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<\/div>\nMiss a day, miss a lot.<\/strong> Subscribe to The Defender’s Top News of the Day<\/a>. It’s free.<\/strong><\/em><\/p>\n A team of researchers has developed a \u201cpowerful new tool in artificial intelligence<\/a>\u201d (AI) that can predict if someone is or isn\u2019t likely to get a COVID-19 vaccine.<\/p>\n According to the University of Cincinnati, the new AI tool \u201cuses a small set of data from demographics and personal judgments such as aversion to risk or loss\u201d to identify \u201creward and aversion judgment\u201d patterns in humans that may help explain one\u2019s willingness to get vaccinated<\/a>.<\/p>\n The researchers presented their findings in a study published Tuesday in the Journal of Medical Internet Research Public Health and Surveillance<\/a>.<\/p>\n The study\u2019s findings \u201ccould have broad applications for predicting mental health and result in more effective public health campaigns,\u201d the university said.<\/p>\n According to the study, \u201cDespite COVID-19 vaccine mandates, many chose to forgo vaccination, raising questions about the psychology underlying how judgment affects these choices.\u201d<\/p>\n The researchers claim their findings \u201cdemonstrate the underlying importance of judgment variables for vaccine choice and uptake, suggesting that vaccine education and messaging might target varying judgment profiles to improve uptake.\u201d<\/p>\n But critics like Brian Hooker, Ph.D.<\/a>, chief scientific officer for Children\u2019s Health Defense<\/a>, said that the new technology implies that those who question vaccines have mental health problems:<\/p>\n \u201cThe whole implication here is that nonconformity to the government propaganda machine\u2019s 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.\u201d<\/p>\n Hooker said the new technology \u201cis a prefabricated substitute to what Big Pharma<\/a> and government health agencies avoid: rational discussions of science and medicine that might expose the truth about vaccine adverse events.\u201d<\/p>\n Using AI to target the \u2018vaccine-hesitant\u2019?<\/strong><\/p>\n Nicole Vike, Ph.D.<\/a>, senior research associate at the University of Cincinnati\u2019s College of Engineering and Applied Science, was the paper\u2019s lead author.<\/p>\n \u201cCOVID-19 is unlikely to be the last pandemic we see in the next decades,\u201d Vike said. \u201cHaving 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.\u201d<\/p>\n The study\u2019s authors said the technology also could be used to \u201caid vaccine rollouts and health care preparedness by providing location-specific details\u201d \u2014 in other words, identifying geographic areas that may experience low vaccination and high hospitalization rates, according to the study.<\/p>\n Critics questioned the study\u2019s claims and also said they were worried about the potential adverse uses of this technology.<\/p>\n \u201cThe 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,\u201d said Michael Rectenwald, Ph.D.<\/a>, author of \u201cGoogle Archipelago<\/a>: The Digital Gulag and the Simulation of Freedom.\u201d<\/p>\n As a result, Rectenwald said, it\u2019s implied that \u201cif 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.\u201d<\/p>\n This may lead to individuals being targeted, Rectenwald said:<\/p>\n \u201cUsing 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 \u2018reprogram\u2019 said defective subjects.<\/p>\n \u201cAt the very least, identifying, targeting and re-educating vaccine hesitant subjects is in the offing.\u201d<\/p>\n Scott C. Tips, president of the National Health Federation<\/a>, said the new technology poses privacy concerns.<\/p>\n Tips said:<\/p>\n \u201cIt is nobody\u2019s business but that of the individual as to whether he or she wants to be vaccinated. Why does anyone need to predict health decisions? \u2018Predictive\u2019 AI on this issue is nothing but a solution looking for a problem. There is no problem here. In fact, we should be glad that there are people who do not want to be vaccinated.\u201d<\/p>\n Similarly, Dr. Kat Lindley, president of the Global Health Project and director of the Global COVID Summit<\/a>, agreed. \u201cThere are many reasons why someone may be vaccine-hesitant, and relying on a program, no matter how intelligent, to predict the outcome, I fear will underestimate the human element and individual experiences.\u201d<\/p>\n Critics also question claims about the technology\u2019s effectiveness. \u201cAI is only as good as the programmer and the parameters it was given, which also includes the biases with which it was created,\u201d Lindley said.