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New Language-Learning Algorithms Risk Reinforcing Inequalities, Social Fragmentation, per U-M Study

April 27, 2022

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5-15 mins
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Presented by Michigan News

Shobita Parthasarathy, director of the U-M Ford School of Public Policy Science, Technology, and Public Policy Program (STPP), and Johanna Okerlund, postdoctoral fellow and report co-author, discuss new research on large language models (LLMs). Recent findings show that LLMs have the potential to benefit society but could likely reinforce inequalities and social fragmentation. Parthasarathy and Okerlund note that these machine learning algorithms could tax the environment and place more power in the hands of tech giants, elaborating on the multiple factors that could emphasize inequity within society. They highlight their study and results from their research, offering policy recommendations.

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