Here’s something for you to contemplate as you consider concerns about election integrity: Do the algorithms that Andrew Paquette, Ph.D., has found surreptitiously embedded in current state board of election voter rolls suggest intelligence agents have decided to bypass voters to vote election simulations?

As documented on GodsFiveStones.com, Paquette has found secret algorithms in the board of election voter registration databases in New York, New Jersey, Ohio, Wisconsin, Pennsylvania, Hawaii, and Texas, with ongoing examinations underway in Arizona and Georgia.

The algorithms appear designed to hide critical voter attribute information, allowing the people who developed the scheme to create and hide “non-existent voters” capable of being assigned legitimate state voter IDs. Once created, the algorithms can vote certifiable mail-in ballots for enough “non-existent voters” to steal an election from an opponent who won through legitimate votes.

Image by AI.

In his analysis of the algorithm found in the New York State Board of Election voter registration database, Paquette detailed how the algorithm could be used in a mail-in ballot scheme to steal an election.

The data uncovered by NYCA’s (New York Citizens Audit) research suggests systemic election fraud is built into New York’s electoral process. The current working hypothesis is that:

1.    False voters were introduced into the voter rolls.

2.    The algorithm covertly tagged these records for easy retrieval when needed.

3.    False registrants requested absentee ballots.

4.    Ballots and ballot envelopes were gathered at central collection points.

5.    Fraudulently generated ballots were cast in fraudulently obtained ballot envelopes.

6.    False voter records were updated to reflect false votes.

7.    After certification, false voter records were manipulated to disguise their purpose and history.

In that paper, Paquette estimated there were approximately 338,000 illegally generated registrations in the New York State Board of Election voter registration database active for the 2020 General Election.

With tens of thousands of nonexistent voter registrations thanks to the algorithm, the criminals accessing the Board of Election computers could easily ask how to structure an election. “Should our Candidate X (the algorithm-chosen winner) win by 1 percent, 3 percent, or more? Should our Candidate X lead throughout election day, surge late in the voting, or require a stoppage of vote counting to produce enough ‘non-existent voters’ to cast mail-in ballots to steal the election?”

The point is that these hidden “non-existent voters” could be activated to cast a certifiable mail-in vote as needed, provided the algorithm assigned legitimate state voter ID numbers to the “non-existent voters.”

The problem with the algorithmic mail-in ballot election fraud scheme is that if you know about the algorithm, the patterns become apparent. In mail-in ballot fraud, we see candidates who are losing the in-person vote surge at the end of the election, when the mail-in ballots are counted. For example, if a candidate through legitimate, in-person voting has a larger lead than anticipated, vote counting stops overnight, followed by a surge of newly discovered mail-in ballots that heavily vote for Candidate X.

To succeed, the scheme requires that the certification process does not involve any forensic attempt to go into the community to investigate whether the mail-in ballots cast belong to legitimate voters. The scheme also depends on lax checking of the signatures on the outside cover of mail-in ballots to ensure they are matched for accuracy with the voter’s signature placed on file at the time of registration.

How close are we to intelligence agencies deciding that with advances in AI and the statistical analytic skills of modern political science, voters are obsolete? This is not a far-fetched question.

In an exchange preserved on video from a 2017 World Economic Forum meeting, Klaus Schwab suggested that voters have become obsolete given advances in computer technology. Schwab said, “But since the next step could be to go into prescriptive mode, which means you do not even have to have elections anymore because you can already predict what, predict, and afterwards you can say, ‘Why do we need the elections?’ Because we know what the result will be. Can you imagine such a world?”

The World Economic Forum quickly attempted to control the damage, issuing a corrective statement insisting that Schwab’s comments were not “a call for action” but a hypothetical musing based on the anticipated predictive capabilities of computer technology in the future.

The academic modeling of presidential elections has advanced to the point where a group of scientists in Peru and Brazil have developed a predictive mathematical model that utilizes machine learning (ML) and an Artificial Neural Network (ANN) to predict presidential election results (PER) with 100 percent agreement with actual elections in Brazil, Uruguay, and Peru. Conceivably, a computer model could run a simulation of a presidential election that would model a victory for the preferred candidate X. But for the computer simulation to be substituted for the actual vote credibly requires that the simulation matched reasonable anticipations of voter preferences.

That conclusion that intelligence agencies are involved in placing algorithms in the state boards of election databases is supported by the complexity of the cryptographic mathematics and cipher intricacy that Dr. Paquette has demonstrated to be characteristic of the voter registration databases that he has discovered. Developing and placing the algorithms into the computer systems of the state boards of elections would require either confederate actors within the state board elections or a covert intelligence operation to penetrate the various state boards.

However, stealing elections to be credible also involves successfully implementing a psychological operation involving control over mainstream media narratives. For example, consider that Joe Biden, after a disastrous debate with Donald Trump, demonstrated diminished mental functioning that disqualified him from being a credible contender. Vice President Kamala Harris was a more credible challenger, provided intelligence agencies could get the mainstream media to report questionable “surveys” that showed her challenging President Trump neck-to-neck despite her history of unpopularity and failure to advance in previous presidential attempts.

That Schwab was engaged in paving the way for a planned elite dystopian future is a reasonable conclusion given the arguments Archbishop Carlo Maria Viganò advanced in an essay entitled “The Technocratic Dystopia: Are novels of Huxley and Orwell an unheeded warning or an example of predictive programming?”* Archbishop Viganò explained: “What Brave New World and 1984 describe corresponds to the same processes of predictive programming that we find in numerous movies having as their theme pandemics, dictatorial regimes after climate crises, and plots by pharmaceutical companies, high finance, and secret societies—that is, to the use of the fictional literary genre as a tool for mass mental processing in order to make the population more willing to accept planned future events.”

Archbishop Viganò defined”predictive programming,’ i.e., the use of a hypothetical comment “as a tool for mass mental programming in order to make the population more willing to accept future planned events.” If the algorithms Paquette has discovered are the handiwork of U.S. intelligence agencies, the New World Order to make voters obsolete has already begun.

GodsFiveStones.com is a tax-deductible 501(c)3 foundation created by Jerome R. Corsi, Ph.D., and Karladine Graves, M.D., managed by Capstone Legacy Foundation.

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*Reprinted in my most recent book: Jerome R. Corsi, Ph.D., The Antiglobalist Manifesto: Ending the War on Humanity (Nashville, TN: Post Hill Press, 2024), Appendix C, “Message of Archbishop Carlo Maria Viganò, ‘The Technocratic Dystopia,’ (April 30, 2023),” pp. 226-234, at p. 232.