Fei-Fei Li

After researchers including Kate Crawford documented pervasive bias in ImageNet's person categories -- including racist slurs, misogynist labels, and ableist classifications -- Fei-Fei Li's team systematically identified non-visual concepts and offensive categories. They proposed and executed removal of 1,593 categories (54% of the 2,932 person categories), addressing both bias and privacy concerns in the foundational AI dataset. This represented a significant acknowledgment that even groundbreaking datasets require ongoing ethical review and correction.

In March 2019, Fei-Fei Li co-founded Stanford's Institute for Human-Centered Artificial Intelligence (HAI) with philosopher John Etchemendy. HAI focuses on advancing AI research, education, policy and practice to improve the human condition. The institute has trained 80+ congressional staffers through bipartisan boot camps, 8,000+ government employees through educational programs, informed the EU AI Act, published the influential annual AI Index Report, and advocated for the National AI Research Resource (NAIRR). Li served on the White House NAIRR Task Force and has provided U.S. Senate and Congressional testimonies on AI governance.

During her role as Chief Scientist of AI/ML at Google Cloud (2017-2018), leaked internal emails revealed that Fei-Fei Li expressed enthusiasm for Google Cloud's role in Project Maven, a Pentagon drone image analysis contract, but cautioned colleagues to avoid mentioning the AI component, writing 'This is red meat to the media to find all ways to damage Google.' She later told the NYT: 'I believe in human-centered AI to benefit people in positive and benevolent ways. It is deeply against my principles to work on any project that I think is to weaponize AI.' She departed Google Cloud in October 2018 following the controversy.

In 2015, Fei-Fei Li co-founded SAILORS (Stanford AI Lab OutReach Summer program) at Stanford to familiarize high school girls with AI. In 2017, the program expanded into AI4ALL, a national nonprofit co-founded with Olga Russakovsky and Rick Sommer, with funding from Melinda French Gates/Pivotal Ventures and Jensen Huang. AI4ALL promotes education, mentorship, and support for underrepresented communities in AI, including women, people of color, and low-income individuals. By 2022, AI4ALL had reached over 10,000 people across all 50 US states, growing from 1 to 16 university partnerships.

Starting in 2007, Fei-Fei Li led the creation of ImageNet, a visual database of over 14 million labeled images that catalyzed the deep learning revolution. The ImageNet Large Scale Visual Recognition Challenge (ILSVRC) spurred breakthroughs including AlexNet in 2012. ImageNet became foundational to modern AI. However, the dataset later faced criticism for biased and offensive labels in person categories and privacy violations from using photos without consent. Li's team responded by removing 1,593 offensive person categories (54% of person categories) from the dataset.