Bender was born in 1973, the daughter of the writer Sheila Bender, with whom she later co-wrote a two-part essay, "More than your English teacher ever told you," for her mother's online magazine, Writing It Real. In high school, she told New York magazine, she declared that she wanted to learn to talk to everyone on earth. She took her first linguistics class at the University of California, Berkeley in the spring of 1992, her freshman year, and in 1993 she took Intro to Morphology and Intro to Programming in the same term. After her teaching assistant presented a grammatical analysis of a Bantu language, she wrote a program to implement it, longhand on paper, at a bar near campus while her boyfriend, the computer scientist Vijay Menon, watched a basketball game. It ran when she typed it in. The TA shrugged. "If I had shown that to somebody who knew what computational linguistics was," she said later, "they could have said, 'Hey, this is a thing.'"

She spent 1993 to 1994 at Tohoku University in Sendai on a Japanese Ministry of Education fellowship and graduated from Berkeley in 1995 with the University Medal, given to one graduating senior each year. Her CV lists advanced Japanese and French, intermediate Mandarin and American Sign Language, and beginning Malayalam and German. At Stanford, on a National Science Foundation fellowship, she joined the Head-Driven Phrase Structure Grammar (HPSG) and LinGO projects at the Center for the Study of Language and Information (CSLI). Her dissertation, completed in October 2000 under Thomas Wasow and Penelope Eckert with John Rickford, Ivan Sag and Arnold Zwicky on the committee, asked how a formal competence grammar could accommodate copula absence in African American English, a variable whose use is shaped by social meaning rather than by categorical rules.

For three years after the PhD she kept a foot in academia and one in industry. She taught at Berkeley and Stanford, co-wrote the 2003 second edition of Sag and Wasow's textbook Syntactic Theory: A Formal Introduction, and worked in 2001 and 2002 as a grammar engineer for Japanese at a start-up, YY Technologies. With Melanie Siegel she described the Japanese HPSG grammar Jacy in 2002, and the two documented it with Francis Bond in a 2016 book.

Her best-known technical project grew out of that work. The hand-built precision grammars of English, German and Japanese had each taken between 5 and 15 person-years and ran to 35,000 to 70,000 lines of code, and their accumulated analyses were, as she and her co-authors put it, "only available through painstaking inspection of the grammars and/or consultation with their authors." In 2002, with Dan Flickinger and Stephan Oepen, she proposed the Grammar Matrix, a starter kit that distils what the existing grammars share into a reusable core, so that a grammar for a new language could start from a cross-linguistically tested base and produce the same kind of semantic representations. An NSF CAREER grant of $474,229 in 2007 funded the work on the Matrix as "computational linguistic typology." With Fei Xia she then started the AGGREGATION project, which tries to generate grammars automatically from the interlinear glossed text that field linguists already produce, for the benefit of language documentation. Her students have extended the Matrix with libraries for evidentiality, information structure and noun incorporation, and her student Joshua Crowgey wrote his 2019 dissertation on grammar engineering for Lushootseed, a Salish language of Puget Sound. A 2022 retrospective in the Journal of Language Modelling, "20 years of the Grammar Matrix," described how it had been used to test hypotheses about increasingly complex interactions between phenomena across languages.

The University of Washington hired her in 2003, and in 2005 she launched its professional master's program in computational linguistics (CLMS), offered both in Seattle and online, which she has directed ever since while also running the department's Computational Linguistics Laboratory. At conferences of the Association for Computational Linguistics she noticed that many people building language technology knew little linguistics, and she began giving tutorials under titles such as "100 Things You Always Wanted to Know About Linguistics But Were Afraid to Ask." She later wrote two short books for practitioners, Linguistic Fundamentals for Natural Language Processing (2013) and a second volume on semantics and pragmatics with Alex Lascarides (2019). New York magazine reported that when an Amazon recruiter approached her and she declined, he asked, "You're not even going to ask how much?"

A theme ran through all of it: most of the field worked on English and treated English as the default. In a 2011 paper she wrote, "Do state the name of the language that is being studied, even if it's English." In November 2018, frustrated again, she tweeted that "Natural Language" is not a synonym for "English." In the spring of 2019 Nathan Schneider, Yuval Pinter, Robert Munro and Andrew Caines independently began calling the practice the "Bender Rule," and posters at NAACL and ACL that summer cited it by name. In a September 2019 essay for The Gradient she said she was happy to lend her name to a principle that "seems obvious and trivial," because the field would not broaden beyond a handful of languages until it stopped pretending that work on English alone was not language-specific. The same concern produced Data Statements for Natural Language Processing (2018), written with Batya Friedman, which asks dataset builders to record which speakers, varieties and annotators a corpus represents. She began teaching a seminar on ethics in language technology in 2017 and co-chaired the ethics review committee for NAACL 2021.

By 2019 language models such as BERT and GPT-2 were topping benchmarks that were supposed to require understanding, and papers and press coverage said the models "understood" language. Bender and Alexander Koller of Saarland University answered at ACL in July 2020 with a position paper, "Climbing towards NLU." Its argument turned on a thought experiment. Two people stranded on separate islands talk by telegraph; a hyper-intelligent deep-sea octopus taps the cable, learns to predict their messages, and eventually impersonates one of them. It gets away with small talk, but when the other islander is chased by a bear and asks how to build a weapon from sticks, the octopus has nothing to offer, because it has only ever seen the form of the words. Bender first told the story with a dolphin; Koller argued for an octopus, whose world is further from ours and which is, she said later, "just inherently funnier." A footnote records that when they gave the bear prompt to GPT-2, it replied, "You're not going to get away with this!" The paper won ACL 2020's Best Theme Paper award.

