not your fault, it's technology. But as far as I'm concerned,
the fact that this is all ultimately in God's hands does not mean we sit around waiting
for somebody else to do something because we all have a positive duty to always be righteous
in everything we do and obedience to God. And so what that means to me is I can't let go of this.
I have to let people know what I have found because to do otherwise is to allow them to be harmed
by whatever is going on here. And that's not something that I feel I can ethically allow.
And I believe that with me and you and Jerome and Stephen and other people and Diana and all
the people on this call and elsewhere, eventually there will be that critical mass that's needed
to give God basically the tools that are necessary to fix this or to right this boat,
which ultimately I believe is going to happen. But I actually don't even care if it's going to
happen or not because either way it's up to me to always behave righteously. And so I'm just going
to take that and let somebody else worry about the rest because that's not my responsibility.
Does that make sense? Yeah, that's wonderful, Andrew. Thank you. I applaud that and share your
views. And articulating what you've just said, Andrew, terrifies the people we're up against,
absolutely terrifies them to hear people like you talking like that. But I respect what you
say and I feel the same way. Jim is the next question. He's a doctor and a radiologist.
And I really applaud your work. I'm not sure if you know about Leah Hoops and Greg Stenstrom
in Pennsylvania. They wrote a book called The Parallel Election. And in that book,
I have seen the book. Okay, I'd like to put you in touch with them because they need to just have
this information in addition to what they already have. Your algorithms are fascinating. And it's
very important to identify how the what I would call the demonic presence that is that maybe within
our intelligence agencies, the Department of Defense that have taken over. And we need to
align with the truth. I'm very I'm grateful for what you've told everybody because what we you
know, we're this battle is bringing the truth to this earth. And and not just keeping it to ourselves,
but bringing it to the opposition, including the intelligence networks and saying, Hey, please
start telling the truth. Please stop interfering and rigging the elections. And please go back to
telling the truth and giving this world back to God that rather than letting the demons take over.
And you know, I'm very glad to hear you say all of that. I'm sorry for talking over you just there,
but you hesitated. But my feeling is exactly that. And that's what I pray for when I go to bed at
night. I pray for truth for people for God to return truth to the world for truth to emerge,
because that is absolutely central to all of the problems that we're seeing.
And the thing about the demonic thing is business. I completely agree with you about that. And the
thing about that, that really, I find kind of shocking is I would have had a very hard time
agreeing with your that statement a few years ago, very, very hard. But as I look at all the
stuff that's going on around the world, not just in America, and I'm seeing how even the people who
are doing these things don't benefit from them. I'm trying to figure out who benefits. There's
basically only one one beneficiary. And that's just a second. No, it's sorry, it was not intended.
Good time. So here's the deal. I talked to a couple different times, we're working on stuff together.
So Craig Campbell, can you believe me? Sorry. There you go. Yes. And that's very important.
I can go into exactly why I think the Department of Defense has made a deal with perhaps actual
demons. And because there's very few reasons that the Department of Defense would be allowed to kill
off the people of the United States, allowed to genetically and people on this call know that I
speak about the genetic specificity of the SARS-CoV-2 spike protein, but be able to kill
off people in a genetically specific way. And what allows this to happen? And that is a really
complicated, really strange situation that I can talk to you about a little bit offline, maybe.
But the point being that we really need to bring the truth to this earth at this time,
because if we don't do it very soon in the next weeks or months, it looks like they are setting
us up for a catastrophe that is outlined somewhat in a movie produced by the Obamas called
Leave the World Behind, which has everything in it from, there's a lot of these incidents that
are going on, including cyber warfare. And the cyber warfare that you're dealing with right now
is really specific, not just to the NSA and the CIA, but also to a group called Unit 8200.
And are you familiar with Unit 8200? I'm not. Unit 8200 is...
The stuff you're talking about is making me think that if you really want the hairs on the end of
your neck to stand up, you need to look at my other sub-stacks that I don't advertise, which
has to do with my dream research, because I had some very interesting stuff up there too. And Jerome
has seen some of that, so if he's still on the line, he could comment.
Okay, I can contact him and try to get the information. So, right. But the issue is...
Again? I'm just waiting for you to finish. Go ahead.
