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Algorithm predicts future crimes with 90% accuracy + Model 4 predicting belief change

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Here’s why the creator thinks the tech won’t be abused
https://www.sciencefocus.com/news/algori...be-abused/

EXCERPTS: The AI model was tested across eight cities in the US and predicts future crimes with 80 to 90 per cent accuracy, without falling foul of bias.

Prof Ishanu Chattopadhyay leads the ZeD Lab at the University of Chicago, where he studies algorithms and data. He tells us about the AI he has developed that can forecast crimes being committed days before they actually occur.

[...] How do you envisage the ways your algorithm could be used?

People have concerns that this will be used as a tool to put people in jail before they commit crimes. That’s not going to happen, as it doesn’t have any capability to do that. It just predicts an event at a particular location. It doesn’t tell you who is going to commit the event or the exact dynamics or mechanics of the events. It cannot be used in the same way as in the film Minority Report... (MORE - missing details)

PAPER: https://www.nature.com/articles/s41562-022-01372-0


New model for predicting belief change
https://www.santafe.edu/news-center/news...ief-change

RELEASE: A new kind of predictive network model could help determine which people will change their minds about contentious scientific issues when presented with evidence-based information.

A study in Science Advances presents a framework to accurately predict if a person will change their opinion about a certain topic. The approach estimates the amount of dissonance, or mental discomfort, a person has from holding conflicting beliefs about a topic.

Santa Fe Institute Postdoctoral Fellows Jonas Dalege and Tamara van der Does built on previous efforts to model belief change by integrating both moral and social beliefs into a statistical physics framework of 20 interacting beliefs.

They then used this cognitive network model to predict how the beliefs of a group of nearly 1,000 people, who were at least somewhat skeptical about the efficacy of genetically modified foods and childhood vaccines, would change as the result of an educational intervention.

Study participants were shown a message about the scientific consensus on genetic modification and vaccines. Those who began the study with a lot of dissonance in their interwoven network of beliefs were more likely to change their beliefs after viewing the messaging, but not necessarily in accordance with the message. On the other hand, people with little dissonance showed little change following the intervention.

"For example, if you believe that scientists are inherently trustworthy, but your family and friends tell you that vaccines are unsafe, this is going to create some dissonance in your mind," van der Does says. "We found that if you were already kind of anti-GM foods or vaccines to begin with, you would just move more towards that direction when presented with new information even if that wasn't the intention of the intervention."

While still in an early stage, the research could ultimately have important implications for communicating scientific, evidence-based information to the public.

"On the one hand you might want to target people who have some dissonance in their beliefs, but at the same time this also creates some danger that they will reduce their dissonance in a way that you didn't want them to," Dalege says. "Moving forward, we want to expand this research to see if we can learn more about why people take certain paths to reduce their dissonance."
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