That autumn Bender and Timnit Gebru, then co-lead of Google's Ethical AI team, wrote "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?" with Angelina McMillan-Major, Bender's PhD student, and Margaret Mitchell, a former student of hers who co-led the Google team. Bender came up with the title phrase while drafting. In early October 2020, she has written, a Google search for "stochastic parrot" returned zero hits. She later learned of a July 2020 blog post by Regina Rini that mentioned a "statistical parrot," and recalled that Stuart Russell had emailed her and Koller in September 2020 praising the octopus paper as "a breath of sanity" amid the field's enthusiasm for "randomized parrots"; she offered him a footnote and he declined. When Google told its employees to withdraw from the paper, Gebru set conditions for staying and left the company in December 2020, in circumstances she describes as a firing and Google as a resignation. MIT Technology Review, which obtained the draft from Bender, summarized it on 4 December; she asked the magazine not to name the Google co-authors "for fear of repercussions," and noted that as a tenured professor she was protected by academic freedom. Mitchell was fired in February 2021. The paper appeared at the ACM FAccT conference in March 2021 with Mitchell listed as "Shmargaret Shmitchell" and an acknowledgment that some of its seven authors had been required by their employer to remove their names. Four days after ChatGPT's release, on 4 December 2022, Sam Altman posted, "i am a stochastic parrot, and so r u."

Bender told New York magazine that in 2016, with Donald Trump running for president and Black Lives Matter protests in the streets, she decided to take some small political action every day, and began reading and amplifying Black women who were criticizing AI, including Joy Buolamwini and Meredith Broussard. She also started challenging the term "artificial intelligence" itself, and remains fond of an alternative an Italian former member of parliament proposed, "Systematic Approaches to Learning Algorithms and Machine Inferences," or SALAMI. In July 2022, on a panel at a large computational linguistics conference, she debated the Stanford computational linguist Christopher Manning over whether meaning requires reference to the world; he argued for a broader, distributional notion of meaning, and she told the audience, "I feel like there's too much effort trying to create autonomous machines, rather than trying to create machines that are useful tools for humans."

In August 2022 she and Alex Hanna, then newly director of research at the Distributed AI Research Institute (DAIR), tried a one-off live stream reacting to a piece of AI hype, with a title borrowed from the television show Mystery Science Theater 3000. They surprised themselves by making it a series, and in the spring of 2023 turned the streams into the podcast Mystery AI Hype Theater 3000, produced with Christie Taylor and opened every episode as "a podcast where we seek catharsis in this age of AI hype." They call the method "ridicule as praxis." When the Future of Life Institute called in March 2023 for a six-month pause on training systems more powerful than GPT-4, Bender, Gebru and McMillan-Major replied on 31 March that its "hypothetical risks are the focus of a dangerous ideology called longtermism that ignores the actual harms resulting from the deployment of AI systems today," and that "Accountability properly lies not with the artifacts but with their builders." TIME put her on its first TIME100 AI list that September, and on 18 October 2023 she testified at a joint hearing of two subcommittees of the House Committee on Science, Space, and Technology on managing the risks of AI. Her CV lists consultations that year with the White House Office of Science and Technology Policy, the staff of several senators and representatives, and the Federal Trade Commission's chief technologist.

Bender was elected vice president-elect of the Association for Computational Linguistics in November 2021 and served as its president in 2024; her presidential address at ACL 2024 in Bangkok on 14 August was titled "ACL Is Not an AI Conference." In March 2025 she debated Sébastien Bubeck of OpenAI, lead author of the "Sparks of Artificial General Intelligence" paper, at the Computer History Museum in Mountain View on the question "Do LLMs really understand?" Bubeck said "understanding is in the eye of the beholder"; Bender said that the claim that they understand was extraordinary, needed extraordinary evidence, and could not be checked while the data behind it stayed hidden.

The AI Con: How to Fight Big Tech's Hype and Create the Future We Want, written with Hanna, was published by Harper on 13 May 2025 and by the Bodley Head in Britain on 22 May, with Spanish and Italian translations following in 2026. It proposes replacing "AI" with the specific automation being sold, calling chatbots "conversation simulators," and meeting unfit deployments with "strategic refusal." Its argument about work, as Hanna put it in interviews, is that AI "is not going to take your job, but it will likely make your job shittier." In June 2025 they wrote in Tech Policy Press that "AGI" is a vague signifier and "conveniently also a means to avoid accountability." She took the argument to the European Parliament's special committee on the European Democracy Shield in July 2025 and to UNESCO's Digital Learning Week in September 2025, where her lecture was titled "We do not have to accept AI (much less AGI) as inevitable in education." On the paper's fifth anniversary, in May 2026, she published "Stochastic Parrots: Frequently Unasked Questions," and told IEEE Spectrum in June 2026 that the paper's biggest omission was exploitative labor, both the conditions of data workers and "the massive theft of people's creative and intellectual output." Her CV, updated in July 2026, lists her as Wyckoff Endowed Professor for 2024 to 2027 and records appearances in two 2026 documentaries, Valerie Veatch's Ghost in the Machine and a Focus Features film, The AI Doc.