Okay. So the issue is that we really need to... The cyber intelligence stuff is very,
very important, because if we don't stop the intelligence agencies, who seem to have been
not only rigging our elections, but infiltrating everything from our hospital networks to the
military to the township governments, then we are going to have a serious problem on our hands,
because... And they are going to false flag other countries like Russia, Iran, Iran, China.
And they're going to blame all these other places when the cyber powers are the United States and
Israel. And we know that. Yeah, well, I'm looking at this as an existential global threat.
Well, the existential global threat is the United States intelligence agencies, along with Six Eyes,
the six intelligence agencies of the countries that are being depopulated the most. United States,
Australia, New Zealand, Canada, United Kingdom, and the Six Eyes, Israel. And we really need to
come to grips with the fact that there are good and bad in all these countries. And we need to
bring the good people back to God and stop God's bad son or the fallen angels from allowing everybody
to be deceived and stop people for doing evil stuff, even though they're getting paid for it.
And that's really the crux of it. Yeah. Yeah, I agree. Actually, I think that that is the heart
of everything. If we bring people back to God, everything, all these problems go away.
Every single one. But we have to bring the yes, but we have to bring the truth to the people.
And we have to actually bring the evidence to the opposition. Any any evidence. And we were
talking with Kirk Moore, who has a case where the HHSOIG and the AUSA are suing him for not
giving the vaccines or allegedly not giving the vaccines or whatever. But we know that these
vaccines or virus, the SARS-CoV-2 spike protein is a bioterror weapon. And they, the intelligence
agencies aren't telling us that they developed it or they knew about it. They knew it was the
intelligence agencies know it's carcinogenic. I mean, how can they mandate that we vaccinate
people with a carcinogen? And if they're obligated to... Actually, I'm sorry. One thing that bugs me
about the vaccine that I don't hear talked about too much. It is talked about, but it's just not
as dramatic, I guess, as some of the other things is how it causes miscarriages and sterilizes its
victims. Because there's this larger agenda where every single front seems to be designed to
prevent people from having kids or to kill the ones that we do.
Yes, but if you know that Albert Borla, the CEO of Pfizer, is not a physician, he's a veterinarian.
All right. He's a veterinarian. And his specialty is two things. Number one, his specialty is how
melatonin protects the fertility of ram sperm. So consider taking melatonin at night. And number two,
his specialty is immunocastration, castrating animals with a series of vaccines.
Why is a guy whose specialty is castrating animals with a series of vaccines the head of Pfizer?
My gosh. And we know that if you get SARS-CoV-2, right?
And if you get...
That is interesting. I agree.
Well, I'm glad you like it. I'm glad you find this interesting. And I don't want to talk too
much longer because I've exceeded my time. But if that's the guy, if that's Albert Borla's specialty,
why don't we ask him how exactly his specialty has to do with Pfizer and why he is not giving
us the treatments and apologizing to the American people and to the people of the world for castrating
us in a genetically specific manner that may not affect him or the people who commissioned this
spike protein. And that's the real secret. You can't have a spike protein that castrates
everybody. You have to protect yourself and your children or the people who invented it have to
protect themselves and their children. Who did it? And nobody will tell, including the intelligence
agencies, will not say who invented the SARS-CoV-2 spike protein and on which supercomputer. And that
brings back to you, it's the supercomputers that are developing these things, the antidotes,
and we're not being given the antidotes. So I look forward to your solutions on how we prevent the
next one, because this 2024 election is going to be really horrific. And how do we stop? And as far
as I can see, it took us four years to figure out all this nonsense. We have to stop it from
happening this next round. How are we going to do that? How are we going to stop?
I think it's going to come down to non-compliance.
And here's the easy way. We have to vote, but the issue is they've got three-way election now,
which is so easy to throw. They've got instead a Democrat, a Kennedy, can't run as a Democrat.
I mean, my gosh, that's ridiculous. How are we going to stop a three-way election from being thrown?
Thank you.
So thanks, Joe. So I wanted to just say, so to your point, Andrew, about getting people back to God.
And you mentioned the other problem that, you know, when these people do not
have a God, then they create their own God. And the gods for many of these human beings
seem to be themselves. Harari being a good example. But so one thing that was interesting
about three days ago, I saw an email just happened to see one email which had a subject and
the 10 commandments are going to be taught in Louisiana schools again, which raised the question
in my mind, how in the world did Louisiana ever get rid of that requirement? It's a deeply religious
state, as I understand it. Yeah, that's my impression too. I can't answer that question
because I don't know. I grew up in California and I actually do remember when there was prayer
in school and then it was done. And at the time, I thought that was a good thing because I didn't
really understand what was good and bad. And obviously, yeah, when my children were small,
I had a very good friend who made a point of I didn't really know him. He was from he was Swedish.
