Tipus de document

Article

Versió

Versió publicada

Data de publicació

Llicència de publicació

cc-by-nc (c) Subías Beltrán, Paula et al., 2025
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/231472

Safeguarding Autonomy: a Focus on Machine Learning Decision Systems

Títol de la revista

Director/Tutor

ISSN de la revista

Títol del volum

Resum

As global discourse on AI regulation gains momentum, this paper focuses on delineating the impact of ML on autonomy and fostering awareness. Respect for autonomy is a basic principle in bioethics that establishes people as decision-makers. While the concept of autonomy in the context of ML appears in several European normative publications, it remains a theoretical concept that has yet to be widely accepted in ML practice. Our contribution is to bridge the gap between theory and practice in ML by encouraging the respect of autonomy in ML-aided decision-making. We do this by proposing a clear framework for operationalizing autonomy and identifying the conditioning factors that currently prevent it. Consequently, we focus on the different stages of the ML pipeline to identify the potential effects on ML end-users’ autonomy. To improve its practical utility, we propose a related question for each detected impact, offering guidance for identifying possible focus points to respect ML end-users autonomy in decision-making.

Citació

Citació

SUBÍAS BELTRÁN, Paula, PUJOL VILA, Oriol and LECUONA RAMÍREZ, Itziar de. Safeguarding Autonomy: a Focus on Machine Learning Decision Systems. Cognitive Systems Research. 2025. Vol. 94. ISSN 1389-0417. [consulted: 24 of September of 2026]. Available at: https://hdl.handle.net/2445/231472

Exportar metadades

JSON - METS

Compartir registre