Three important steps in my maturation process

我成长过程中的三个重要步骤

My father passed recently, and he was twice my age. I am approximately the same age that he was when I was born, and I am now “the old generation” - there’s no one left in the generation above me. At the same time, I recently joined a company that skews younger-than-me. When I joined Google in 2011, I had just turned 30, and was in the mainstream demographics of Google in 2011. There were a bunch of more senior folks, with the very senior ones being in their 50s and having completed stints at Bell Labs. I admired a lot of these “greybeards” (even though this is a sexist term - what’s the right female equivalent? There were a few very senior female engineers that I would love to include). So perhaps it is natural that I am reflecting on “what were the important realizations that I made since my early 20s that had a profound impact on the way I think about the world”? In some sense: What are the insights I had that made me “more mature”, for some positive definition of “mature”? This post tries to list them.

我父亲最近去世了，他去世时的年龄正好是我现在的两倍。我现在的年龄大约和我出生时他当时的年龄相当，我成了“老一辈”——我上面那一代人已经不在了。与此同时，我最近加入了一家员工普遍比我年轻的公司。2011 年我加入谷歌时刚满 30 岁，处于当时谷歌员工的主流年龄段。那时有很多资深人士，最年长的在 50 多岁，曾在贝尔实验室工作过。我很钦佩这些“老白男”（尽管这是一个性别歧视的词汇——女性的对应词是什么？当时也有几位非常资深的女性工程师，我很想把她们也包括进去）。因此，我反思“自 20 岁出头以来，有哪些重要的感悟深刻影响了我看待世界的方式”，这或许是很自然的。从某种意义上说：有哪些见解让我变得“更成熟”了（取“成熟”的正面定义）？这篇文章试图列出这些感悟。

1. The importance of understanding your own incentive structure, and not believing everything you think. I recently wrote a Twitter thread about the topic. Oppenheimer was very publicly guilt-ridden about the creation of the nuclear bomb, and von Neumann at some point quipped “some people profess guilt to claim credit for sin”. In my young years, particularly in situations when I had 0day that nobody else had, I agonized about the responsibility that comes with having 0day. Should I fix them? Should I use them for good? Will the world be harmed this way? Or that way? In the end, it turns out that - while individuals matter - many ideas have a “time at which they are ripe”, and the actions of the individual matter less than the individual thinks in that moment. There is also almost no way to predict the ways in which what you do impacts the broader world. If you were asked: “Would it be good if this 0day was used to apprehend a terrorist?” you would probably say “this is good”. If you were asked “would it be good if this 0day is used to arrest someone and then torture and waterboard him 183 times?”, you would probably say “this is bad”. So if your 0day was used to capture KSM, it is probably good? Or bad? Things get very complicated very quickly. Is closing 0days good for society, because it makes everything safer? Or is it enabling oppression, because buggy systems are easier to bypass? There are no good answers, and your own incentive structure will greatly influence how you choose your beliefs. In the end, people want to be the heroes of their own story, and at the same time they have basal needs for recognition, for material goods, etc. - so they will try to construct a narrative that allows them to satisfy their basal needs while also remaining the hero of their saga. Anxiety about the impact of your work is self-flattering, and you have to recognize it as such, and keep it in check - it’s sugar for your ego, but history will largely route around you, because while individual decisions matter in specific situations, the overall flow of history is less sensitive to the individual than the individual thinks. The broader lesson, though, is: Do not believe everything you think. Examine your own incentive structures carefully. Ask yourself what alternative narratives for your behavior and beliefs could be, especially if they contradict the narrative of the heroic saga you’re constructing for yourself. Carefully weighing the question “how might I be the villain in this story?” is an important and valuable skill. Similarly, meta-cognition - just observing your own thoughts in a detached manner, and then being able to interpret, analyze, and contextualize them with regards to your own incentive structures, is a great skill to cultivate.

