Neuro-symbolic systems for Responsible AI
Year: 2025
Type: article
Abstract: Keynote talk at PFIA 2025 in Burgundy, France: https://pfia2025.u-bourgogne.fr/invites/ Machine learning (ML) techniques have become pervasive across a range of different applications, and are now widely used in areas as disparate as recidivism prediction, consumer credit-risk analysis, and insurance pricing. Likewise, in the physical world, ML models are critical components in autonomous agents such as robotic surgeons and self-driving cars. Among the many dimensions that arise in the use of ML technology in such applications, analysing properties such as correctness, fairness, and so on is both immediate and profound. In this talk, we advocate for a two-pronged approach to ethical/resposible decision-making enabled using rich models of autonomous agency: on the one hand, we need to draw on philosophical notions of such as beliefs, causes, effects and intentions, and on the other, we consider the problem of practical and effective knowledge acquisition and learning
Author: Belle, Vaishak
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7078247705
FWCI:
Cites:
Cited by:
Related to: