Fei-Fei Li, pioneer in generative AI models, advocates for a human-centered approach to dealing with AI. She discusses the evolution of computer vision, the impact of generative AIs on society, concerns about bias and disinformation, and the potential sentience of AIs.
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question_answer ANECDOTE
Vision as Cornerstone of Intelligence
Fei-Fei Li describes vision as a cornerstone of intelligence, essential for animals' survival and evolution.
For humans, seeing is fundamental for learning, interaction, and socialization.
question_answer ANECDOTE
ImageNet's AI Revolution
Fei-Fei Li recounts the creation of ImageNet with millions of labeled images enabling AI to recognize thousands of object classes.
The dataset sparked a revolution in AI after AlexNet used it to drastically improve image recognition in 2012.
volunteer_activism ADVICE
Responsibility in AI Governance
Educate the public with nuanced, clear information about AI's risks including bias, disinformation, privacy, and job changes.
Developers, businesses, and governments must take responsibility for ethical AI creation, deployment, and governance.
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A year ago, the public launch of ChatGPT took the world by storm and it was followed by many more generative artificial intelligence tools, all with remarkable, human-like abilities. Fears over the existential risks posed by AI have dominated the global conversation around the technology ever since.
Fei-Fei Li, a pioneer that helped lay the groundwork that underpins modern generative AI models, takes a more nuanced approach. She’s pushing for a human-centred way of dealing with AI—treating it as a tool to help enhance—and not replace—humanity, while focussing on the pressing challenges of disinformation, bias and job disruption.
Fei-Fei Li is the founding co-director of Stanford University’s Institute for Human-Centred Artificial Intelligence. Fei-Fei and her research group created ImageNet, a huge database of images that enabled computers scientists to build algorithms that were able to see and recognise objects in the real world. That endeavour also introduced the world to deep learning, a type of machine learning that is fundamental part of how large-language and image-creation models work.
Host: Alok Jha, The Economist’s science and technology editor.
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