Coming soon · Book Profile
The Worlds I See Curiosity, Exploration, Discorvery at Dawn of Ai
A pioneering AI scientist recounts her improbable journey as an immigrant from China to the forefront of the AI revolution, revealing the human story behind the technology and advocating for a future where artificial intelligence is developed to augment human dignity.
A profile of this book is on the way.
What it’s about
“The Worlds I See” is the memoir of Dr. Fei-Fei Li, a leading figure in the field of Artificial Intelligence. It traces her path from a middle-class childhood in China to a life of struggle and discovery as a teenage immigrant in America, where her passion for science led her to the vanguard of the AI revolution. The book provides an insider's account of the breakthrough creation of ImageNet, a massive visual database that became a catalyst for the modern era of deep learning. More than just a history of a technology, this is a deeply personal story of perseverance, curiosity, and the crucial role of humanity in science. Dr. Li argues that as AI becomes an ever-more-powerful force, its development must be guided not by algorithms alone, but by a profound commitment to human values, ethics, and diversity, a vision she calls “human-centered AI.”
The through-line
- Who it’s for
- The reader is a curious individual—a student, technologist, leader, or concerned citizen—who is fascinated by the rise of Artificial Intelligence but feels anxious about its complexity, its potential negative impacts, and the impersonal narrative surrounding it. They want to understand AI on a deeper, more human level and find a hopeful path forward for the technology.
- The problem
- AI is an opaque and rapidly advancing field, making it difficult to grasp its true nature, its history, and its profound implications for society. The reader feels intimidated, anxious, or even fearful about AI, worrying that it is a dehumanizing force controlled by a select few and driven by motives that neglect human well-being.
- The plan
- Understand the human story of AI's evolution through the author's personal and professional journey.
- Learn the pivotal role of vision and large-scale, human-centric data in the modern AI revolution.
- Embrace the principles of Human-Centered AI to guide the future development and application of the technology responsibly.
- The payoff
- The reader gains a profound and nuanced understanding of AI, seeing beyond the hype and headlines. · They feel empowered and optimistic about the future, equipped with principles to guide the development of AI for the betterment of society. · They discover how they can contribute to a future where AI respects and enhances human dignity in all its forms.
See our guide
Additional reading
- Perceptrons · Marvin Minsky and Seymour Papert
This 1969 book's mathematical proof of the limitations of early neural networks is credited with launching the first 'AI winter,' making it a crucial historical text that the modern deep learning movement had to overcome.
- The Organization of Behavior · Donald Hebb
Published in 1949, this book introduced the theory of Hebbian learning ('neurons that fire together, wire together'), which provided a core biological inspiration for Geoff Hinton and the entire connectionist approach to AI.
- On Intelligence · Jeff Hawkins
This book's thesis that the brain's neocortex operates on a single master algorithm directly inspired Andrew Ng and shaped his successful pitch to Larry Page to create the Google Brain lab.
- Superintelligence: Paths, Dangers, Strategies · Nick Bostrom
This philosophical book, heavily promoted by Elon Musk, framed the debate around the potential existential risks of AGI and became a foundational text for the AI safety movement and organizations like OpenAI.
- Gödel, Escher, Bach: An Eternal Golden Braid · Douglas Hofstadter
It exposed the author to the idea that the mind could be understood in discrete, mathematical terms and introduced her to the philosophical implications of computation.
- The Emperor's New Mind · Roger Penrose
Along with Hofstadter's book, it challenged the author with its rich connections between different fields and its rigorous, scientific approach to understanding intelligence and the mind.
- What Is Life? · Erwin Schrödinger
This book by a famous physicist turning his attention to biology sparked the author's shift from physics toward the life sciences and the mystery of the mind.
- WordNet · George Armitage Miller (and team)
This lexical database project provided the author with the conceptual map and ontology that became the structural foundation for ImageNet, revealing a path to organizing the visual world at a massive scale.
- Superintelligence · Nick Bostrom
The book's exploration of AI's future became a mainstream success and a topic of discussion in the author's 'AI Salon,' highlighting the growing societal and philosophical questions surrounding the field.
- Clinical Versus Statistical Prediction · Paul Meehl
A foundational 1954 book that demonstrated through numerous studies that simple statistical formulas consistently outperform the intuitive judgments of human experts, providing an early rationale for algorithmic decision-making.