Algorithmic Bias and Risk Assessments: Lessons from Practice
نویسندگان
چکیده
In this paper, we distinguish between different sorts of assessments algorithmic systems, describe our process assessing such systems for ethical risk, and share some key challenges lessons future algorithm audits. Given the distinctive nature function a third-party audit, uncertain shifting regulatory landscape, suggest that second-party are currently primary mechanisms analyzing social impacts incorporate artificial intelligence. We then discuss two kinds assessments: an risk assessment narrower, technical bias assessment. explain how depend on each other, highlight importance situating within its particular socio-technical context, number and, potentially, The discussion builds team’s experience advising conducting clients across industries in last 4 years. Our main goal is to reflect factors potentially ethically relevant use algorithms draw nascent audit industry, hope helping all parties minimize harm from their use.
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ژورنال
عنوان ژورنال: Digital Society
سال: 2022
ISSN: ['2731-4650', '2731-4669']
DOI: https://doi.org/10.1007/s44206-022-00017-z