Algorithmic Fairness from a Sociotechnical Lens
William Isaac, Ph.D.Research Scientist, DeepMind
Simons Foundation Presidential Lectures are free public colloquia centered on four main themes: Biology, Physics, Mathematics and Computer Science, and Neuroscience and Autism Science. These curated, high-level scientific talks feature leading scientists and mathematicians and are intended to foster discourse and drive discovery among the broader NYC-area research community. We invite those interested in the topic to join us for this weekly lecture series.
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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