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

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2021

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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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