Collaborative Research: ReDDDoT Phase 2: Enabling Participatory Privacy Protections for AI — NSF Award to FRED HUTCHINSON CANCER C
Artificial intelligence (AI) works by learning from patterns in data. Building AI technologies depends on acquiring data for training models. Responsible development of AI as part of public interest technology (PIT) requires building AI that benefits the public interest while safeguarding data used to power AI systems.
| Award title | Collaborative Research: ReDDDoT Phase 2: Enabling Participatory Privacy Protections for AI |
|---|---|
| Award ID | 2429840 |
| Awardee | FRED HUTCHINSON CANCER CENTER |
| City | SEATTLE |
| State | WA |
| Amount obligated | $120,511 |
| Principal investigator | Sean Kross |
| Program | ReDDDoT-Resp Des Dev & Dp Tech |
| Start date | 10/01/2024 |
| Abstract | Artificial intelligence (AI) works by learning from patterns in data. Building AI technologies depends on acquiring data for training models. Responsible development of AI as part of public interest technology (PIT) requires building AI that benefits the public interest while safeguarding data used to power AI systems. Safeguarding data require tradeoffs between the level of protection provided and the usefulness of the models created with the data. These tradeoffs create a tension that PIT orga |
| Source | NSF Awards |
$799/mo
Try NSFGrants →