本文介绍了Wise AI Wednesdays项目，旨在分享AI安全领域的研究进展。作者分享了对Wise AI和智慧的看法，探讨了研究方向的转变、资金前景、领域建设的重要性、贡献方式的拓展以及理论与实践并行的必要性。文章还强调了主观研究的价值，并提出了探索、批评、修复的研究阶段，最后总结了点状叙述的价值。

💡研究方向的转变：最初的研究方向是“通过模仿学习的Wise AI顾问”，现在作者更倾向于“百花齐放”的研究方法，认为应该探索更多合理的研究路径，而不是执着于单一方法。

💰资金前景的改善：AI安全领域，特别是与Wise AI相关的项目，似乎更容易获得资金支持，例如Cosmos x FIRE Truth-seeking Round和AI for Human Reasoning Fellowship。这使得Wise AI项目的推进成为可能，尽管可能需要调整项目以符合资助方的兴趣。

🌱领域建设的重要性：作者将重心从直接研究转向研究与领域建设并重。这包括论证Wise AI的价值、探索影响理论以及确定高优先级的具体项目。

✍️贡献方式的拓展：通过AI安全营和与其他人的交流，作者对贡献方式有了更广泛的认识。现在他认为人们可以通过多种方式为该领域做出贡献，包括理论研究和实践探索。

🔬理论与实践并行的必要性：作者强调同时进行理论研究和实践的重要性。他认为，长时间停留在理论层面容易忽略实际挑战，这些挑战可能对项目成败至关重要。

🗣️主观研究的价值：作者认为，在领域早期，探索性的、主观的研究往往被低估。在早期阶段，广度比严谨性更重要，但随着领域的发展，这种平衡应该发生变化。

🔄研究阶段的探讨：作者提出了一个研究新领域的理想阶段模式，包括探索、批评、修复和持续迭代。在探索阶段，重点是开辟新的研究领域；在批评阶段，深入的批判对于识别潜在的致命缺陷至关重要；在修复阶段，尝试修复之前阶段暴露出的问题。

Published on May 29, 2025 7:13 AM GMT

I recently finished leading an AI Safety Camp project on Wise AI Advisors^[1] (my team included Chris Cooper, Matt Hampton, and Richard Kroon). Since we want to share our work in an orderly fashion, I’m launching Wise AI Wednesdays. Each Wednesday^[2], I (or one of my teammates) will be sharing a post, initially drawn from our AI Safety Camp outputs, but later including shifting to include future work and outputs summaries or commentary on related research. I’m hoping that a regular posting schedule will help cultivate Wise AI/Wise AI Advisors as a subfield of AI Safety.

This inaugural post provides an update on how my views on AI and wisdom have changed since I won 3rd prize in the Automation of Wisdom and Philosophy Competition. My views have evolved considerably since then, so I thought it was worth posting an update:

Broadening My Focus: I had originally labelled my research direction as Wise AI Advisors via Imitation Learning. While I still see this as a particularly promising approach, I’m now interested in Wise AI Advisors more broadly. Many different reasonable-sounding paths exist; it would be arrogant to believe I’ve found the One True Path without much more investigation. I’m now more inclined to follow a 'let a thousand flowers bloom' path.More Favourable Funding Landscape: There seems to be more desire to fund work adjacent to this space than I had anticipated. For example: Cosmos x FIRE Truth-seeking Round and Fellowship on AI for Human Reasoning. I initially thought significant effort would be needed to convince funders, but it now seems quite possible to secure funding for Wise AI projects, even though you might have to choose a project that intersects with a funder's interest level.Increased Emphasis on Field-Building: Consequently, my focus has shifted from solely direct research progress to a combination of research and field-building. While I'm still defining what this entails, activities like establishing the case for Wise AI, exploring theories of impact, and identifying concrete, high-priority projects seem important right now.Expanded View of Possible Contributions: My ideas about what kind of work might be useful have broadened significantly thanks to AI Safety Camp and conversations with others. I now see a much wider range of ways people can contribute (see my draft post with project proposals).Importance of Simultaneous Pursuit of Both Theory and Practice: I now believe it’s crucial to have people pursuing both theory and practice simultaneously and collaboratively. While it can be tempting to delay attempting to implement anything until all the theoretical building blocks are in place, if you spend all your time in ‘theoryland’, it’s extremely easy to overlook pragmatic challenges—challenges that could easily turn out to be make-or-break.Subjective Research as Underrated: I feel that exploratory, subjective research is often underrated—especially in the early stages of a field. Initial exploration needs a 'lay of the land', which traditional scientific research can struggle with because it’s hard to measure many bits^[3]. At first, bandwidth matters more than rigor—but the balance should shift as the field matures.Exploration vs Critique: I’ve recently been wondering whether research into a new sub-field is best accomplished with explicit phases (Obviously, past a certain point, such coordination might be impossible, but I’m discussing the ideal rather than pragmatics):
Phase 1: Exploration: Focus on opening up an area of exploration, with the role of critique mainly being about what to prioritise.Phase 2: Critique: Once reasonable proposals exist, in-depth criticism becomes vital to identify any potentially fatal flaws.Phase 3: Rebuilding/repair: Attempting to fix or patch any flaws exposed in the previous phase. Optimism is important in this phase to avoid prematurely ruling out potential fixes.Phase 4 and further: Continue alternating between critique and repair.
The Value of Dot Points: I wasn’t originally planning to continue writing up more bulleted lists, but I'm now much more willing to stand behind the value of this format in particular circumstances. They are useful as previews, help get information out quickly, and suit posts like this one that provide multiple quick updates rather than a single, in-depth topic.

Thanks for reading and see you next Wednesday!

1. ^{^}

   Originally Wise AI Advisors via Imitation Learning. As I say further down, I pivoted towards “let a thousand flowers bloom” rather than one particular approach.

2. ^{^}

   It is still Wednesday for US night owls.

3. ^{^}

   That said, it might be worthwhile doing some more objective research earlier on if the acquisition cost of knowledge is low enough or if you’re worried that once schools of thought form, people won’t update on empirical evidence.

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