I was in Sweden at the time. And but he was a good friend. And he said,
introduce your take your children to church and introduce them to at least give them the possibility
to read the Bible and stuff like that. And I said, Why, why do you mention that? Nothing else. He
said, because if you don't, he said, your children will create their own God, and their own God might
be a lot worse than the God we know about. So and I thought that was I'm not a Christian. I'm open to
it. But but I was brought up as a Christian Church of England. But I do have noticed in the last four
and a half years that the people who pray and who get comfort from the knowledge that God is with
them, they are our allies, because they are so brave, and they are prepared to take risks that
people who don't believe in God are not prepared to take. And so those are the people I really
respect and who I've regarded as my biggest allies, that almost to a man.
Sorry. Sorry, I wanted to comment on that. Because this reminds me of something that
I've always found rather curious about most entertainment in the form of films and
television shows. And that is if you if you look at what the worst possible thing is that they can
they can think of for their script to drive their plot, whatever it might happen to be,
is death or physical torture. And as far as I can tell, based on my understanding of the world,
the worst possible thing anybody can do is to be disobedient to God, that that is worse than
absolutely anything. There's nothing that even comes close to comparing with that.
And that's why the kind of threats that are levied against honest people don't affect them
quite as much. They might feel the pain, they might actually be harmed, they might not like it, but
they quite often, provided they're strong in their faith, are going to stick to their guns.
The reason is because they know that it is worse to be disobedient to God and his commandment
than it is to suffer whatever it is the bad guys might want to throw at us. That's just my feeling.
Yeah, so I just I've got a couple of points here. So Jim was talking to you about the
the guy who Kirk Moore, the doctor who's being, he said sued, but actually, as I understood,
is he's being he has been indicted by federally criminal criminal indictment, as I understand it.
And so anyway, that's very interesting. He was a brilliant guest. And you would get on well,
very well with him. And I wanted to ask you about the it seems to me that the the thing that makes
the discovery of the algorithms so important in your mind is that it takes away the plausible
deniability, which is often built into these intended crimes. You can see it in the 20s,
you since in the last four and a half years, there's been a lot of criminality, in my opinion,
but always there's this plausible deniability built into it, which actually makes things 10
times worse in my mind. Because it demonstrates the extent of evil. So so with the the interesting
thing about your discovery of the algorithms is that the plausible deniability disappears,
but it's still evil. So I just wondered whether you was in your comments.
Well, the thing that bugs me about it is that while that's true, I really wish I could take this
all the way to the finish line by gaining access to the computers that they're using on the other
side. You know, one thing that is causing a lot of problems for everyone involved with any kind of
election integrity investigations is that the officials on the other side aren't willing to
be transparent. So even though a lot tells us that they must give us certain materials,
they refuse to do it. And if they refuse, there's not much we can do. And what this does is it kind
of reminds me of when I was a little kid. And you've got a bully blocking your way at a certain
point, you know, the only way to get him to move is to push them out of your way. And I feel like
I'm just gonna call them the bad guys generically here, because I don't know who exactly is doing
all this stuff. But the bad guys are essentially daring us to push them out of the way physically,
knowing that we don't want to because then all of a sudden we lose plausible deniability on the
righteousness of our action. So it forces us to deal with them on a level where they have
a really strong advantage. But one good thing I happen to be seeing, or at least I think I'm
seeing is things seem to be turning in our favor now. It's very interesting to see that,
because they really did have all of the advantages. And they seem to be whittled down,
you know, a little bit more every day and bigger and smaller chunks. And I think that eventually
it's going to erode to a point where there's a total loss of faith in leadership. And this is
something I've seen at some big companies I've worked for, where when the subordinates lose
faith in their superiors, the superiors lose all power because they're hamstrung, they absolutely
can't get anything done if the people working for them don't want to do it. And it's kind of like a
strike without going on strike. I've seen this in more than one office, by the way. I've experienced
when I was working at Universal Studios, the people working there somehow intuitively realized
that our bosses were not, they didn't really know what they were doing. As a result, they started
doing less work. And this became a crisis of leadership where I was ultimately offered
their job, along with a couple colleagues of mine. The management at Universal said, would you,
Andrew, and you two guys? So Andrew, I worked for the military, the British military,
and some of my officers became very good friends of mine so we could talk openly. I wasn't military,
I was working for the military, but I wasn't military. And they said, and they told me that
the biggest fear in any officer's mind is when the men turn against the officers. So, you know,
and very often wars are ended. So the Vietnam War, I believe, was one of these, that the officers
were getting shot in the back by their own men. That's when they pulled the plug on the wars.
