本文探讨了理性主义项目在克服认知偏差方面面临的挑战，指出心理学研究的局限性以及偏差对个体适用性的问题。尽管如此，文章强调了理性主义在预测重要事件（如加密货币、新冠疫情和人工智能）上的准确性，并认为其在理解认知科学和统计学方面的优势不可忽视。作者提出通过在模拟情境中突出偏差的有害影响，来帮助人们学习和避免这些错误，并强调了“弄清楚并应用”的重要性。文章区分了这种方法与电子游戏和现实生活，认为现有的游戏在优化趣味性而非挑战性，且缺乏现实生活的反馈机制。最后，作者表达了对现有理性主义游戏的不足以及未来发展方向的思考，并鼓励他人参与相关实践。

💡 **理性主义项目的核心困境与价值**：理性主义项目旨在通过消除偏差来提升认知能力，但面临心理学研究的局限性以及偏差个体化适用性的难题。然而，理性主义在预测重大事件（如加密货币、新冠疫情、人工智能）方面展现了显著的准确性，并在理解认知科学和统计学方面拥有独特优势，这使其价值不容忽视。

🚀 **通过模拟情境克服偏差的策略**：文章提出了一种创新的方法，即在模拟环境中设置特定情境，使人们面临的偏差异常但合法地凸显出来。这种“情境化学习”有助于人们在不知晓具体错误类型和时机的情况下，更有效地学习和避免潜在的认知陷阱，从而获得“迁移学习”的机会。

🎮 **理性主义游戏与现实的差异**：与电子游戏不同，作者认为现有的游戏往往侧重于娱乐而非挑战，即使有挑战也并非旨在提升现实能力。同时，现实生活缺乏游戏提供的重复尝试、清晰规则和及时反馈，其高风险和长反馈周期也使得从错误中学习变得更为困难。因此，需要专门设计的“理性”游戏来弥补这些不足。

🤔 **对未来理性主义实践的展望**：作者承认目前缺乏具体的理性主义游戏实践，并表达了对现有“D&D.Sci”等模式的局限性（如过度依赖数据科学技能、缺乏情感投入、时间投入大）的担忧。尽管如此，作者仍鼓励社区成员积极探索和开发能够有效训练认知技能的游戏和方法，并愿意提供支持。

Published on November 3, 2025 4:10 PM GMT

Introduction

Basis: The rationalist project was built on the idea of overcoming bias, using the last half-century of psych findings to eliminate errors and thereby become stronger.Problem: The psych literature is wrong (mostly, probably, plausibly; we don't even know).Problem: Even when it's right, it might not apply to an individual: maybe people in general are overconfident, but that doesn't mean you specifically are on the specific topic in question.Problem: Some biases are subtly loadbearing, or cancel out other biases.But: We do keep getting important things right, especially purely-epistemically^[1]. We called crypto, called covid, and called AI. (If I'd made investment decisions over the last decade based solely on What LW Is On About This Month, I'd be retired by now.)Also: We're one of the few spaces which have even started to process the massive holes in the psych literature, or who collectively grok statistics well enough to understand where they went wrong.And: The study of what minds can do seems easier than the study of what minds will do. Test subjects, incentivized appropriately, will consistently try their best; we can then study what conditions improve their best.So: I don't think we get to give up.

My proposed approach

Put people in synthetic situations where the problems you're warning people against are anomalously but legitimately salient.

Notes:

Errors are best addressed en masse. If you deliver a 30 minute class about avoiding the sunk cost fallacy, they will - if you're lucky - learn to avoid the sunk cost fallacy in the context of a 30 minute class about avoiding the sunk cost fallacy. If they don't know in advance which errors will hurt them or how, and it's not immediately obvious from the shape of the challenge, that should give Transfer Learning a fighting chance.You should account for the possibility that people are making the opposite mistake. It makes sense to tilt the experience so it's about the more common flaw, but if someone is chronically underconfident or changes tack too readily, they shouldn't be rewarded for that. (Maintaining some level of agnosticism here also reduces dependency on the psych literature.)"Figure this out" is good. "Figure this out and then use it" is better. (c.f. natural/compound weightlifts vs weightlifting on machines)

Isn't this just videogames? Or games in general?

No. It should be. But it isn't.

Games:

Are usually optimized for fun, not challenge.
Are, when optimized for challenge, usually optimized for challenge-for-the-sake-of-challenge, not challenge-for-the-sake-of-getting-stronger-outside-the-game.
Are usually not primarily about strategy.
Are, when strategic, usually too easy to teach the average asp-rat anything.
Are, when strategic and difficult, usually dependent on massive time commitments.
(. . . like only getting to lift heavy weights with high numbers of reps; like having your only choices being light jogs or gruelling marathons, and never getting to sprint.)
Are usually not about Inference.
Are, when about Inference, usually center maximally-fuzzy vibes and/or maximally-sterile logic; few intermediate contexts where e.g. Bayes is appropriate.
Will actively lie to you about probability in particular. (XCOM:EU is the one modern-ish mainstream-ish hard strategic uncertainty-involving title I'm aware of where the probabilities shown onscreen are the actual probabilities; everything else including the sequel systematically lies to the player to accommodate their limitations and mitigate their frustrations.^[2])Require genre familiarity (to an extent you're probably ignoring if you have genre familiarity).

Isn't this just life?

Nope.

Life:

Doesn't give you multiple tries^[3].Doesn't show all its rules at the end so you know where you went wrong^[3].Has long feedback loops.Presents important decisions infrequently and suddenly.Has high stakes which complicate learning from big mistakes: it's hard to admit you screwed up something important, and trauma can make you over-correct^[4].Has all the easy and fundamental inferential problems already solved; you need to spend at least two decades studying things other people figured out before you have a chance to discover something novel and important and timeless, which will be your first chance to use or develop your discover-something-novel-and-important-and-timeless skills.Is notoriously unfair and arbitrary^[3].

. . . Is this a "please make and/or play more D&D.Sci scenarios you guys" post?

I wish!

Despite its merits, my genre:

Hard-requires and focuses-on data science skills; rationality skills are secondary. (People who don't know their way around a command line or a spreadsheet are at best stuck spectating.)Doesn't emotionally involve players, except in a "sure hope I'm right!", "argh I don't understand!", or a "wonder what the gimmick is this time?" sense; no chance to practice managing or channeling Feels during problem-solving.Requires a (honestly, probably excessively) significant investment of time and effort.Hard-requires and focuses-on data science skills; rationality skills are secondary. (I know I said this before but it's a significant enough limit that imo it's worth repeating.)

So what's the plan?

Well, in the immediate term, my plan . . .

. . . is to make this post, and then hope someone else follows up on it.

I do have some ideas for rationalish/inferencey games^[5], but I'm starting a demanding new dayjob next week and I expect that to be my priority for the foreseeable; realistically you're not going to get anything solid from me until the middle of next year at the earliest. So if anyone wants a headstart on me, they're warmly encouraged to begin building now^[6].

(Also, if anyone knows about already-existing rationality games I might have missed, I look forward to seeing them in the comments.)

1. ^{^}

   Conversely, most of our failures seem to happen at the "And What Should We Do About That?" step.

2. ^{^}

   I reserve a special place in hell for Fire Emblem's numerical clownery.

3. ^{^}

   NB: this claim is contested.

4. ^{^}

   These aren't mutually exclusive; people can be in denial about what they actually got wrong, and then over-correct for something else.

5. ^{^}

   This is actually an understatement on par with "Mt. Everest is somewhat taller than the average house".

6. ^{^}

   . . . and to DM me for support playtesting: I'm told I give helpful feedback!

Discuss