<\/p>\n Tim Hinchliffe<\/a>, editor of The Sociable<\/a>, said, \u201cWe\u2019ve seen how ChatGPT spits out nonsense<\/a> and we\u2019ve seen the diversity disaster that was Google Gemini<\/a>, so it\u2019d be best to approach the results with caution. And when there is AI-human teaming, the results can still be biased.\u201d<\/p>\n \u201c\u2018Garbage in, garbage out\u2019 applies equally to AI-driven decisions and results every bit as much as it applies to any other decisions or results made by humans and \u2018dumb\u2019 computers,\u201d Tips said. \u201cIf the AI is searching through mainstream-only files and data for its answers, then it will come up with incorrect and biased results.\u201d<\/p>\n \u2018Who will be the next targets of this attitude-predicting apparatus?\u2019<\/strong><\/p>\n Other experts suggested governments could abuse the technology and weaponize it against the public.<\/p>\n \u201cIt\u2019s indicative of the state of medicine and the priorities of our federal government to see more research being done on how to increase uptake<\/a> of whatever product they\u2019re defining as a vaccine, than to do the safety studies the public has been crying out for,\u201d said Valerie Borek, associate director and lead policy analyst for Stand For Health Freedom<\/a>.<\/p>\n \u201cThis study fits the decades-long approach to using psychology<\/a> and our subconscious to push products and agendas,\u201d she said. \u201cThere is already technology that can assess biometric data such as heart rate, temperature and eye movements, combined with audio and location information.\u201d<\/p>\n Citing an example, Borek said the Centers for Disease Control and Prevention \u201calready has a record of using cellphone data for public health surveillance<\/a>.\u201d<\/p>\n Borek added:<\/p>\n \u201cThe government has too much data to comb through, so the use of AI is inevitable for public health surveillance. How long before the devices we voluntarily wear and carry are used for AI predictions of our health choices?<\/p>\n \u201cWill those predictions lead to any governmental interventions? We need to ask these questions of our lawmakers and do what we can to minimize our digital footprint.\u201d<\/p>\n According to Hinchliffe:<\/p>\n \u201cIf \u2018AI can predict people\u2019s attitudes,\u2019 then predicting so-called vaccine hesitancy would be just the start. What comes next? Predicting who is a climate denier? What about predicting people\u2019s attitudes toward presidential candidates and who they\u2019ll likely vote for? Who needs elections when the AI already knows who will win<\/a>?<\/p>\n \u201cWhat happens when the re-education and propaganda schemes don\u2019t work? Will data on predicting people\u2019s attitudes go to governments so they can crack down on dissidents? Who will be the next targets of this attitude-predicting apparatus? My guess would be people who are \u2018hesitant\u2019 about the climate change narrative<\/a>.\u201d<\/p>\n Study claims AI can \u2018make accurate predictions about human attitudes\u2019<\/strong><\/p>\n According to the University of Cincinnati\u2019s announcement<\/a>, the development of the new AI tool was based on a survey conducted in the U.S. in 2021, involving a representative sample of 3,476 adults. Respondents \u201cprovided information such as where they live, income, highest education level completed, ethnicity and access to the internet.\u201d<\/p>\n Participants were asked if they had received a COVID-19 vaccine, with approximately 73% of respondents reporting they were vaccinated, \u201cslightly more than the 70% of the nation\u2019s population that had been vaccinated in 2021,\u201d according to the study.<\/p>\n They were then \u201casked to rate how much they liked or disliked a randomly sequenced set of 48 pictures on a seven-point scale of 3 to -3,\u201d to quantify \u201cmathematical features of people\u2019s judgments as they observe mildly emotional stimuli.\u201d<\/p>\n \u201cThe judgment variables and demographics were compared between respondents who were vaccinated and those who were not. Three machine learning approaches were used to test how well the respondents\u2019 judgment, demographics and attitudes toward COVID-19 precautions predicted whether they would get the vaccine,\u201d the announcement states.<\/p>\n According to the study, \u201ca small set of demographic variables and 15 judgment variables\u201d were identified, which \u201cpredict vaccine uptake with moderate to high accuracy and high precision.\u201d<\/p>\n The announcement says these findings show \u201cthat artificial intelligence can make accurate predictions about human attitudes with surprisingly little data or reliance on expensive and time-consuming clinical assessments.