2021-RD-David-Kaiser

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  The interface of artificial intelligence (AI) and machine-learning (ML) techniques with people --- both individuals and groups --- presents special opportunities as well as challenges. The challenges are often described as "algorithmic bias," though there exists a whole range of potential harms and unintended consequences that can arise throughout the entire ML pipeline. Several of these challenges are exacerbated when AI and ML techniques move beyond research settings into real-world applications. The broad aim of new programmatic efforts at MIT on Social and Ethical Responsibilities of Computing (SERC) is to prepare students and facilitate research to address these important challenges.

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