When computers cheat, they inevitably leave evidence behind By Andrea Widburg
Dr. Shiva Ayyadurai, a multi-credentialed MIT grad, ran the numbers, and the computer data generated in Michigan scream out “fraud!”
You should learn three main things from this post: (1) The Supreme Court can consider statistical evidence of fraud and can order a new election. (2) Most of the computers used for voting in America have a built-in mechanism that allows votes to be weighted in favor of a candidate. (3) If someone does tell a computer to mess with the election outcome, the computer’s processes will inevitably create unnatural data trails that prove human intervention in vote counts – and that’s what happened in three Michigan counties.
The Supreme Court
Alexander Macris found Donohue v. Board of Elections of State of New York, 435 F.Supp. 957 (E.D.N.Y. 1976), a case with close parallels to 2020’s election. After President Ford lost in 1976, Republican voters sued New York, alleging that systematic fraud deprived them of their voting rights. The district court allowed the suit and stated the following legal test: (1) Plaintiffs had to prove specific acts of misconduct that (2) involved ‘willful or knowing’ ballot fraud (3) by state officials or private persons acting jointly with state officials that (4) changed the outcome of the election.
The court held that the plaintiffs could introduce expert opinions and statistical analyses showing that voting patterns markedly deviated from the predictable uniformity to be found in random samples from elections counts that were honest. If the plaintiffs, won, said the court, they could get an order requiring a new presidential election. Any other outcome would fail to protect election integrity (especially in presidential elections) that is “essential to a free and democratic society.”
Donohue plaintiffs were unable to meet the legal test because they did not introduce sufficient evidence showing that fraud changed the outcome. However, there’s an unending flow of evidence in this year’s election, both witness testimony and data evidence, showing fraud sufficient to change the election’s outcome in the contested states.
Vote-counting machine irregularities
Some of the statistical data Trump needs can be found in the video at the bottom of this post. In it, Shiva Ayyadurai, Ph.D., a multi-credentialed MIT grad whom leftists despise works with Bennie Smith, a software engineer, election commissioner, and data analyst, and Phil Evans, and inventor, engineer, and data analyst, to show massive voting machine fraud in three Michigan counties.
Ayyadurai leads with some fundamentals.
First, most vote tabulation using computers is fraught with ambiguity and the potential for error. As we’ve learned, the ballots going into the system can be fraudulent (dead voters, fake voters, faked ballots, etc.). Democrat-run states increase the potential for fraud with mass mail-in voting, prohibitions against voter ID, and a failure to check signatures.
Second, we don’t know what goes on inside the computers. The computers work by taking a snapshot of each ballot and then working off the snapshot. By law, these snapshots must be saved for 22 months, but Democrat-run counties and states tend to delete them immediately.
Third, we don’t have evidence tying voters to the ballots fed into the computers. After all, since voters leave empty-handed. Moreover, if voters enter data on the computer screen and then hand a printout to a poll worker, although voters can see accurate words on that printout, they have no idea if the coding that the computer reads is accurate.
Fourth, almost all voting machines (including Dominion’s) are intentionally programmed with something called a “weighted race feature.” This allows the computer to add a multiplier to a candidate’s actual votes. For example, the machine could automatically multiply every Biden vote by some number over one.
In the video, Ayyardurai carefully demonstrates that, in Oakland, Macomb, and Kent counties, the machines were set to systematically take votes away from Trump and hand those same votes to Biden. The outlier was Wayne County, a heavily Democrat, minority county. Not only did the machine not steal Trump’s votes, but the data also showed that Trump overperformed in this county (although not enough to win in it).
Intriguingly, the more heavily Republican a precinct was, the more votes the machine stole from Trump and gave to Biden, creating a beautifully sloping line on the graph that could never have occurred naturally. If you know how to read them, machines are rotten liars.
It’s noteworthy how ambiguous the data are. For just three of the four counties analyzed, the analysis showed that Trump’s margin was reduced by a minimum of 138,000 votes. Now imagine if this vote theft occurred in Michigan’s other 80 counties.
And of course, keep in mind that Michigan is one of the states that allegedly passed thousands of fraudulent ballots into those voting machines. (See here, here, and here, for examples.) When you consider that Biden allegedly “won” by less than 3%, the combination of voting machine manipulation and illegal votes means Trump is right – he probably won Michigan handily:
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