Workshopbeitrag

Audit, Don’t Explain – Recommendations Based on a Socio-Technical Understanding of ML-Based Systems

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Text/Workshop Paper
Datum
2021
Autor:innen
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Quelle
Mensch und Computer 2021 - Workshopband
MCI-WS02: UCAI 2021: Workshop on User-Centered Artificial Intelligence
Verlag
Gesellschaft für Informatik e.V.
Zusammenfassung
In this position paper, I provide a socio-technical perspective on machine learning-based systems. I also explain why systematic audits may be preferable to explainable AI systems. I make concrete recommendations for how institutions governed by public law akin to the German TÜV and Stiftung Wartentest can ensure that ML systems operate in the interest of the public.
Beschreibung
Heuer, Hendrik (2021): Audit, Don’t Explain – Recommendations Based on a Socio-Technical Understanding of ML-Based Systems. Mensch und Computer 2021 - Workshopband. DOI: 10.18420/muc2021-mci-ws02-232. Bonn: Gesellschaft für Informatik e.V.. MCI-WS02: UCAI 2021: Workshop on User-Centered Artificial Intelligence. Ingolstadt. 5.-8. September 2021
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