It's a similar thing to what you were describing. I didn't know that. Yeah, yeah. They get shot.
Yeah, I mean, when the county clerk no longer believes her boss has the authority to do things
that she knows are illegal, and so she refuses to do them or protects herself against it by
storing evidence away, if it's only Tina Peters in Colorado, they might be able to shut her up.
But if it's not just Tina Peters, but, you know, 20 and then 30 and then 40 and then 100 other
county clerks all around the country, that becomes an unstoppable wave. Because the one thing about
human beings that I haven't been noticing, or you have as well, is that we really detest it when
people lie to us. It's really one of the worst things that anyone can do to another person is to
deceive them. And with good reason, because lies put us all at risk. So if a leader is telling
you lies, it's very serious, because all the people he's leading, he's putting at risk of
losing their lives. So human beings sense when they're being lied to. And as you say,
it's extremely important to them, because they need to be able to trust the people who are
supposedly leading them. And now it seems to me that governments are promoting anti-human agendas,
which are against human nature. But they've also betrayed their countries in the last
four and a half years. These governments and politicians. Oh, definitely.
And the guilty of treason.
By the way, as far as I'm concerned, oh yeah. I'll tell you something interesting. When I presented
this material to some people at the Special Investigations Unit in Albany, at the end of
the meeting, one of the guys there said, this is treason. Just right out like that.
Absolutely.
A couple of the other guys nodded their heads in agreement. But the thing is, is that
the truth is something that once somebody realizes that they've been deceived,
they lose all faith in that person. And it is very hard to recover it, if at all. So the most part,
once you've been lied to, it's like a cheating spouse. It's like you never really fully trust
that person again. And I see that is going to probably be ultimately what brings this whole
Altschuh-Karz down. But to get there, all of this information has to get out. So like this stuff I'm
talking to you about, this is just one part of the puzzle. And it's going to reach a certain
group of people. And those people, a subset of them are going to realize, oh, hey, wait a minute,
this realizes I've been lied to. I can't trust them anymore. Okay. So that's great. Now they're
on our side. But there are so many other things that are going on simultaneously. They're going
to reach different audiences. All those things have to happen. The vaccine stuff is terribly
important. And it's causing people to open their eyes. And eventually, I believe our leadership
will lose all of their support from their subordinates. And at that point, the whole
thing is going to fall apart. That's what I think is going to happen.
Sure. But the problem with things falling apart, Andrew, is that, you know, what's going to replace
it? So it's a bit, you know, when the system is broken up and falling apart, there'll be a time
when the people are not governed. And unfortunately, people, human beings, what they are,
you know, they like to be in cults. And the problem is atrocities get committed when there's no
leadership. Do you see when there's a power vacuum? And that's the worry.
Oh, yeah. That's one of the most dangerous aspects of the election problems that we're seeing here.
Like, for instance, I'm convinced, and perhaps I'm deceiving myself to be convinced this way,
but at the moment, I am convinced that every election in New York has been invalid for the
last several years, possibly as far back as the year 2000. Meaning every single person who's been
in office, whether they actually got enough votes from the voters to put them there or not,
there's no way to know. And therefore, they may as well be illegitimate because all of the elections
have been controlled, which means the normal and appropriate remedy would be to take every single
person out of office, which means, as you say, we would have no government at all. We'd have no one
there to deal with making sure that our power is on and the lights are on and the police are getting
paid and all that kind of stuff. I agree that would be a problem. However, sometimes you just
have to do it. So the question is, is this the difference between smoking and not smoking where
you immediately start driving benefits from not smoking? Or is it more like taking out a very
badly placed malignant tumor in your brain? It has to be removed and it has to be removed fully,
but you have to be extremely careful how you do it. Now, it's more like the latter than the former,
but it doesn't change the fact that it has to be removed completely. And I do believe that is
absolutely true. I don't think any part of it should be left. And I hate to put it this way.
