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AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery.

AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery.
How do AI agents influence knowledge work? This paper finds that agents shift worker effort from implementation to supervision, which especially benefits verifiable work and expert workers. I use data from the coding platform Cursor to study agents in software production.
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How do AI agents influence knowledge work? This paper finds that agents shift worker effort from implementation to supervision, which especially benefits verifiable work and expert workers. I use data from the coding platform Cursor to study agents in software production.
What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.

What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.
"In this talk, I will argue against one popular socio-technical solution to the problem of opacity: rationale explanations. Such explanations are taken to achieve many important political values enabled by explanations, such as trust, recourse, respect, and accountability, as well as to enable decision-makers to comply with GDPR. For example, by providing data subjects with a single or small set of counterfactuals that link specific inputs to a desired output value, rationale explanations based on counterfactuals enable individuals to achieve recourse. However, I argue that rationale explanations are often not the best means to enable the relevant political values. The general insight is that rationale based explanations combine two different types of politically important explanations: causal explanations, that give individuals the information needed to adjust their behavior, and normative explanations, which justify the use of the system or a particular application of it." - Kate Vredenburgh
