Researchers Develop Artificial Intelligence Tool To Predict Vaccine Hesitancy

Researchers at the University of Cincinnati and Northwestern University developed a “tool in artificial intelligence” to predict whether someone is willing to receive a COVID-19 shot.

The “system integrates the math of human judgment with machine learning to predict vaccine hesitancy,” according to the University of Cincinnati.

“We used a small number of variables and minimal computational resources to make predictions,” said lead author Nicole Vike, a senior research associate in UC’s College of Engineering and Applied Science.

“COVID-19 is unlikely to be the last pandemic we see in the next decades. Having a new form of AI for prediction in public health provides a valuable tool that could help prepare hospitals for predicting vaccination rates and consequential infection rates,” Vike continued.

So, if you don’t want an experimental injection, an AI tool will find you.

Don’t Want a Vaccine? New AI Tool Will Find You https://t.co/Wwg5t8jm2S

— The Vigilant Fox (@VigilantFox) March 23, 2024

From the University of Cincinnati:

Researchers surveyed 3,476 adults across the United States in 2021 during the COVID-19 pandemic. At the time of the survey, the first vaccines had been available for more than a year.

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Respondents provided information such as where they live, income, highest education level completed, ethnicity and access to the internet. The respondents’ demographics mirrored those of the United States based on U.S. Census Bureau figures.

Participants were asked if they had received either of the available COVID-19 vaccines. About 73% of respondents said they were vaccinated, slightly more than the 70% of the nation’s population that had been vaccinated in 2021.

Further, they were asked if they routinely followed four recommendations designed to prevent the spread of the virus: wearing a mask, social distancing, washing their hands and not gathering in large groups.

Participants were asked to rate how much they liked or disliked a randomly sequenced set of 48 pictures on a seven-point scale of 3 to -3. The pictures were from the International Affective Picture Set, a large set of emotionally evocative color photographs, in six categories: sports, disasters, cute animals, aggressive animals, nature and food.

Vike said the goal of this exercise is to quantify mathematical features of people’s judgments as they observe mildly emotional stimuli. Measures from this task include concepts familiar to behavioral economists — or even people who gamble — such aversion to risk (the point at which someone is willing to accept potential loss for a potential reward) and aversion to loss. This is the willingness to avoid risk by, for example, obtaining insurance.

“The framework by which we judge what is rewarding or aversive is fundamental to how we make medical decisions,” said co-senior author Hans Breiter, a professor of computer science at UC. “A seminal paper in 2017 hypothesized the existence of a standard model of the mind. Using a small set of variables from mathematical psychology to predict medical behavior would support such a model. The work of this collaborative team has provided such support and argues that the mind is a set of equations akin to what is used in particle physics.”

New U of Cincinnati developed AI is working to pinpoint those choosing not to jab. Will likely lead to authoritarian compulsive policies for those dissenters deemed mentally deficient in some way???https://t.co/nEb9dkv6DB

— Elise Villemaire (@Villainessa) March 22, 2024

“Despite COVID-19 vaccine mandates, many chose to forgo vaccination, raising questions about the psychology underlying how judgment affects these choices. Research shows that reward and aversion judgments are important for vaccination choice; however, no studies have integrated such cognitive science with machine learning to predict COVID-19 vaccine uptake,” the researchers wrote.

“This study aims to determine the predictive power of a small but interpretable set of judgment variables using 3 machine learning algorithms to predict COVID-19 vaccine uptake and interpret what profile of judgment variables was important for prediction,” they added.

Brian Hooker, Ph.D., chief scientific officer for Children’s Health Defense, said the tool implies that vaccine-hesitant individuals have mental health problems.

“The whole implication here is that nonconformity to the government propaganda machine’s standard of care makes one some type of mental case or extreme outlier. The whole thing smacks of a Brave New World where potentially non-compliant individuals are targeted with messaging based on fear and irrationality,” Hooker said, according to The Defender.

AI can predict people’s attitudes to vaccines | University of Cincinnati https://t.co/ySSQSCNule (mentions @jmirpub)

— JMIR Publications (@jmirpub) March 19, 2024

The Defender reports:

The study’s authors said the technology also could be used to “aid vaccine rollouts and health care preparedness by providing location-specific details” — in other words, identifying geographic areas that may experience low vaccination and high hospitalization rates, according to the study.

Critics questioned the study’s claims and also said they were worried about the potential adverse uses of this technology.

“The main problem with research like this is the underlying premise: Vaccine hesitancy must be accounted for in terms of the (aberrant) psychology of the subjects and not with reference to the efficacy and safety of the vaccine(s) in question,” said Michael Rectenwald, Ph.D., author of “Google Archipelago: The Digital Gulag and the Simulation of Freedom.”

As a result, Rectenwald said, it’s implied that “if people are vaccine-hesitant, the fault is endemic to them rather than to the vaccine itself. From this premise, the research seeks to justify vaccination as normal by linking anomalous mental and psychological characteristics with vaccine hesitancy.”

This may lead to individuals being targeted, Rectenwald said:

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“Using AI to predict vaccine hesitancy on these terms might include mobilizing AI programs to target and even identify individually vaccine-hesitant subjects. We might also expect AI programs that seek to overcome vaccine hesitancy with attempts to ‘reprogram’ said defective subjects.

“At the very least, identifying, targeting and re-educating vaccine hesitant subjects is in the offing.”

Read the study, titled ‘Predicting COVID-19 Vaccination Uptake Using a Small and Interpretable Set of Judgment and Demographic Variables: Cross-Sectional Cognitive Science Study,’ HERE.

This is a Guest Post from our friends over at 100 Percent Fed Up.

View the original article here.