I don't want to sound like a tough guy or anything, but I don't know how America survives
if we tolerate this kind of thing. In fact, I find it very interesting that tolerance has become the
tolerance has become the anthem of the bad people. Because essentially what they want is you want,
they want you to tolerate any evil that they might happen to commit. And as such, I would say that
the tolerance is, as a slogan anyway, is a very evil thing. And it's something that we have to
turn around. We cannot say that, let's just say, I don't know what the denomination is all over
the people on this call belong to, but as a Christian or as a godly nation that we are going
to tolerate evil. It's just not going to happen. So Andrew, I think one of the key things in America
in particular, you know, so people who are Americans love America with good reason,
apart from the illegal wars and all that. But anyway, and the so people who are friends of
America feel this way, you know, that I think that one of the key things in America could be
if people like you started mentioning treason, as it should be mentioned at the moment,
at the moment, and after the unbelievable things that have happened in the last four years,
I really think that people understand treason, they know it's wrong. And then but they need
to be reminded, this one of the worst crimes that can be committed, at least in the United Kingdom.
So until quite recently, I think in the last 20 years, the only crime that you could be
get a capital punishment for in the UK, in theory, this was was high treason. But I think that's been
removed now. So it's so according to British, Britain, the worst crime is definitely treason,
worse than mass murder. And so I think we ought to emphasize that because I agree with you that what
you discovered, as I understand it, the key discovery of yours is the is the the algorithms.
And I think that when you mentioned that the reason they need to be interested in it and
outraged is that it's treason. The people who set up this system.
Yeah. So one thing about that particular word is that the people on the other side of this are
trying to redefine. And they're trying to narrow it to such an extent that it becomes very difficult
to say that. And they're also trying to say that saying something is treason is the equivalent of
inciting people to commit murder, because the punishment for treason is execution.
And by the way, I agree with you. But I'm just telling you what the other side of this looks
like. And the thing is, when I look at it, I think that the algorithm actually comes
about as close as we're going to get to showing that, particularly after look, I've only got one
source for this. So I don't I don't like saying this is a fact. So I'm just going to tell you what
the source said. And this has to be independently verified, make me feel happy about it. But
I showed this algorithm. I spent a lot of time with this guy, four hours in person and a couple
hours on the phone. And he said he'd seen this algorithm like it or the same one used in to
control an election in I think it was Iraq. But he said the Middle East, because he said that when
he was with military intelligence, and Saddam Hussein was overthrown, they they went ahead and
support of the election. And the goal was to make sure the bosses didn't come back to power. And so
what they did was they use this tool, which he said resembled the algorithm I found to control
the voter rolls so that they could ensure that the candidate they wanted to win would win,
which would mean that they're using this in foreign countries. Okay. And that gets us a lot closer to
treason, because now we're using something that would be treason there here. And also,
this might not be the greatest of arguments. But Jerome, are you still on the call? What do you
think? Am I right about this or not? Jerome, I think so he's muted though. Jerome, are you there?
He might have walked away briefly. Probably. Does that make sense to you?
It does to me. Yes, absolutely. But I can't speak for everybody on the call. But I just wanted to
what so you mentioned that there was some settlement agreement which was ignored. And that was a fraud
of the courts. Did you are you intending to take that up again, because that seems very important
to me. So if you get nowhere with, you know, if you if you question them about that, and
and nothing happens, then you've got proof that the that the court is being defrauded,
but actually the court doesn't care. I have a feeling that the court doesn't care. And
I also have a feeling that for whatever reason, judicial watch is uninterested in pursuing it.
I did publicize it by writing an article about it. And I have spoken about it to other people.
I have yet to get a reaction from judicial watch. And I certainly haven't had a reaction from
anyone else. But in my opinion, it's definitely worth following up on the explanation given in
the in the court documents, which are signed as you know, truthful and are a condition of the
settlement agreement are as far as I can tell, false by looking at the two databases involved.
Well, not least it shows that the rule of law isn't operating in
as far as that court is concerned anyway. But actually one of the one of the worst things
that happened in America was when lawyers started getting threatened. I mean, never mind
the disbarred which happened to Rudy Giuliani and a few others. But before that happened,
we had attorneys who worked for Donald Trump, who are getting threatened by local prosecutors,
saying that they would go after their law licenses if they worked for Donald Trump,
because what Donald Trump was doing was challenging election. And this is a very bad
thing, nevermind that Democrats do it all the time. But when I saw that, I was thinking,
hey, wait a minute, we have a right to counsel of our choice, right. But if they're threatening
the Council of our choice, then we no longer have the Council of our choice. Absolutely.
