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Geoffrey Hinton And Fei-Fei Li Call Thousands To Discuss Responsible AI Development


AI pioneers Geoffrey Hinton and Fei-Fei Li, whose research ignited the “Big Bang” of artificial intelligence more than ten years ago, are attempting to address a new issue: how to safely and responsibly develop the revolutionary technology.

The “godfather of AI,” Hinton, a University Professor Emeritus at the University of Toronto, has spent the last six months raising awareness of the existential threat posed by the rapid development of large language models like ChatGPT and Google’s PaLM, let alone shorter-term dangers like unemployment, fake news, and “battle robots.”

Li, a professor at Stanford University and the institute’s co-director, acknowledges that there are significant risks associated with AI and stresses the importance of making investments in public institutions to help shape the technology’s future. She has optimism about the future nonetheless.

“If we do the right thing, we have a chance – we have a fighting chance of creating a future that’s better,” said Li at a recent event with Hinton that was hosted by U of T at the MaRS Discovery District and livestreamed to thousands of people online.

“So, what I really feel is not delusional optimism at this point – it’s actually a sense of urgency of responsibility.”

The Hinton-Li talk, which served to launch the Radical AI Founders Masterclass, a four-week program designed to teach AI researchers how to build AI companies, was organized by Toronto venture capital firm Radical Ventures in collaboration with U of T, Stanford, the Vector Institute, and other organizations.

“It’s already clear that artificial intelligence and machine learning are driving innovation and value creation across the economy. They are also transforming research in fields such as drug discovery, medical diagnostics and the search for advanced materials,” U of T President Meric Gertler said during his introductory remarks. “Of course, at the same time, there are growing concerns about the role AI will play in shaping humanity’s future – so today’s conversation certainly addresses a timely and important topic.”

Li and Hinton described how, in 2012, Hinton’s graduate students used the ImageNet database created by Li and her colleagues to test object recognition software to show the power of deep learning neural networks. Jordan Jacobs, the discussion’s facilitator and a co-founder of Radical Ventures and the Vector Institute, referred to it as AI’s “Big Bang moment.”

Hinton remarked that his warning is being heard, despite his continued concern over the ability of today’s AI systems to ingest vast amounts of data and instantaneously exchange their learnings with one another, a quality he claims could one day result in greater intellect.

“I’m quite optimistic that people are listening,” he said.

The extensive debate sparked a swarm of inquiries from both the live audience and the online audience, including both students and entrepreneurs who were keen to implement responsible AI development at their firms.

The conversation was described as “profound” and “unparalleled” in Melanie Woodin’s final statements as dean of the Faculty of Arts & Science at the University of Toronto.

Hinton’s call for greater study on reducing the risks of artificial intelligence (AI) resonated with the students in the room, according to Steve Engels, a professor teaching stream at the U of T’s department of computer science, who was present at a watch party.

“It’s nice when they get to see some of the people who are working on the technology also call people to action in order to try to respond to it,” he said. “There isn’t opposition between the people making the technology and the people who are trying to regulate it and protect us from it.”

The discussion left Arielle Zhang, a third-year machine intelligence major at the University of Toronto’s Faculty of Applied Science & Engineering, feeling upbeat about the future and her place in it.

“The conversation was pretty inspiring,” she said, adding that it helped convince her to pursue a another degree in academia – a place where topics such as AI privacy and fairness can be more easily explored.

“Those are the issues the new generation is facing.”

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