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Podcasts ›› LLM? More Like “Limited” Language Model with Emily M. Bender, University of Washington

LLM? More Like “Limited” Language Model with Emily M. Bender, University of Washington

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As a co-author of the often cited (and debated) Stochastic Parrots paper from 2021, Emily M. Bender is a staunch critic of large language models (LLMs). Having worked in computational linguistics for more than 20 years, Emily’s deep understanding of LLM mechanics has her questioning many of the emerging use cases we see in the world. She joins Robb and Josh for a provocative exploration of generative AI on an important episode of Invisible Machines.

Emily M. Bender is a distinguished computational linguist and professor at the University of Washington, where she has held various faculty positions since 2003. With a rich academic background including an AB in Linguistics from UC Berkeley and a PhD from Stanford University, Bender’s research focuses on multilingual grammar engineering, computational linguistics, and the societal impacts of language technology. She is renowned for her contributions to the development of the LinGO Grammar Matrix, her seminal books on linguistic fundamentals for natural language processing, and her advocacy for ethical considerations in AI research, particularly concerning large language models.

Emily M. Bender gained significant recognition for her pivotal paper titled “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜,” co-authored with Google researcher Timnit Gebru and others, presented at the ACM Conference on Fairness, Accountability, and Transparency in 2021. The paper addressed ethical concerns surrounding the development of natural language processing systems, particularly emphasizing the potential risks associated with large language models trained on vast text corpora. This work contributed substantially to the discourse on AI ethics and played a crucial role in raising awareness about the societal implications of language technology. Also, Emily hosts Mystery AI Hype Theater 3000, where, alongside sociologist Dr. Alex Hanna, she breaks down the AI hype, separates fact from fiction, and distinguishes science from bloviation.

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