ethics + ai

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Artificial Intelligence and machine learning algorithms operate in societies that are shaped by profound forms of social, material, and political inequality. AI algorithms both exacerbate existing structural inequalities, and create new inequalities. A range of established concerns have emerged, including bias, fairness, accountability, explainability, and responsibility. I am particularly interested in how AI affects marginalized communities, including people of color, precarious workers, women, trans and non-binary, Indigenous, poor, and disabled people, who are all particularly at risk of being adversely affected by AI, whether through increased surveillance, invasions of privacy, misrecognition by facial recognition software, or exclusions from data sets.

Since 2019, I have co-led the creation of the Munich Embedded Ethics Lab at the Technical University of Munich, including the development of the “embedded ethics” methodology for studying social, ethical, and legal considerations of AI development processes. This has included partnerships with robotics developers, STS scholars, and bioethicists. I have a particular interest in the use of AI in mental healthcare.



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