Latest / Brett Keane and Eve Show / Election data analysis finds over 432,000 votes were removed from President Donald Trump across at least 15 counties

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Election data analysis finds over 432,000 votes were removed from President Donald Trump across at least 15 counties · Brett Keane and Eve Show

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  When we see over 400,000 errors in the state of Pennsylvania,
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  when we see direct switches like we saw in Bibb County, Georgia,
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  where there's over 12,000 votes that were swapped from Trump to
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  Biden, these are people's votes. This matters.
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  The Data Integrity Group, A group of data scientists, has
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  been dissecting publicly available data on the
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  presidential election multiple states, most recently in
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  Pennsylvania. They found over 432,000 votes
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  were removed from President Donald Trump in at least 15
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  counties. Time series election data shows
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  Trump's votes decreasing in various counties at many time
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  points instead of increasing in an election.
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  As you count votes, you typically only see vote
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  increments, not decrements, unless some error occurred that
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  needs to be assessed. So if you say, well, there was
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  this human error here, that's fine.
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  That's one I need to know. All these other 37, are they
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  human error as well? Are these machine error?
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  I don't know. The group also testified before
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  the Georgia Senate that more than 30,000 votes were removed
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  from President Trump in Georgia I.
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  Mean the improbabilities of some of these things that we're
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  bringing out are just way off the charts in terms of what
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  you'd expect in a normal distribution or any type of
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  expected behavior. This is American Thought
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  Leaders, and I'm Jan ya Kelek, Linda McLaughlin.
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  Such a pleasure to have you on American Thought Leaders.
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  Thank you so much for having me. I can't thank you enough, Jan.
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  Well, and I actually, it's not just Linda McLaughlin, it's
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  actually the data Integrity group that that the show is with
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  today. And you're the communications
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  person for the data Integrity group.
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  We recently published your work on the Pennsylvania data.
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  All your work is done with publicly available data, which
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  is a really interesting approach.
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  Tell me about what you're doing. Absolutely.
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  So I think like a lot of people, you know, the night of the
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  election, I was confused by what was happening.
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  I was seeing these strange vote totals.
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  The data wasn't performing the way that many of us saw it
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  happening in different parts of the evening.
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  And we saw these strange drops and declines live on television.
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  And I think for a lot of people, you know, there's a simple
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  explanation, which is that voting is supposed to be very
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  straightforward. You know, this is an additive
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  process. One candidate gets more votes
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  than the other, and we move on. But that night, we saw votes
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  actually dropping live on television.
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  You know, whole swings of votes, hundreds of thousands.
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  And I was sitting there with my family and friends saying, what
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  is happening? I don't, I don't understand.
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  And I'm not a data scientist. I work in politics.
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  I work in media. It's been my business for 15
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  years, and so when I started seeing this happen, I thought,
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  I've got to find this out. So I did.
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  I started looking around for data scientists, finding people
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  that were much smarter than myself to understand these
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  numbers and make sense out of them.
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  And that's really how this came about.
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  Well, so why don't you tell me who are the core members here of
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  the group and what do they contribute?
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  And then we'll get into a bit more about what you actually
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  did. Absolutely.
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  So we've got an amazing team of people that come from all walks
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  of life. They have very different
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  political ideologies and philosophies on elections, on
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  the Constitution, on our Republic.
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  But I think the one thing that we all agree on, and it's a very
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  interesting point, is that data is language.
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  It's a language that very few of us speak to the depth and
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  intricacy that these individuals speak.
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  And So what we have found is that they all came to this.
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  So John Basham is a meteorologist, but he has a
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  background in data science because that's used in that
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  profession. And he's also, you know, a
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  patriot to this country and served his country and has a
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  background in some of those operations, understanding some
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  of that intelligence. Then we have Justin Mealy, you
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  know, an NSA analyst, also a data scientist who took a look
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  at the the numbers and how they were speaking to one another and
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  where those strange corrections were happening.
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  Then we have Dave Leboux, an artificial intelligence expert,
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  another data scientist. So we have these people who use
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  data in very, very different ways.
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  And then we all came together in this group to look at the
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  numbers and say, this doesn't make sense.
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  It doesn't matter what role, what walk of life you come from,
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  what political field, it doesn't make sense and it's not fair to
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  the citizens of the country. It is not fair to the voters who
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  stayed up, waited in line for hours during a pandemic to get
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  their vote counted and to keep our Republic what it is meant to
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  be free and fair. So you've done a number of these
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  kind of explanatory videos that detail I guess these
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  irregularities that are found in the data in Pennsylvania and
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  Georgia. I think those are the two we'll
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  cover a little more in depth today because they're the most
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  recent and also obviously topical on the Georgia side.
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  But in essence OK, you are looking at air unexplainable
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  errors and data. Do I have this right?
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  Absolutely. Basically what we have seen is
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  that when you start to clean what we call cleaning the data
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  and looking at it and I get in trouble all the time because
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  data, not data. So you'll hear me flip flop on
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  that quite a bit. But basically what we've seen is
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  these numbers just don't make sense.
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  There's a pattern that that numbers follow based upon
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  previous voting elections, looking at demographics, looking
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  at geographical location. And suddenly these same votes
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  that are happening in one location have these spikes,
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  grand spikes out of nowhere, and then return to what would be
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  considered normal or consistent with what we would expect from
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  the numbers. And then we were also seeing
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  these influx of changes. And every time a change would
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  happen, whether the votes were removed, whether they were
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  swapped, whether it was an even swap or just a partial swap, it
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  always ended up benefiting Biden.
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  And every time, that rule never changed.
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  And that was our constant. And then we saw these data
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  numbers and these everything's moving around, and it makes no
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  sense. Nothing is following the pattern
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  as it should be seen. And it's basically abuse of
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  data. But that's not a language that
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  many in our society speak. So you need to have it broken
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  down in a way that is consumable and digestible and
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  understandable by your average American.
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  So we try to make analogies and graphs and animations so that
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  you can understand some of the things that are happening in
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  every day conversation. And that's been really important
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  to us because we want people to understand what's happening.
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  You know, data is is not partisan.
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  It's not blue, it's not red, it's binary.
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  It's just numbers. The numbers tell the story.
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  It's the truth.