And they now deny us that constitutional rights. And I haven't seen a single person
write one word on that subject, which really disappoints me. I've read quite a lot about the
subject. I've read a lot of very popular commentators like Alan Dershowitz and
Jonathan Turley and a number of other attorneys who've opined on the subject, but none of them
have dealt with the fact that this denies us our right to counsel. And I suspect the reason may be
because the right to counsel is limited to, or at least it's described as a part of our criminal
code. And at the time, the cases that Donald Trump was filing were not criminal, they were civil
cases. But eventually they did become criminal cases. And it still isn't being talked about. I
think it's a very important issue because as soon as you start telling lawyers you're going to be
disbarred or you're going to be thrown in jail or you're going to be fined $94 million like Giuliani
was for simply representing your client, there's no way you can have the representation of your
choice with that. Absolutely. Because the lawyers who otherwise represent you are not available.
Yep, so they use threats, I agree, and coercion. And so I was going to ask you whether you think
with a judicial watch they've gone quiet about that or whatever, was it judicial watch?
Maybe they were threatened, unknown to you.
Yeah, I can buy that. I mean, I don't want to cast dispersions on their motives because I don't know
what they are. And I certainly know that I don't want to take unnecessary risk. I don't have the
job right now. I mean, I do occasional freelance work. But I certainly don't make the kind of
money I used to make when it wasn't illegal to be a conservative in the country. And just for an
instance, I used to be a very well-respected, successful university lecturer. And I can't get
a job as a university lecturer in America because I'm conservative and I'm not about to find one of
those diversity statements that they want everyone to come in. Oh, great. As far as I'm concerned,
there's a lot. So you won't sign them? That causes me to self- What? Sorry, what did you say you
won't sign them interested in? Well, they have these forms, they're called diversity and inclusion
statements. And so anyone who wants to apply for a job at a university has to find this thing that
says that you're committed to diversity, that if somebody tells you they're a girl, even though
they're obviously a boy, you're going to pretend that they're a girl, this kind of thing. And I'm
just, that's not something I'm going to do. It's not honest to find something like that. And anyone
who does find it just to get a job is, you know, they're being dishonest. So I either become one
of them in order to get a job or I refuse and I don't get the job. So I know people who sign those
forms willy-nilly because they have no, they told me they sign them because they have absolutely no
intention of honoring what they've signed. So I don't know what- Yeah, but I feel uncomfortable.
Sorry? Yes, I understand that you're- I'm not comfortable doing something like that. If it's
false, I just can't bring myself to find it. So essentially they sign them, they sign them daring
the employer to sue them if they don't, do you understand what I mean? They just don't care.
They just sign it as a ridiculous piece of paper. They have no respect for the piece of paper. They
have no intention of doing what they've said. And I agree. I can understand that you wouldn't
want to compromise yourself. I wanted to ask you, the last question was where you don't,
you know, if you don't want to answer this, that's fine. But where do you get your
unbelievably strong values from, Andrew? We need more people like you.
I can't, I don't really know for sure. But one thing I do know is that I do have an innate sense
of whether something I have said is correct or not. And if I get a sense that it's not,
I tend to investigate it to see why. Okay. And I also made a deal with myself a long, long time ago
that if I ever find out that I said something that was incorrect to someone else, I have to correct
it. So I will make real efforts to like track down the person and, you know, call them up or write
them or see them in person or whatever it is to correct the error. Now, it's not always practical
to do that. But what this means is it's a huge incentive for me not to make the error in the
first place, which makes me a lot more careful with what I say. And it makes me more willing
to investigate things. I'll tell you one thing that's kind of an interesting subject on its own.
But a long time ago, when I first met my wife, she was constantly telling me, you know, Andrew,
that dream you told me about yesterday or last week or whatever just came true. So you're having
dreams about the future. And I thought she was out of her mind and it was ridiculous. And I kept
telling her that. But then that little voice in the back of my mind said, you know, you're telling
her this is not true because it's impossible is not a very good answer. You have to actually prove
it to her and to yourself before you can actually say that honestly. So I finally figured out that
if I kept a journal of my dreams that was dated with every dream, I could prove that she was wrong.