2. 理解自身激励机制的重要性，以及不要相信你所想的一切。我最近在 Twitter 上写了一个关于这个话题的帖子。奥本海默曾公开对制造原子弹感到内疚，而冯·诺依曼曾打趣道：“有些人宣称内疚是为了通过罪恶来博取名声。”在我年轻的时候，特别是在我掌握了别人没有的 0day（零日漏洞）时，我曾为拥有这种漏洞所带来的责任而苦恼。我应该修复它们吗？我应该把它们用于善事吗？世界会因此受到伤害吗？最终结果证明，虽然个人很重要，但许多想法都有其“成熟的时机”，个人的行为并没有他当时想象的那么重要。此外，几乎无法预测你的行为会如何影响更广阔的世界。如果有人问你：“如果这个 0day 被用来抓捕恐怖分子，是好事吗？”你可能会说“这是好事”。如果问你：“如果这个 0day 被用来逮捕某人，然后对他进行 183 次水刑折磨，是好事吗？”你可能会说“这是坏事”。那么，如果你的 0day 被用来抓捕哈立德·谢赫·穆罕默德（KSM），它是好事还是坏事？事情很快就会变得非常复杂。修复 0day 对社会有益吗，因为它让一切变得更安全？还是说它助长了压迫，因为有漏洞的系统更容易被绕过？这些都没有标准答案，你自己的激励机制将极大地影响你如何选择自己的信仰。归根结底，人们希望成为自己故事里的英雄，同时他们又有对认可、物质财富等的基本需求——所以他们会试图构建一种叙事，既能满足基本需求，又能让自己保持英雄形象。对工作影响的焦虑是一种自我吹捧，你必须意识到这一点并加以控制——这对你的自尊心来说是糖衣炮弹，但历史大体上会绕过你，因为虽然个人决策在特定情况下很重要，但历史的整体走向对个人的敏感度远低于个人所想。更广泛的教训是：不要相信你所想的一切。仔细审视你自己的激励机制。问问自己，对于你的行为和信仰，是否存在其他的叙事方式，特别是当这些叙事与你为自己构建的英雄史诗相矛盾时。仔细权衡“我怎么可能是这个故事里的反派？”这个问题是一项重要且有价值的技能。同样，元认知——以超然的方式观察自己的想法，然后能够根据自己的激励机制来解释、分析和情境化这些想法，是一项值得培养的伟大技能。

3. Monocausal determinism is an illusion, and largely does not exist outside of computer debugging. The monocausal determinism that young computer enthusiasts get used to is an illusion that generations of electrical and process engineers spent their lives perfecting and maintaining. It is because of these engineers that computer scientists could largely get away without probabilities or any empirical grounding in the past. There is an argument that you have so many natural scientists that crossed over into AI because CS education was for a long time too focused on reasoning within the deterministic monocausal illusion. The reality is: Computing machines are physical devices, which includes wear & tear, differences in quality between items, and “probabilistically deterministic behavior”, e.g. it’ll appear deterministic most of the time if not shaken too much. If pushed a bit - be it temperature, voltage, electromagnetic fields, or even rapid memory accesses to adjacent DRAM rows - determinism has a tendency to go out of the window, the illusion collapses, and we’re dealing with a very different beast. FWIW - this also makes me wonder about model alignment, because even a perfectly aligned model will be subject to random bit flips in inference, and it’s hard for me to imagine that you can maintain any reasonable guarantees in the presence of bit flips to inopportune values at inopportune times. The real world is one where very few things that happen have a single reason, and very few truly deterministic transmission mechanisms. Everything is probabilistic, and everything is multicausal. Measurement noise is real, experiment design is difficult. Interestingly, if you think about this carefully, you also realize that the scientific method is a classifier that is intentionally biased against accepting something as true - so that we only accept things as true that are beyond any reasonable doubt true. A somewhat fascinating corollary of this is that there exists a large class of true things that will never be scientifically shown as true.

4. 单因决定论是一种错觉，除了在计算机调试之外，它在很大程度上并不存在。年轻的计算机爱好者所习惯的单因决定论，是几代电气和工艺工程师耗尽一生去完善和维护的一种错觉。正是因为这些工程师的存在，计算机科学家在过去很大程度上可以不必考虑概率或任何经验基础。有一种观点认为，之所以有这么多自然科学家转向人工智能领域，是因为计算机科学教育长期以来过于专注于在决定论的单因错觉内进行推理。现实情况是：计算机器是物理设备，这意味着它们存在磨损、个体质量差异以及“概率性决定行为”，例如，如果不受到太大干扰，它在大多数时候看起来是决定性的。如果稍微施加压力——无论是温度、电压、电磁场，还是对相邻 DRAM 行的快速内存访问——决定论往往就会消失，错觉随之破灭，我们面对的将是一个完全不同的怪物。顺便提一下，这也让我对模型对齐产生了怀疑，因为即使是一个完美对齐的模型，在推理过程中也会受到随机位翻转的影响，我很难想象在位翻转到不合时宜的值、发生在不合时宜的时间的情况下，你还能维持任何合理的保证。现实世界中，很少有事情只有一个原因，也很少有真正决定性的传输机制。一切都是概率性的，一切都是多因的。测量噪声是真实存在的，实验设计是困难的。有趣的是，如果你仔细思考这一点，你也会意识到科学方法是一个有意偏向于不接受某事为真的分类器——这样我们只接受那些毫无疑问为真的事物。由此得出的一个相当迷人的推论是：存在一大类真实的事物，它们永远无法被科学地证明为真。

5. The dichotomy between reason and emotion is a cultural construct, and neither grounded in neuroscience nor in logic.

6. 理性与感性之间的二分法是一种文化建构，既没有神经科学依据，也没有逻辑依据。