[[{“value”:”Researchers at the University of Cincinnati and Northwestern University developed a” tool in arbitrary 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 little computing 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 improbable to be the last pandemic we see in the next decades. Having a new form of AI for prediction in public health provides a useful tool that could help prepare hospitals for predicting vaccination rates and significant infection rates”, Vike continued.
So, if you do n’t want an experimental injection, an AI tool will find you.
Do n’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 second vaccines had been available for more than a year.
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 applicable 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.
Additionally, they were asked if they regularly followed four recommendations designed to prevent the spread of the virus: wearing a mask, social distancing, washing their hands and no gathering in large groups.
Participants were asked to rate how much they liked or disliked a arbitrarily 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 physically expressive color photographs, in six categories: sports, disasters, pretty animals, violent animals, nature and food.
Vike said the goal of this exercise is to quantify scientific features of people’s judgments as they observe somewhat emotional stimuli. Measures from this task include concepts familiar to behavioural economists — or even people who gamble — for aversion to risk ( the point at which someone is willing to accept probable 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 enjoyable or aversive is fundamental to how we make skilled decisions”, said co- senior author Hans Breiter, a professor of computer science at UC. ” A sperm paper in 2017 hypothesized the existence of a standard model of the mind. Using a small set of variables from scientific psychology to predict medical behavior would support such a model. The work of this creative team has provided for support and argues that the mind is a set of equations equivalent to what is used in particle physics”.
New U of Cincinnati developed AI is working to pinpoint those choosing never to jab. Will possible lead to authoritarian persistent 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, some 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, yet, no studies have integrated such mental science with machine learning to predict COVID- 19 vaccine uptake”, the researchers wrote.
” This study aims to determine the predictive power of a little but comprehensible set of judgment variables using 3 machine learning algorithms to predict COVID- 19 vaccine uptake and interpret what profile of judgment variables was essential for prediction”, they added.
Brian Hooker, Ph. D., general medical officer for Children’s Health Defense, said the tool implies that vaccine- anxious 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 intellectual case or extreme outlier. The whole thing smacks of a Brave New World where possible non- cooperative 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 even could be used to “aid vaccine rollouts and health care preparedness by providing location- certain details” — in other words, identifying regional areas that may experience low vaccination and great hospitalization rates, according to the study.
Critics questioned the study’s claims and likewise said they were worried about the potential negative 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 prevalent to them rather than to the vaccine itself. From this premise, the research seeks to justify vaccination as normal by linking anomalous emotional and mental characteristics with vaccine hesitancy”.
This may lead to individuals being targeted, Rectenwald said:
” Using AI to predict vaccine hesitancy on these terms might include uniting AI programs to target and also identify individually vaccine- anxious subjects. We might even expect AI programs that seek to overcome vaccine hesitancy with attempts to ‘ reprogram’ said incorrect 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 Statistical Variables: Cross- Sectional Cognitive Science Study,’ HERE.”}]] [[{“value”:”
Researchers from the University of Cincinnati, Northwestern University and the University of California at Berkeley developed an “artificial intelligence tool” that predicts whether someone will accept a COVID-19 injection.
According to the University of Cincinnati, the “system integrates human judgment and machine learning to predict vaccine hesitation.”
“We used a limited number of variables and minimal computing resources to make predictions,” said Nicole Vike, a lead author and senior research associate at UC’s College of Engineering and Applied Science.
“COVID-19 will not be the last pandemic in the next decade.” Vike added that a new form AI for public health prediction could be a valuable tool to help hospitals predict vaccination rates and subsequent infection rates.
If you don’t wish to receive an experimental injection, the AI tool will locate you.
Don’t Want a Vaccine? New AI Tool Will Find You https://t.co/Wwg5t8jm2S
The Vigilant (@VigilantFox), March 23, 2024
From the University of Cincinnati
Researchers conducted a survey of 3,476 adults in the United States during the COVID-19 Pandemic in 2021. The first vaccines were available for over a year at the time of the study.
The respondents provided information on their ethnicity, income, education level, and where they live. According to U.S. Census Bureau data, the demographics of respondents matched those of Americans.
Participants were asked whether they had received any of the COVID-19 available vaccines. Around 73% of respondents reported that they had been vaccinated. This is slightly more than the 70% vaccination rate of the population in 2021.
They were also asked if, on a regular basis, they followed four recommendations to prevent the spread: wearing a face mask, social distance, washing their hands, and not gathering large groups.
The participants were asked to rate a randomly selected set of 48 images on a scale of 0 to 3 out of 7. The images were taken from the International Affective Picture Set. This is a large collection of emotionally evocative photographs in six categories, including sports, disasters and cute animals.
Vike said that the goal of the exercise was to quantify mathematical features in people’s judgments when they observe mildly emotionally stimuli. This task includes concepts that are familiar to behavioral economics or even gamblers, such as aversions to risk (the point where someone is willing accept a possible loss in exchange for a reward) and aversions to loss. This is the willingness of a person to avoid risk, such as by obtaining insurance.
“The framework we use to judge what is rewarding and aversive has a fundamental impact on how we make medical choices,” said Hans Breiter, a professor at UC who is also a senior author. “A seminal article in 2017 hypothesized that there was a standard mental model. A model based on a few variables from mathematical psychology would be supported by using them to predict medical behavior. This collaborative team’s work has provided support for this model and argues that mind is a similar set of equations to those used in particle physics.”
The new AI developed by the University of Cincinnati is working to identify those who choose not to vaccinate. Will likely lead to authoritarian policies for those deemed mentally deficient? ?https://t.co/nEb9dkv6DB
— Elise Villemaire (@Villainessa) March 22, 2024
“Despite COVID-19 vaccination mandates, many chose not to vaccinate, raising questions about how judgment affects such choices. Researchers found that reward and aversion judgements are important in vaccination choice. However, no studies have integrated cognitive science with machine-learning to predict COVID-19 uptake.
This study aims at determining the predictive power of 3 machine learning algorithms for COVID-19 vaccine uptake, and interpreting what profile of judgement variables was important for predictions,” they added.
Brian Hooker, Ph.D. Chief Scientific Officer for Children’s Health Defense said that the tool implies vaccine-hesitant individuals suffer from mental health issues.
“The whole implication is that nonconformity with the government propaganda machine’s standard of care makes you a mental case or an extreme outlier.” The whole thing reminds me of a Brave New World, where non-compliant people are targeted by messages based on fear and irrationality,” Hooker told 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 stated that the technology could also be used to “aid in vaccine rollouts and healthcare preparedness by providing specific location details” — i.e., identify geographic areas where there may be low vaccination rates and high hospitalizations, according to the report.
Critics have questioned the study and expressed concern about the possible negative uses of this technology.
The main problem with this type of research is the underlying assumption: Vaccine hesitancy should be accounted for by the (aberrant and distorted) psychology of subjects, and not by the efficacy and/or safety of the vaccines in question,” said Michael Rectenwald Ph.D.
Rectenwald explained that this implies “if people are vaccine-hesitant then the fault is with them and not the vaccine.” The research aims to prove that vaccination is normal by relating anomalous mental and emotional characteristics with vaccine hesitancy.
Rectenwald stated that this could lead to individuals being targeted.
AI programs could be used to identify and target vaccine-hesitant individuals. We could also expect AI programs to try to overcome vaccine hesitancy by’reprogramming’ the defective subjects.
“At a minimum, identifying, targeting, and re-educating vaccination hesitant subjects will be in the works.”
Click HERE to read the study titled “Predicting COVID-19 vaccination uptake using a small and interpretable set of judgment and demographic variables: Cross-Sectional Cognitive Science Studies.”
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