Keeping humans at the center of AI
She’s a towering figure behind today’s AI boom but not everyone thought Fei-Fei Li was on the right track when she came up with a giant visual database called ImageNet.
Li, a founding director of Stanford University’s Institute for Human-Centered Artificial Intelligence, is out with a new memoir that recounts her pioneering work in curating the dataset that accelerated advances in computer vision.
The book, “The World I See,” also portrays a childhood that shifted from China to New Jersey and follows her rise through academia and Silicon Valley as AI commercialization brought attention and backlash.
You describe how you envisioned ImageNet as more than just data. Can you explain?
ImageNet is the quintessential story of identifying the North Star of an AI problem and finding a way to get there. One of the fundamental problems in visual intelligence is understanding, or seeing, objects because the world is made of objects. Human vision is grounded in our understanding of objects. There are many, many of them. ImageNet attempted to define the problem and provide a path to solve it — big data.
If I could travel back 15 years when you’re at work on ImageNet and told you about DALL-E, Google Gemini and ChatGPT — what would most surprise you?
What does not surprise me is that everything you mention is large-data based. They’re pretrained on a large amount of data. That’s exactly what I was hoping for. What surprised me is we got to generative AI faster than most of us thought. Generation for humans is actually not that easy. Most of us are not natural artists. We need the Van Goghs of the world.
What do you think most people want from intelligent machines and is that aligned with what scientists and tech companies are building?
I think fundamentally people want dignity and a good life. That’s almost the founding principle of our country. Machines and tech should be aligned with universal human values — dignity and a better life, including freedom and all of those things. Sometimes when we talk about tech or sometimes when we build tech, whether it’s intended or unintended, we don’t talk enough about that.
What are the biggest misconceptions about AI?
The biggest misconception of AI in journalism is when journalists use the subject AI and a verb and put humans in the object. Human agency is very important. We create technology, we deploy technology, and we govern technology. The media and the public discourse, but heavily influenced by media, is talking about AI without the proper respect to human agency.