Algorithmic unfairness, infrastructure & genealogies of data | Alex Hanna, Google | DISCOVERY

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AI for Good

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Published on April 13, 2022 12:00:00 AM ● Video Link: https://www.youtube.com/watch?v=j8hn-EMQFhc

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This AI and Health Discovery discusses the problems of algorithmic bias and datasets used in machine learning and AI systems. Join Alex Hanna, a researcher on the Ethical AI team at Google, to uncover deeper issues with data used in AI, including problematic categorizations and the extractive logics of crowd work and data mining. This talk will first focus on reframing data as a form of infrastructure, and as such, implicating politics and power in the construction of datasets. Secondly, it discusses the development of a research program around the genealogy of datasets used in machine learning and AI systems. It will present why these genealogies should be attentive to the constellation of organizations and stakeholders involved in their creation, including the intent, values, and assumptions of their authors and curators, and the adoption of datasets by subsequent researchers to ensure fairness in automated decision-making systems.

🎙 Speakers:
Alex Hanna, Director of Research, Distributed AI Research Institute (DAIR)

Shownotes ⏱
00:00 Intro
01:52 Panelist intro
04:18 Algorithmic unfairness
11:32 Datasets as infrastructure
31:43 Research program for the Genealogy of Data
50:54 Q&A
1:04:57 Outro


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