Collaborative Research: EAGER: FDASS: Interrogating Conflicting Accountabilities — NSF Award to New York University (NY, $93,620)
Software systems, including Artificial Intelligence (AI) systems, have been rapidly and increasingly adopted to enact policy in public administration. The resulting interactions between policymaking and AI adoption are complex and social, legal, and technical, yet research-driven policy guidance is sorely lacking. This
| Award title | Collaborative Research: EAGER: FDASS: Interrogating Conflicting Accountabilities |
|---|---|
| Award ID | 2532415 |
| Awardee | New York University |
| City | NEW YORK |
| State | NY |
| Amount obligated | $93,620 |
| Principal investigator | Simone Zhang |
| Program | DASS-Dsgng Accntble SW Systms |
| Start date | 10/01/2025 |
| Abstract | Software systems, including Artificial Intelligence (AI) systems, have been rapidly and increasingly adopted to enact policy in public administration. The resulting interactions between policymaking and AI adoption are complex and social, legal, and technical, yet research-driven policy guidance is sorely lacking. This research intervenes on the lack of empirical evidence about how accountability structures interact and evolve when automated decision systems are deployed in public sector organiz |
| Source | NSF Awards |
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