Algorithmic Fairness from a Sociotechnical Lens

Books, films and television increasingly portray artificial intelligence as poised to reshape modern society. Yet many real-world AI systems deployed so far have manifested salient societal risks with the potential for acute harms to historically marginalized peoples. In response, various stakeholders have sought to propose ethical guidelines and technical mitigations to serve as ethical guardrails for future technology deployment and development.

In this talk, William Isaac will propose that in order for ethical frameworks and technical mitigations to be effective in realigning technology for socially beneficial outcomes, social and historical insights must be meaningfully taken into account. Using examples from multiple domains in the context of algorithmic fairness, he will discuss how critical evaluations which blend insight from data science and the social sciences can lead to a dynamic sociotechnical “lens” to mitigate societal harms and identify socially beneficial applications. He will conclude the lecture by discussing potential challenges to adopting a sociotechnical lens in practice and highlight open questions for future research.

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• Wear a mask while in the auditorium and restrooms

Please note that by entering the Simons Foundation, you are attesting that you are not experiencing COVID symptoms and are not knowingly positive for COVID