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  • November 24, 2023
  • Shahala VP
Andrew Ng Commends India's Light-Touch Approach to AI Regulation

In the dynamic realm of artificial intelligence (AI), the imperative of regulation has become a focal point, sparking debates on finding the right equilibrium between oversight and fostering innovation. Andrew Ng, a British-American computer scientist, and technology entrepreneur has lauded India's approach to AI regulation, emphasizing the importance of striking the right balance.

While acknowledging the necessity of regulations in the AI landscape, Ng raised concerns about the potential stifling of innovation if an excess of regulations is poorly implemented. He highlighted the need for effective regulations and clarity on deploying AI in critical areas such as healthcare. Reflecting on the European Union's AI Act, Ng noted both thoughtful and flawed aspects, suggesting a tiered approach to AI risk mitigation, particularly in high-risk applications like job screening.

Expressing his limited familiarity with the Indian approach to regulation, Ng indicated a positive perception, stating, "My sense is that India is taking a very light touch. And I think India’s approach is good. In fact, most Asian nations have been regulating AI with a much lighter touch, which has been a good move."

During the interview, Ng also commented on the leadership of his former student and OpenAI CEO, Sam Altman, expressing praise for Altman's leadership while deeming the recent situation unfortunate. He mentioned the tragedy surrounding Altman's departure and criticized OpenAI's governance structure as being discredited.

Ng weighed in on the global AI landscape, noting that fewer Asian countries have succumbed to the hype surrounding AI extinction, primarily observed in Europe. Regarding the development of Artificial General Intelligence (AGI), Ng offered a perspective, estimating it to be decades away, contrary to some optimistic claims suggesting achievement within 3-5 years. He emphasized a cautious approach to AGI development, pointing out varying timelines and perspectives within the AI community.