It actually proved she was right. At which point I had to eat my words, which I did.
That's what the other subject is about. I'm kind of well known in the.
Are you able to share the the the the address of the internet address of the substance in the
chat or not the one you're talking about, the relatively hidden one? Yeah, I can. I don't talk
about this too much because some people are made very uncomfortable by people who claim to have had
this kind of experience. But I've had so many of them. I do write about it. I'm doing it right now.
I'm typing it in. If I were you, I would go to the earliest pages, not the most recent ones,
because those are the most spectacular ones. Sorry, when you missed that one, sorry. Pardon?
What did you say? You said I would go to if I were you, I would go to and then that word I missed.
The earlier entries and the reason is because the more recent ones are they just concern
what I consider to be a weaker introduction to the material than if you go to the older one.
I did it because I've had some dreams I think are so important that they basically should be shared.
You know, like 911. I had eight dreams about the 911 disaster in the year 1990 and one in 1989.
And so I printed those off and I sent them to some people at the time.
But they're not all like that. Some of them actually do. Some of them have to do with other
subjects. Like for one, I'm going to leave out all the details and just tell you the punch line. But
basically I was told in the dream that it's better to live a blameless life than to wish for and
receive a comfortable one. Okay. And I think that the logic of that stands on its own. And I've
certainly had other advice like that that I consider equally salutary. Does that make sense?
Yes, absolutely. It does to us anyway. Okay. Andrew, thank you so much for coming on
and for speaking so bravely. And what a brilliant thing you've done. So as I understand it,
let's just nail this down. Are you the first one to have discovered these algorithms in the
voting systems? As far as I know, yes. And I haven't encountered anyone who has said any different.
And actually, I'll go again, if Jerome is here, I think he'd be a better person to hear this
because, you know, I'm talking about myself all of a sudden. But yeah, so Jerome, are you here?
Jerome, I think he's walked away from this. Okay, I'll say this. But from what I'm told by the
the experts, like what I've been told from experts I've talked to on this,
this algorithm is so well hidden that they're astonished that it was ever found at all.
Never mind that it was me that found it. Apparently, they consider this to be almost
a miracle that it was found. Brilliant. Brilliant work by you. Well, after listening to you,
I'll tell you something. So after listening to you for over three hours now, Andrew,
I'm not astonished. Yeah. You're brilliant. You probably don't realize it. Well, maybe you do
partly but not you don't understand how brilliant you are, I think.
So anyway, well, thank you. I appreciate it. What were you going to tell us? Okay, so
I didn't hear that fully, but I'm assuming you're saying goodbye now so I can hang up
or did you have another question? No, I'm saying that you said that you nobody thought that you
would be that anyone could find these algorithms and they were astonished that you had found them.
And I said, well, after listening to you for over three hours now, I'm not astonished. Yeah.
Oh, thank you. Yeah, I think the reason they were astonished it was me is mainly because they were
astonished that anybody found it. Okay, so it just happened to be me. So that's why they're
astonished it was me. Absolutely. The few who've actually gone a little bit farther than that,
to say why in particular is it astonishing that I would, the couple who had any comment on that are,
I think, feel that way because I don't have a math background. And I don't have a background in
cryptography. But on the other hand, Wow, I've got people on the other end of it saying,
that's why you did find it. Because if you did have those backgrounds, you wouldn't. Yes.
Because the way it was implemented was designed to avoid all of the detection
methods used by people with that kind of a background. So yeah, so I think that my
background is... I think they're both copyrights.
Yeah, that wouldn't surprise me. I mean, ultimately, one of the things I became known for in
computer graphics was my ability to fix files that had been screwed up by other people. And what that
meant was I had to analyze very complicated files and find out which parts belong together and then
put them there. Which is very difficult, tedious work that most people don't like to do, but
it doesn't bother me. So I got very good at it and got a reputation for it. And that's essentially
what I was doing here. Very good. Oh, it looks like Jim has another comment. Should I take that
question or are we ending this? Yeah, Jim, go ahead. Thank you very much. I just wanted to know if you
would come on Telegram for a little while and maybe share your sub stack because I can't really
get it through this chat and maybe talk or share some more questions and answers. The Telegram chat
is a place where we can share links and things like that. And maybe in the future, we can put
that Telegram chat on the invitation so that afterward we can talk there if we have more time
or if individuals have more time. So if it's okay with Steven and with Charles,
very appreciative for their moderation. So thanks. I could do that, but not right now. I just say,
you know, I'm working on a project that I have to have finished by Friday and I have been delayed
thanks to excessive number of migraine headaches that had me in bed for about six days. So I want
to do that first. Can I give you some information that may help you with the migraines?
