AI in Healthcare and the Public Sector: How to Face the Challenges of High-Risk Applications and What AI Research Can Get Out of It
| dc.contributor.author | Braun, Tanya | |
| dc.contributor.author | Möller, Ralf | |
| dc.date | 2024-11-01 | |
| dc.date.accessioned | 2025-01-13T11:15:16Z | |
| dc.date.available | 2025-01-13T11:15:16Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Application projects, may it be in healthcare and the public sector or elsewhere, have the potential to advance foundational (“genuine”) artificial intelligence (AI) research. Unfortunately, insights from specific application projects are rarely propagated back to AI research. This article argues for ways to facilitate such backpropagation and how the contributions in this special issue enable exactly this backpropagation. It also addresses the challenges that come along with high-risk application project, which frequently occur in the area of healthcare and the public sector due to the sensitivity of the subjects. | de |
| dc.identifier.doi | 10.1007/s13218-024-00853-w | |
| dc.identifier.issn | 1610-1987 | |
| dc.identifier.uri | http://dx.doi.org/10.1007/s13218-024-00853-w | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/45570 | |
| dc.publisher | Springer | |
| dc.relation.ispartof | KI - Künstliche Intelligenz: Vol. 38, No. 3 | |
| dc.relation.ispartofseries | KI - Künstliche Intelligenz | |
| dc.title | AI in Healthcare and the Public Sector: How to Face the Challenges of High-Risk Applications and What AI Research Can Get Out of It | de |
| dc.type | Text/Journal Article | |
| mci.reference.pages | 119-126 |