Comparing Decision Makers: Theory and Implications for AI — NSF Award to Massachusetts Institute of Technology (MA, $460,999)
This project develops a new method for comparing human and artificial intelligence (AI) decision-making, generating insight on how to combine human and AI input in high-stakes decisions like medical diagnoses. While researchers can easily observe an AI tool’s prediction process, human decision-making is more complicate
| Award title | Comparing Decision Makers: Theory and Implications for AI |
|---|---|
| Award ID | 2519938 |
| Awardee | Massachusetts Institute of Technology |
| City | CAMBRIDGE |
| State | MA |
| Amount obligated | $460,999 |
| Principal investigator | Nikhil Agarwal |
| Program | Economics |
| Start date | 08/01/2025 |
| Abstract | This project develops a new method for comparing human and artificial intelligence (AI) decision-making, generating insight on how to combine human and AI input in high-stakes decisions like medical diagnoses. While researchers can easily observe an AI tool’s prediction process, human decision-making is more complicated. For example, a radiologist’s diagnostic decisions may reflect both their judgments about the presence of cancer and their assessments of the cost of an incorrect diagnosis, but |
| Source | NSF Awards |
$799/mo
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