Events

Johns Hopkins Institute for Assured Autonomy and the Berman Institute of Bioethics

Present

Tackling the Intractable Problem of Bias

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Passcode: 090299

ABSTRACT

Biases are a major source of harm in our world, and it is now widely recognized that the use of algorithms and AI can maintain, exacerbate, and even create these social, structural, and psychological biases. In response, there have been many proposed measures of bias, aspirational principles, and even proposed regulations and policies to eliminate (algorithmic) biases. Prorfessor Danks argues, though, that most of these responses fail to address the core ethical and societal challenges of bias; at best, they provide very noisy guides that might sometimes be helpful. After surveying these issues, he offers a diagnosis: our solutions have focused on only one of either technical or policy responses, rather than joint technical-policy solutions informed by domain expertise. He provides an example of such a joint solution based on his recent work that integrates bias discovery (technical) with mechanism knowledge (domain expertise) to identify potential responses (policy). While this approach also has flaws, it is better able to identify both sources of problematic bias and potential mitigation actions.