Rayid Ghani How AI/ML Can Both Predict and Shape Patient Behavior

Episode Summary

In this week’s show, Harry interviews Rayid Ghani, a computer scientist at Carnegie Mellon University who studies how to use AI and data science to model and influence people’s behavior in realms like politics, healthcare, education, and criminal justice.

Episode Notes

In this week’s show, Harry interviews Rayid Ghani, a computer scientist at Carnegie Mellon University who studies how to use AI and data science to model and influence people’s behavior in realms like politics, healthcare, education, and criminal justice.

Ghani tells Harry he grew up hating coding since the very need for it showed that “computers are really stupid and dumb.” But Ghani says he eventually realized that machine learning can change that by allowing programmers to teach computers the rules of the game, at which point they can improve on their own and learn to solve real problems.

Ghani went on to become chief data scientist for the 2012 Obama campaign, and he has since used what he learned about data analytics to study applications of AI to large-scale social problems in many areas, including healthcare. He’s currently a Distinguished Career Professor in the Machine Learning Department at Carnegie Mellon University’s School of Computer Science.

In political campaigns, Ghani says, machine learning and other forms of AI are used not just to predict voter behavior but, in combination with behavioral psychology insights, to change it. “Why not do the same thing for issues with effects that are much, much broader?” he asks. “In health, we do fairly macro policies around ‘everybody should get this vaccine.’ But often you don’t have enough resources to make sure that happens.” AI and machine learning may be able to help by predicting who needs help the most and then persuading them to make the necessary changes—for example, changing their diet and lifestyle to avoid Type 2 diabetes. But it’s all a tricky area to study, he says. “Those are the two things we need to couple together—prediction combined with behavior change—and that requires both the data about these individuals and, more importantly, creates ethical issues about how we test these ideas.”

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