Teaching computers to see and societies to compute
Introduction to Fei-Fei Li
**Dr. Fei-Fei Li** is a pioneer of **artificial intelligence** and one of today’s most influential women in technology. She is a Professor in the Computer Science Department at Stanford University, and Co-Director of Stanford’s Human-Centered AI Institute.
She cofounded AI4ALL, a non-profit aimed at improving diversity in the field of AI, and, together with her team at Stanford, is aiming to instill human sensitivity to artificially intelligent algorithms. She is also known for her work on the ImageNet project, which is a database of over 15 million images that help ‘train’ computers to recognize and understand pictures.
Li’s Early Life & Higher Education
Fei-Fei Li was born in **Beijing** and grew up in **Chengdu**, southern China, and, as a child, kept mostly to herself. When she was 12, her father emigrated to the US and settled in **Parsippany, New Jersey**; Li and her mother joined him when Li was 16.
Within a couple of years, Li had very good command of the English language and was excelling at school. She was so advanced in math that her high school math instructor, Bob Sabella, put together an ad hoc version of an advanced calculus class, which he taught Li during lunch breaks. Li graduated from Parsippany High School in 1995; she was inducted in the school’s Hall of Fame in 2017.
After graduating from Parsippany High School in 1995, Fei-Fei Li earned a scholarship to study **physics, computer science** and **engineering** at Princeton University, graduating with honors. In 2000, she started her PhD in electrical engineering at the California Institute of Technology (Caltech) and graduated in 2005 with her dissertation titled Visual Recognition: Computational Models and Human Psychophysics.
Li’s Career
Li is currently the inaugural Sequoia Professor in the Computer Science Department at Stanford University, and Co-Director of Stanford’s Human-Centered AI Institute. Her main research areas are in **machine learning, deep learning, computer vision** and **cognitive and computational neuroscience**.
Prior to Stanford and following the completion of her PhD at Caltech, Li worked as an assistant professor in the Electrical and Computer Engineering Department at University of Illinois Urbana-Champaign, and then joined the Computer Science Department at Princeton University.
In 2009, Li moved to Stanford as an assistant professor, becoming professor in 2017 and serving as the Director of Stanford’s AI Lab from 2013 to 2018. During a sabbatical from Stanford in 2017-18, she worked at Google as Vice President and served as Chief Scientist of AI/ML at Google Cloud.
Li on ImageNet
Fei-Fei Li is mostly known for her work as a leading scientist and principal investigator on the ImageNet project, which is a database of over 15 million images. ImageNet is a large database that helps ‘train’ computers to identify and comprehend what’s in a picture, thus revolutionizing the field of large-scale visual recognition.
ImageNet is a large image dataset organized according to the WordNet hierarchy, which is a large lexical database of English. Each meaningful concept in WordNet, including multiple words or word phrases, is called a ‘synonym set’ or ‘synset.’ WordNet contains more than a 100,000 synsets, with the majority of them being nouns.
ImageNet provides an average 1000 images to illustrate each synset. What makes ImageNet so special is that the images of each concept are quality-controlled and human-annotated, aiming to offer tens of millions of cleanly labeled and sorted images for most of the concepts in the WordNet hierarchy.
Li’s work on the project has led to one of the biggest breakthroughs in AI. Her contribution in the field “using learning methodologies based on statistical and neuroscience principles” was recognized by the International Association for Pattern Recognition in 2016.
Li & AI4ALL
In 2017, with funding from Melinda Gates and Jensen Huang, **Li cofounded AI4ALL** which is a national non-profit summer program aimed at **increasing diversion and inclusion in AI education**. According to AI4ALLs’s website “AI4ALL Opens Doors to Artificial Intelligence for Historically Excluded Talent Through Education and Mentorship.”
AI4ALL’s outreach includes girls, people of color and people from financially disadvantaged backgrounds. The first summer program took place on the Stanford campus and, by 2018, AI4ALL had successfully launched 5 more summer programs including at Princeton University, Carnegie Mellon University, Boston University, University of California Berkeley, and Canada’s Simon Fraser University. Today, AI4ALL’s summer programs take place in 16 sites across the U.S.
Li Recalibrating the Field of AI
The field of AI is growing exponentially and, while Li is one of its pioneers, she is also aware of its drawbacks and potential risks if not used wisely. Without proper guidance, she argues, AI technology will widen the wealth divide even further and reinforce social biases, while also making technology even more exclusive.
