Emily M. Bender — Author (2)
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? [Book] Goodreads
author: Emily M. Bender / Timnit Gebru publishing house: ACM 2021 - 3
The past 3 years of work in NLP have been characterized by the development and deployment of ever larger language models, especially for English. BERT, its variants, GPT-2/3, and others, most recently Switch-C, have pushed the boundaries of the possible both through architectural innovations and through sheer size. Using these pretrained models and the methodology off fine-tuning them for specific tasks, researchers have extended the state of the art on a wide array of tasks as measured by leaderboards on specific benchmarks for English. In this paper, we take a step back and ask: How big is too big? What are the possible risks associated with this technology and what paths are available for mitigating those risks? We provide recommendations including weighing the environmental and financial costs first, investing resources into curating and carefully documenting datasets rather than ingesting everything on the web, carrying out pre-development exercises evaluating how the planned approach fits into research and development goals and supports stakeholder values, and encouraging research directions beyond ever larger language models.
The AI Con [Book] NeoDB Goodreads Skybridge
The AI Con
author: Emily M. Bender / Alex Hanna publishing house: Harper 2025 - 5
A smart, incisive look at the technologies sold as artificial intelligence, the drawbacks and pitfalls of technology sold under this banner, and why it’s crucial to recognize the many ways in which AI hype covers for a small set of power-hungry actors at work and in the world.

Is artificial intelligence going to take over the world? Have big tech scientists created an artificial lifeform that can think on its own? Is it going to put authors, artists, and others out of business? Are we about to enter an age where computers are better than humans at everything?

The answer to these questions, linguist Emily M. Bender and sociologist Alex Hanna make clear, is “no,” “they wish,” “LOL,” and “definitely not.” This kind of thinking is a symptom of a phenomenon known as “AI hype.” Hype looks and smells It twists words and helps the rich get richer by justifying data theft, motivating surveillance capitalism, and devaluing human creativity in order to replace meaningful work with jobs that treat people like machines. In The AI Con , Bender and Hanna offer a sharp, witty, and wide-ranging take-down of AI hype across its many forms.

Bender and Hanna show you how to spot AI hype, how to deconstruct it, and how to expose the power grabs it aims to hide. Armed with these tools, you will be prepared to push back against AI hype at work, as a consumer in the marketplace, as a skeptical newsreader, and as a citizen holding policymakers to account. Together, Bender and Hanna expose AI hype for what it a mask for Big Tech’s drive for profit, with little concern for who it affects.