Audit, Dont Explain -- Recommendations Based on a Socio-Technical Understanding of ML-Based Systems

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 TUV and Stiftung Warentest can ensure that ML systems operate in the interest of the public.