This week, with all the sensational news of corporate upheaval and intrigue at OpenAI, the leading artificial intelligence (AI) company in the world, we’re all suddenly taking note of this strange new chapter in the history of human technological innovation. Indeed, ever since the release of ChatGPT last year, with its astounding capabilities to generate text and write software, it’s become an unavoidable new topic of conversation and thought, as we try to figure out what it portends for the future of work, society and even the human race itself.
It was in this context that I noticed and picked up a copy of The Worlds I See by Dr. Fei-Fei Li at my local library. I’m so glad I did, because it’s a truly excellent book, combining a poignant personal account of the author’s life as a young Chinese immigrant girl, along with her parents, as they try to build a better life in America, with an insider’s look at how the quest for AI has developed over the past two decades inside our major universities and corporations.
If you dive into the details of AI and its history in the various news stories now appearing almost daily in the media, you will quickly find not only Dr. Li’s name and story, but also those of many of the other influential players with whom she has worked and who she names and describes in her book, who are now leading the industry and its ongoing research and development.
Li’s most notable contribution to the field flowed from her decision as a young professor to try to build a huge database (called Image Net) holding digitized, labelled images of all the physical objects in our world. She succeeded, despite the seemingly overwhelming size of the project, and the discouragement of some older eminent scientists in the field, who saw it as both a hopeless and pointless undertaking. Her account of the process by which she led a small group of young scientists to overcome every obstacle in their way is a fascinating and inspiring story of scientists and engineers at work in our own era.
But her success in creating Image Net had unexpected consequences that accelerated the larger AI project. After sponsoring a contest to have other researchers use her database to train algorithms for computerized visual recognition of objects over several years, it suddenly turned out that neural networks – an AI architecture that had been tried in the past but had been in academic disfavor for several decades – proved to be massively more effective than more recent techniques, once it had been trained with a sufficiently large database.
From this major achievement, Dr. Li became one of the top experts in computer vision in the world. She was sought after as a scientist, researcher and teacher, and ended up moving from Princeton to Stanford, and then ultimately to a top position in AI at Google, where she found a very different culture than that of academia, with different priorities, and a far larger budget for her fast-growing research department.
At the same time she was leading this world-changing AI research, though, she was also living a human life we would all recognize. For example, her mother has suffered for many years with a chronic, life-threatening health condition, which led Dr. Li to think about new uses to which AI could and should be put in serving the needs of humanity.
As a result of her mother’s challenge to use her research to help others, she became involved in an effort to apply computer vision to problems of patient care in hospitals. But when she encountered unexpected resistance from those she thought she was helping (the nurses and medical staff), she was forced to begin considering more closely the negative side of the AI equation, and to think more deeply about the ethical and moral implications of her life’s work.
In the course of this life she recounts, she has also been a wife, a mother, a friend and mentor to many colleagues, and a loving daughter to both her parents, and she nicely weaves many of those important personal relationships and how they influenced her work into the larger story of her brilliant career.
So much of how we reached this technological moment, and what it portends for our futures, has taken place behind the closed doors of university laboratories and in corporate board rooms. This outstanding and compassionate personal account by a leading scientist in AI explains how we got here, what it felt like to be one of the key contributors in such a dramatic process of human discovery and innovation, and also how both the perils and potential rewards of this technology have come into sharper focus at each step forward. Very highly recommended.