The history of AI is often told through a handful of famous men. But many of the field’s foundational ideas, datasets, tools and ethical frameworks came from women — some of whom received far less recognition than they deserved at the time. Here are some of the figures whose work shapes the AI we use today.

Ada Lovelace (1815–1852)

Working with Charles Babbage on his proposed Analytical Engine, Lovelace wrote what is often considered the first published computer program, in notes from 1843. She also foresaw that computing machines could manipulate symbols beyond numbers, such as music — while cautioning that the engine could not “originate anything”, a remark Alan Turing later discussed as “Lady Lovelace’s objection” in his 1950 paper on machine intelligence.

Grace Hopper (1906–1992)

A US Navy rear admiral and computing pioneer, Hopper developed one of the first compilers and championed programming languages closer to English, influencing COBOL. Her work made programming accessible to far more people — a foundation for all software, including AI.

Karen Spärck Jones (1935–2007)

A British computer scientist, Spärck Jones introduced inverse document frequency (IDF) in 1972, a way of weighting terms by how rare they are across documents. Combined with term frequency as TF–IDF, it became a cornerstone of search engines and information retrieval, and remains relevant in retrieval systems used with language models today.

Fei-Fei Li

A professor at Stanford, Fei-Fei Li led the creation of ImageNet, a dataset of millions of labelled images organized into thousands of categories. The associated ImageNet challenge became the benchmark where deep learning’s breakthrough happened in 2012 with AlexNet. Li co-directs Stanford’s Institute for Human-Centered AI, co-founded the nonprofit AI4ALL to increase diversity in AI, and founded World Labs, a company working on spatial intelligence. She is often called the “godmother of AI”.

Daphne Koller

A Stanford professor known for her work on probabilistic graphical models and machine learning, Koller co-founded Coursera in 2012 with Andrew Ng, bringing university courses — including influential machine learning courses — to millions online. She later founded insitro, a company applying machine learning to drug discovery.

Cynthia Breazeal

A pioneer of social robotics at the MIT Media Lab, Breazeal built Kismet in the late 1990s, a robot head designed to engage in social interaction with expressive faces, and has worked on robots and AI for education and families.

Joy Buolamwini

As a researcher at the MIT Media Lab, Buolamwini co-authored the 2018 Gender Shades study with Timnit Gebru, which found that commercial facial analysis systems had much higher error rates for darker-skinned women than for lighter-skinned men. The work prompted companies to improve their systems and influenced debates about facial recognition regulation. She founded the Algorithmic Justice League.

Timnit Gebru

A computer scientist who co-led Google’s Ethical AI team, Gebru co-authored Gender Shades and the influential paper on the risks of large language models, On the Dangers of Stochastic Parrots (2021). Her departure from Google in late 2020 drew widespread attention to research independence in industry. She founded the Distributed AI Research Institute (DAIR).

Many others

This list is far from complete. Women have led major contributions in reinforcement learning, robotics, natural language processing, AI policy, and the safety and ethics fields — and many teams building today’s AI systems are led by women researchers and engineers.

Why representation matters

Diverse teams are more likely to notice problems — like biased datasets or harmful use cases — that homogeneous teams miss. Organizations such as AI4ALL, Women in Machine Learning (WiML) and Black in AI work to broaden participation in the field.

What to watch next

  • Programs that broaden participation in AI education and research.
  • Recognition of historical contributions in AI and computing.
  • Research on bias and fairness led by diverse teams.
  • Women founders and leaders at AI labs and startups.

Key takeaways

  • Ada Lovelace wrote what is often considered the first published computer program.
  • Karen Spärck Jones introduced inverse document frequency, foundational to search.
  • Fei-Fei Li led ImageNet, the dataset behind the 2012 deep learning breakthrough.
  • Gender Shades by Buolamwini and Gebru exposed bias in facial analysis systems.
  • Diverse teams help identify problems homogeneous teams miss.

Frequently asked questions

Who is called the godmother of AI?

Fei-Fei Li is often called the godmother of AI for her role in creating ImageNet and advocating human-centered AI.

What was the Gender Shades study?

A 2018 study by Joy Buolamwini and Timnit Gebru showing that commercial facial analysis systems performed worst on darker-skinned women.

How can more women get into AI?

Through education programs, mentorship and communities such as AI4ALL, WiML and others that support people entering the field.