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Published Dec 28, 2023

2023 in AI, with Nathan Benaich

Daniel Bashir and Nathan Benaich delve into the transformative power of generative AI across various sectors, examining its impact on productivity, protein engineering, and creative fields. They also discuss the challenges in AI benchmarking, the open vs. closed-source debate, and the complexities of global AI regulation, emphasizing the UK's balanced approach.
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  • Regulation

    The discussion on AI regulation highlights the varied approaches taken by different countries, with the UK and US being prominent players. emphasizes the importance of building state capacity to understand AI's complexities, as many government officials lack the necessary knowledge 1. He notes that the UK's strategy of empowering existing regulators, rather than creating new ones, is sensible, as it balances innovation with risk management 2.

    State capacity, I think, is super important. It's obviously challenging to do that because the people who know how this stuff works, generally, the ones who build it and the ones who build it, are kind of more motivated to ship products than they are to influence government policy.

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    This approach contrasts with the US, where skepticism about legislators' understanding of AI persists.

       

    Governance

    Global AI governance remains a complex challenge, with limited progress beyond high-level commitments. observes that while there is significant energy directed towards policy, achieving global alignment is complicated by diverse interests and approaches 3. The EU's recent AI Act exemplifies the varied regulatory landscapes, with different regions adopting unique strategies 1.

    It just feels like there's a lot of different cooks in the kitchen now. So getting alignment globally would be pretty complicated.

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    This divergence underscores the difficulty in establishing cohesive global standards.

       

    EU & UK

    The EU and UK have distinct approaches to AI regulation, focusing on empowering existing frameworks and setting standards. praises the UK's balanced strategy, which avoids creating new regulators and instead enhances current ones to manage AI risks effectively 2. The UK's agreements with AI companies like DeepMind aim to improve risk understanding and set benchmarks 4.

    The best they can do is set standards or try and set standards, try and set best practices and benchmarks, and then be open and collaborative with sharing that expertise.

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    This pragmatic approach contrasts with the EU's more legislative-driven methods.

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