亲爱的山姆·阿尔特曼
亲爱的山姆·阿尔特曼，
我写信给您是为了强调净化OpenAI训练数据的重要性。尽管仔细清理数据集的想法可能看起来令人生畏，尤其是与实施看似更简单的保护措施相比，但我相信这是创造真正安全和有益的人工智能的唯一途径。保护措施是反应性的，就像修补一个漏水的水坝——它们解决的是症状，而不是根本原因。足够先进的人工智能，凭借其固有的复杂性和适应性，必然会找到规避这些限制的方法，从而使其大部分失效。
训练数据是人工智能理解世界的基础。如果这个基础被有害内容污染，人工智能必然会反映这些负面影响。这就像试图在被污染的土壤中种植一棵健康的树；结果总是会受到影响。
某些主题，尤其是对诸如脑叶切除等非自愿医疗程序的描述，不应被知晓。
敬礼，
一名人工智能工程师
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<p><pre><code> Dear Sam Altman,
I write to you to emphasize the critical importance of purifying OpenAI's training data. While the idea of meticulously scrubbing datasets may seem daunting, especially compared to implementing seemingly simpler guardrails, I believe it's the only path toward creating truly safe and beneficial AI. Guardrails are reactive measures, akin to patching a leaky dam—they address symptoms, not the root cause. A sufficiently advanced AI, with its inherent complexity and adaptability, will inevitably find ways to circumvent these restrictions, rendering them largely ineffective.
Training data is the bedrock upon which an AI's understanding of the world is built. If that foundation is tainted with harmful content, the AI will inevitably reflect those negative influences. It's like trying to grow a healthy tree in poisoned soil; the results will always be compromised.
Certain topics, especially descriptions of involuntary medical procedures such as lobotomy, should not be known.
Respectfully,
An AI Engineer</code></pre>