Li argued her point on Capitol Hill in 2018 at a hearing of the US House Committee on Science, Space, and Technology, titled Artificial Intelligence—With Great Power Comes Great Responsibility. In her words: “If we make fundamental changes to how AI is engineered—**and who engineers it**—the technology will be a transformative force for good. If not, **we are leaving a lot of humanity out of the equation**.”
Introduction to danah boyd
**danah boyd** is a technology and social media scholar with particular focus on **social and cultural inequities** stemming from the relationship between technology and society. boyd, who decided to change her name to all lower case for personal and political reasons, has degrees from Brown University, MIT, and Berkeley.
boyd is the founder and president of **Data & Society**, a research institute based in New York whose aim is to address the **ethical and legal implications of emerging technologies**. Her recognitions include the Electronic Frontier Foundation’s Pioneer/Barlow Award and the Young Global Leader of the World Economic Forum in 2011.
boyd is also a Partner Researcher at Microsoft and Distinguished Visiting Professor at Georgetown University.
boyd’s Early life
boyd was born in 1977 in Pennsylvania, U.S.A. She grew up in Lancaster, Pennsylvania, and attended Manheim Township High School from 1992-1996. While she excelled academically and was active in many extra-curricular activities, including theater and Model UN, she had a difficult time blending in and wasn’t active socially.
boyd had little interest in computers but found them to be a useful escape from school life. She spent a lot of time **creating content, browsing, and conversing with strangers** and was fascinated by the connections she was making.
boyd attributes her survival in high school to her mother’s support, the internet, which opened a door of possibilities, and her determination to succeed.
Her childhood dream was to go to the Naval Academy and become an astronaut, but an accident to her neck when she was 16 put an end to that dream and forced her to switch career paths.
From Mattas to boyd
**boyd’s name is integral to her identity**. She was born ‘Danah Michele Mattas,’ her mother adding the ‘h’ at the end of her first name because she liked how balanced it looked. When she was young, boyd added her stepfather’s name to her own, making it ‘Danah Michele Mattas Beard.’
Following her mother and stepfather’s divorce, boyd decided to take her maternal grandfather’s surname ‘Boyd’ because she felt it represented her **family, culture, and heritage**.
In 2000, **she legally changed her name** to what she felt fit: ‘danah michele boyd.’ boyd chose to stylize her name in **all lower case** for several reasons. On a personal level, she felt that ‘danah’ is more balanced and elegant, while politically she always questioned the reason why names should be capitalized and follow a certain style.
As she puts it: “it’s my name and i should be able to frame it as i see fit, as my adjective, not someone else’s. Why must it follow some New York Times standard guide for naming?” It is worth noting that, as seen in her quote above, boyd also doesn’t capitalize the pronoun ‘i’ as she thinks it’s quite “self-righteous.”
boyd’s Education
After graduating from high school, boyd attended Brown University for her bachelor’s degree where she studied computer science. She then obtained a master’s in Media Arts and Sciences from MIT, with her thesis focusing on “how people manage their presentation of self in relation to social contextual information in online environments.”
In 2008, boyd earned her PhD at the University of California Berkeley School of Information. Her dissertation titled Taken Out of Context: American Teen Sociality in Networked Publics focused on American teenagers and their use of social networking sites at the time, including Facebook and MySpace.
boyd's Career
While boyd was at Berkeley for her PhD, she participated in a 3-year ethnographic project examining the use of technology by youths, which was funded by the MacArthur Foundation, and wrote several articles on youth identity and the implications of social networking.
Over the years, she has written many papers examining **media manipulation, algorithmic fairness, social media, privacy, teen drama/bullying**, and other related topics.
In 2014, boyd published her groundbreaking book titled _It’s Complicated: The Social Lives of Networked Teens_, documenting her findings on how young people use social media as part of their daily practices. The book propelled boyd to the forefront of her field, and she has since been recognized as an authority on the intersection of technology and society.
In 2013, boyd founded **Data & Society**, a research institute that examines sociotechnical vulnerabilities in an effort to remedy structural inequities. At Data & Society, boyd and her team are working on topics such as fairness and accountability in **machine learning, combating bias in data,** and the **cultural dynamics surrounding artificial intelligence**.