And I have to do that off? Yes. Yeah, do it offline because I actually have to get back to my work.
But that would be fine with it. Okay. And if you can't reach me, you can reach me through the
moderators because consider drinking saffron tea. Consider drinking saffron tea. It increases the
diffusion coefficient through ischemic tissue and the spasms in the vessels are due to ischemic
tissue. So what helps in the acute situation is what may help. This is not advice. Talk to your
physician about it is sipping on some oxygen, which means like, what's this got to do with the,
I don't understand what this has got to do with them. It's just his own headache.
I'll talk to him later on. Thank you very much. Sorry. Yeah. Okay. Sorry. I think I'm going to let
you guys go then. Yes. Thank you. Well, I was trying to find a good time to finish, but I'm
not the usual moderator Charles is, but he's fallen asleep in Australia, I think,
because it was five o'clock in the morning when we started in Australia, in Melbourne. So thank you
very much, Andrew. You're a brilliant guest and I'm so happy that you've spoken to us. Oh, one last
question. So why are people knowing what we think happened in 2020, some of us anyway,
why are people so confident that that won't happen again?
That I think is really peculiar. It reminds me of something, it's kind of tickling the back of my
mind right now. Well, I'll give you a cartoon. If you remember Charlie Brown back when that was
still being published and Lucy, I was pulling the football away from him at the last minute and him
being willing to give it another try because she kept saying, oh no, I'll hold it this time. And
then she pulls it away again. I think it's kind of an endless hope that it will be done right,
because the person actually doesn't know what else to do, but to hope because they have no idea how
to fix it themselves. Absolutely. I think you're right. Have a great day then. And it was my
pleasure to be able to talk to you guys, although hopefully the next time if we ever do this again,
the connection will be better and there won't be all these time lags. Okay. By the way,
Jerome Corsi is a wonderful ally for you, Andrew. Oh, well, thanks. Yeah, I thought it was interesting
and good that he contacted me. So I appreciated that. He once told me in a conversation,
he once told me in a conversation, I'm sure he won't mind because he's got a good sense of humor.
He once told me in a conversation on the phone that he should have got his PhD when he was 15.
So I said, when did you get your PhD? In government from Harvard, by the way. And he said 21.
And I thought, wow, that's pretty amazing. I wanted to do that when I was young. And I think
I probably could have, but I didn't have the money to go to school. I was one of these typical
poverty stricken kids who had zero money. In fact, that's why I left college, because I only
had enough to go so far. And then I had to quit work for a living. Did you know Aaron Schwartz?
Are you familiar with the work of Aaron Schwartz, who was also a computer genius?
It doesn't ring a bell, but it's a fairly common name. So it's possible. Okay. Well, he was the
guy who was indicted by the federal government for something to do with MIT. They accused him of
stealing documents or something from MIT. I hope I haven't got it wrong. And essentially, they bullied
him. That's starting to sound a little familiar. I'm actually rethinking my opinions on a lot of
things, thanks to my discovery of how biased the media is. There was a politician in Illinois who
took Obama's position in the House of Representatives. And then he got thrown in jail. And I thought,
well, he was a bad guy because he was selling Obama's feet. Because that's the story that went
out. But then he got released after being pardoned by Donald Trump. And he went ahead and gave a
few interviews. And those interviews indicated to me that the charges against him were Trumped up.
And the same thing goes for Julian Assange and Edward Snowden, both of whom I was inclined to
believe the official story on until the last few years when all of a sudden my trust in the media
evaporated to nothing. And now I work with them and I'm thinking, well, those guys were real workers
also. But anyway, I do have to run. Sure. There's a wonderful film about Harry Schwartz on YouTube,
I think, which I thoroughly recommend to you. It's brilliant. And he was targeted by the government,
for some reason unknown to us all. But thank you so much, Andrew, for coming on.
No problem. Have a good day. Bye bye. Yes. Bye bye.