\u201d<\/p>\n The same announcement quoted Aggelos Katsaggelos, Ph.D.<\/a>, endowed professor of electrical engineering and computer science at Northwestern University, who claimed \u201cThe study is anti-big-data<\/a>\u201d because the new technology \u201ccan work very simply\u201d and without the need for \u201csuper-computation.\u201d<\/p>\n \u201cIt\u2019s inexpensive and can be applied with anyone who has a smartphone. We refer to it as computational cognition AI. It is likely you will be seeing other applications regarding alterations in judgment in the very near future,\u201d Katsaggelos said.<\/p>\n Lindley disagreed. She told The Defender \u201cCalling this anti-big-data is an oxymoron, because to be able to claim a high level of accuracy, the program would have to encompass a high level of understanding of the hesitancy itself.\u201d<\/p>\n \u201cThe problem with this AI initiative is the population-wide approach, which disregards any individual concerns and experiences,\u201d Lindley said. \u201cIf I have learned anything practicing medicine these past 20 years, it is that the human element matters and it\u2019s unpredictable by its nature.\u201d<\/p>\n \u2018Tip of the iceberg\u2019: AI may also be used for rapid development of vaccines<\/strong><\/p>\n Other AI-related technologies in the healthcare realm have recently been introduced.<\/p>\n At the annual meeting of the World Economic Forum<\/a> (WEF) in January, Pfizer CEO Albert Bourla<\/a> praised the role of AI in the development of Paxlovid<\/a>, a prescription oral medication marketed as a treatment for COVID-19.<\/p>\n \u201cIt was developed in four months,\u201d Bourla said<\/a>, whereas development of such a drug \u201cusually takes four years.\u201d He said AI helped significantly reduce the amount of time needed for the \u201cdrug discovery\u201d process, where you \u201creally synthesize millions of molecules and then you try to discover within them, which one works.\u201d<\/p>\n Bourla credited this breakthrough with saving \u201cmillions of lives\u201d and predicted more such developments in the future. \u201cOur job is to make breakthroughs that change patients\u2019 lives,\u201d Bourla said. \u201cWith AI, I can do it faster and I can do it better.\u201d<\/p>\n \u201cI truly believe that we are about to enter a scientific renaissance in life sciences because of this coexistence of advancements in technology and biology,\u201d Bourla added. \u201cAI is a very powerful tool. In the hands of bad people [it] can do bad things for the world, but in the hands of good people [it] can do great things for the world.\u201d<\/p>\n During the same WEF panel discussion<\/a>, Jeremy Hunt<\/a>, the United Kingdom\u2019s chancellor of the Exchequer<\/a>, said AI could lead to the rapid development and deployment of vaccines.<\/p>\n \u201cWhen we have the next pandemic, we don\u2019t want to have to wait a year before we get the vaccine,\u201d he said. \u201cIf AI can shrink the time it takes to get that vaccine to a month, then that is a massive step forward for humanity.\u201d<\/p>\n A WEF project, first announced in 2019, is funding research on the use of \u201csynthetic\u201d AI-generated \u201cpatients\u201d<\/a> and \u201csynthetic\u201d clinical trial data<\/a>.<\/p>\n Concerns over AI\u2019s predictive ability have led to some action from lawmakers around the world. On March 13, the European Parliament passed the Artificial Intelligence Act<\/a>, which contains several restrictions and prohibitions on the use of AI in various contexts.<\/p>\n According to Greece\u2019s Business Daily<\/a>, \u201cEmotion recognition in the workplace and schools, social scoring<\/a>, predictive policing (when it is based solely on profiling a person or assessing their characteristics), and AI that manipulates human behaviour or exploits people\u2019s vulnerabilities\u201d are forbidden by this legislation.<\/p>\n Yet, for Hinchliffe, \u201cUsing AI to predict people\u2019s attitudes towards vaccines and vaccine hesitancy is just the tip of the iceberg,\u201d as AI technology can then \u201cbe used to predict attitudes on just about anything.\u201d<\/p>\n \u201cIf successful, predicting people\u2019s attitudes will lead to predicting their behavior. Predicting their behavior means knowing more about them than they know about themselves,\u201d he said. \u201cOnce humans are \u2018hackable<\/a>,\u2019 then all bets are off: They can be manipulated and controlled in the most nefarious of ways.\u201d<\/p>\n Correction<\/p>\n<\/div>\n![\"RFK](\"https:\/\/childrenshealthdefense.org\/wp-content\/uploads\/rfk-jr-cropped.png\")
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