Andrew Ng

Shaping the future of AI and preparing for the post-artificial general intelligence era is crucial for ensuring that AI benefits humanity. Collaborative efforts are essential to address ethical, safety, and societal impact challenges.

While third-party audits for major AI systems could enhance transparency and trust, the field is rapidly evolving. It's crucial to find a balance that encourages innovation while addressing potential risks, and the best approach may vary across different contexts.

While AI safety is incredibly important, I don't believe that dedicating a third of computational resources solely to it is the most efficient approach. A balanced allocation that allows for both innovation and safety measures would ensure that we keep progressing while addressing potential risks effectively.

I don't believe AI labs should automatically pause training based on indications from AI Safety Institutes. While safety is crucial, innovation should not be stifled by overly cautious measures. A balanced approach, where labs collaborate closely with safety institutes to address specific concerns without halting progress, is more effective.

While it's important to consider the impacts of AI on society, focusing too heavily on 'legacy humans' might slow innovation. Our priority should be on maximizing AI's potential to improve lives broadly, rather than accommodating all traditional perspectives.