What is it about?

AI encompasses many tools and perspectives that are useful to basic science, including tools for prediction and summarizing data. Likewise, the tools of decision science and psychology can help open up and understand the "black box" of AI models.

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Why is it important?

Machine learning tools developed in AI research are being rapidly developed, and they can open up new theoretical approaches that basic science has not been able to breach before. The reason is that they allow us to use "simulation-based" models -- those that are driven by computation rather than by elegant mathematical formulations. Many natural systems, including the human mind, are unlikely to have these elegant mathematical descriptions -- meaning that the tools of AI can be used to create better and better models of how the human mind works by subverting the limitations of traditional modeling approaches. This perspective piece also looks at how decision science -- which specializes in understanding how a "hidden" system (the mind / brain) works from its observed behavior -- can be used to inform our understanding of AI systems. The same experimental manipulations we use to study human behavior can also be applied to AI behavior, so that we better understand why and how they do what they do.

Perspectives

This is a forward-looking piece about the role of AI in decision research and the role of decision research in AI. My hope is that the two fields can grow together, and that this paper will help chart the course for future collaborations between the fields.

Dr. Peter Kvam
Ohio State University

Read the Original

This page is a summary of: Using artificial intelligence to fit, compare, evaluate, and discover computational models of decision behavior., Decision, August 2024, American Psychological Association (APA),
DOI: 10.1037/dec0000237.
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