Fei-Fei Li is an iconic figure in the field of artificial intelligence and the fight for greater gender diversity in the IT sector. Here’s a portrait of the woman who opened the doors to artificial intelligence as we know it today and raised the first questions about the potential risks associated with its unregulated and exclusive use.
“If you read every AI article and extracted all the names that are cited, we guarantee you that women appear only rarely. For every woman cited on artificial intelligence technologies, there are 100 times as many men cited.” Fei-Fei Li for Bloomberg in 2016 [1].
Fei-Fei Li was born in 1975 in Beijing, China, and arrived in the United States with her parents in 1991. From 1995 to 1999, she studied physics, computer science, and engineering at Princeton University, earning a master’s degree in physics, applied mathematics, and engineering physics. She continued her studies at the California Institute of Technology (Caltech) from 2000 to 2005, where she completed a thesis entitled “Visual Recognition: Computational Models and Human Psychophysics.” After receiving her thesis, Fei-Fei Li joined the University of Illinois as an assistant professor in the Department of Computer Science and Electronics, a position she held until 2006 [2].
Creation of ImageNet
During her academic career, she realized that it was just as, if not more, important to work on the quality and quantity of training data as on the artificial intelligence algorithm used. This realization marked the beginning of her thinking on the development of the ImageNet dataset. As she explained in her TED talk in Vancouver in 2015 [3], if we wanted to enable computers to learn to recognize objects, places and situations like a child would, we would need a phenomenal amount of annotated images to train with.
By accepting a position as assistant professor in the Department of Computer Science at Princeton University in 2007, Fei-Fei Li met Christiane Fellbaum, professor and one of the creators of WordNet, a lexical database, from which she built ImageNet [4]. This database is filled from the approximately 1 billion images present on the Internet and the work of cleaning, sorting and labeling carried out by independent workers (Amazon Mechanical Turk). In 2009, ImageNet had more than 15 million images in 2200 different categories, was presented at the Conference on Computer Vision and Pattern Recognition (CVPR) in Florida and made available as open data to the scientific community.
In 2010 the ILSVRC (ImageNet Large Scale Visual Recognition Challenge) competition was launched, an annual competition where ImageNet is used to evaluate image processing algorithms on their accuracy for several computer vision tasks [5]. The goal of this competition was both to provide a state-of-the-art review of computer vision performance and to promote the development of more efficient techniques [6].
In 2009 she was recruited by Stanford University, where she still works today. From 2013 to 2018 she was the director of the Stanford Artificial Intelligence Laboratory (SAIL).
Co-founding of AI4ALL
In 2015, Olga Russakovsky, one of his PhD students, told him about her idea for a program to open doors to the fields of computer vision, machine learning, deep learning, and cognitive and computational neuroscience for underrepresented people. Fei-Fei Li and Olga Russakovsky, along with Rick Sommer (Executive Director of Pre-College Studies), founded SAILORS, a summer program for high school girls to learn about human-centered AI [7]. In 2017, with the help of several grants, SAILORS became AI4ALL, a national non-profit organization aimed at making AI more diverse and inclusive. From then on, partnerships with different universities multiplied.
As of December 2022, AI4ALL has reached more than 10,000 people in each of the 50 states and around the world. The existence of this type of program is crucial given that only 14% of people working in the world of AI are women and only 11% are Hispanic or Black. However, in addition to the fact that the economic impact of AI continues to grow, these technologies have a growing impact on populations, and a lack of diversity in the scientists behind these technologies can only lead to an increase in the biases associated with them. Fei-Fei Li challenged the US government on this issue during her 2018 testimony for the Science, Space, and Technology Committees: “There is nothing artificial about artificial intelligence: it is inspired by people, created by people, and, most importantly, it impacts people. […] With the right guidance, AI will make life better.” But without it, it is doomed to widen the wealth gap even further, make technology even more exclusive, and reinforce biases we have spent generations overcoming. This will be an ethical, philosophical, and humanist challenge” [8].
Co-founding of HAI
This awareness of the need to regulate the development of artificial intelligence led her to co-found, in 2019, the Human-Centered AI Institute (HAI) at Stanford, where she returned after spending the period 2017-2018 as Vice President and Director of Artificial Intelligence for Google Cloud. The mission of this institute is to continue AI research, regulations and practices to improve the human condition [9].
In 2020 she was elected a member of the United States National Academy of Engineering.
“I believe [AI] is a powerful technology that can make a difference. But all technology is a double-edged sword ,” she warned at the 2019 Grace Hopper Celebration (a ceremony to celebrate women in computing) [10].
This desire to improve AI research while warning of its dangers still follows her today.
Through the numerous conferences she attends and the books she publishes, she informs the scientific community and the general public about the positive and negative effects that this technology can have and the need to think about its development by and for humans. She met President Biden in June 2023, as a member of the working group dedicated to the establishment of the NAIRR (National Artificial Intelligence Research Resource), a federal resource aimed at making data, algorithms and computing resources available. In July, a bill was introduced to establish the NAIRR in order to provide researchers with the
resources needed to develop AI safely. In 2023 she was named among the 100 most influential people in AI [11].
Sources:
[1] Bloomberg Professional Services. (2017, March 28). Artificial intelligence has a ‘sea of dudes’ problem | Insights | Bloomberg Professional Services.
https://www.bloomberg.com/professional/blog/artificial-intelligence-sea-dudes-problem/
[2] Fei-Fei Li. https://fr.wikipedia.org/wiki/Fei-Fei_Li
[3] Li, F. (n.d.). How we teach computers to understand pictures [Video]. TED Talks. https://www.ted.com/talks/fei_fei_li_how_we_re_teaching_computers_to_understand_pictures?language=fr. 2015.
[4] ImageNet. https://fr.wikipedia.org/wiki/ImageNet
[5] ImageNet. https://image-net.org/challenges/LSVRC/
[6] Brownlee, J. (2019, July 5). A gentle introduction to the ImageNet Challenge (ILSVRC).
MachineLearningMastery.com. https://machinelearningmastery.com/introduction-to-the-imagenet-large-scale-visual-recognition-challenge-ilsvrc/
[7] Results – AI4ALL. (2022, December 20). AI4ALL. https://ai-4-all.org/about/results/
[8] House Science, Space, and Technology Committee. (2018, June 26). Hearing – AI – With great power comes great responsibility (Event EventID=108474) [Video]. YouTube. https://www.youtube.com/watch?v=_ObbBp5Vo9U
[9] Stanford Institute for Human-Centered Artificial Intelligence. https://hai.stanford.edu/about
[10] GHC19 – Fei Fei Li, talking about who would change AI [Video]. YouTube.
https://www.youtube.com/watch?v=MOxRohTGXt8 (2019, October 13).
[11] Time. (2023, September 7). TIME100 AI. https://time.com/collection/time100-ai/
Written by Loane D.
