Are you willing to get the COVID-19 vaccine? AI says it knows the answer – cleveland.com

CINCINNATI, Ohio A new artificial intelligence tool developed at the University of Cincinnati can accurately predict whether someone is willing to be vaccinated against COVID-19 with only a little bit of information.

Such accurate assessments of perceptions about vaccines and other medical treatments is information that may one day be useful in designing more effective public health campaigns beyond COVID-19, say the creators of the technology.

COVID-19 is unlikely to be the last pandemic we see in the next decades, said lead author Nicole Vike, a senior research associate in UCs College of Engineering and Applied Science. 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.

The predictive artificial intelligence system uses a small set of data from demographics along with information about a persons personal judgments. Then using some patterns about how one responds to rewards and aversion to risk, it comes up with its answer.

The framework by which we judge what is rewarding or aversive is fundamental to how we make medical decisions, explained co-senior author Hans Breiter, a professor of computer science at UC.

Breiter, Vike and the other researchers developed and tested the accuracy of their model by surveying nearly 4,000 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.

Respondents provided information such as where they live, income, highest education level completed, ethnicity and access to the internet.

They were also asked if they had received either of the available COVID-19 vaccines and 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 then shown a set of 48 color photographs in six categories: sports, disasters, cute animals, aggressive animals, nature and food and asked to rate how much they liked or disliked each of them on a seven-point scale.

The pictures were designed to evoke some mild emotion. The way a person responds to the pictures tells behavioral scientists how a person makes judgements about taking risks and protecting themselves from loss.

The judgment variables and demographics were compared between respondents who were vaccinated and those who were not. What they found was that AI could make accurate predictions about human attitudes with surprisingly little data or reliance on expensive and time-consuming clinical assessments.

We found that a small set of demographic variables and 15 judgment variables predict vaccine uptake with moderate to high accuracy and high precision, the authors wrote.

In terms of computing power, the whole thing is pretty easy too.

And in age of big-data, the team says their work provides evidence that sometimes less information is better.

The study is anti-big-data, said co-senior author Aggelos Katsaggelos, an endowed professor of electrical engineering and computer science at Northwestern University.

It can work very simply. It doesnt need super-computation, its 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.

The study was published in the Journal of Medical Internet Research Public Health and Surveillance.

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Are you willing to get the COVID-19 vaccine? AI says it knows the answer - cleveland.com