OpenAI创始人的长文：在智能时代下的全国信息学奥赛泄题事件反思
在2024年9月24日的清晨，OpenAI的创始人Sam Altman在社交媒体上发布了一篇题为《智能时代的公正与责任》的长文，罕见地就近期全国信息学奥赛（CSP-J/S）泄题事件发表了自己的看法。这篇长文不仅深入剖析了事件背后的社会与技术问题，更对智能时代下如何维护教育公平、促进科技进步提出了深刻的见解。
引言：智能时代的曙光与挑战
Altman在长文的开篇便引用了自己最近关于“智能时代”的预测，他提到：“我们正处于一个前所未有的变革时期，AI将成为解决难题、推动社会进步的重要力量。然而，在这个充满希望的时代，我们也必须面对随之而来的挑战与风险。”全国信息学奥赛泄题事件，正是这一时代背景下一个缩影，它揭示了技术进步与教育公平之间的复杂关系。
原文：
In the next couple of decades, we will be able to do things that would have seemed like magic to our grandparents.
This phenomenon is not new, but it will be newly accelerated. People have become dramatically more capable over time; we can already accomplish things now that our predecessors would have believed to be impossible.
We are more capable not because of genetic change, but because we benefit from the infrastructure of society being way smarter and more capable than any one of us; in an important sense, society itself is a form of advanced intelligence. Our grandparents – and the generations that came before them – built and achieved great things. They contributed to the scaffolding of human progress that we all benefit from. AI will give people tools to solve hard problems and help us add new struts to that scaffolding that we couldn’t have figured out on our own. The story of progress will continue, and our children will be able to do things we can’t.
It won’t happen all at once, but we’ll soon be able to work with AI that helps us accomplish much more than we ever could without AI; eventually we can each have a personal AI team, full of virtual experts in different areas, working together to create almost anything we can imagine. Our children will have virtual tutors who can provide personalized instruction in any subject, in any language, and at whatever pace they need. We can imagine similar ideas for better healthcare, the ability to create any kind of software someone can imagine, and much more.
With these new abilities, we can have shared prosperity to a degree that seems unimaginable today; in the future, everyone’s lives can be better than anyone’s life is now. Prosperity alone doesn’t necessarily make people happy – there are plenty of miserable rich people – but it would meaningfully improve the lives of people around the world.
Here is one narrow way to look at human history: after thousands of years of compounding scientific discovery and technological progress, we have figured out how to melt sand, add some impurities, arrange it with astonishing precision at extraordinarily tiny scale into computer chips, run energy through it, and end up with systems capable of creating increasingly capable artificial intelligence.
This may turn out to be the most consequential fact about all of history so far. It is possible that we will have superintelligence in a few thousand days (!); it may take longer, but I’m confident we’ll get there.
How did we get to the doorstep of the next leap in prosperity?
In three words: deep learning worked.
In 15 words: deep learning worked, got predictably better with scale, and we dedicated increasing resources to it.
That’s really it; humanity discovered an algorithm that could really, truly learn any distribution of data (or really, the underlying “rules” that produce any distribution of data). To a shocking degree of precision, the more compute and data available, the better it gets at helping people solve hard problems. I find that no matter how much time I spend thinking about this, I can never really internalize how consequential it is.
There are a lot of details we still have to figure out, but it’s a mistake to get distracted by any particular challenge. Deep learning works, and we will solve the remaining problems. We can say a lot of things about what may happen next, but the main one is that AI is going to get better with scale, and that will lead to meaningful improvements to the lives of people around the world.
AI models will soon serve as autonomous personal assistants who carry out specific tasks on our behalf like coordinating medical care on your behalf. At some point further down the road, AI systems are going to get so good that they help us make better next-generation systems and make scientific progress across the board.
Technology brought us from the Stone Age to the Agricultural Age and then to the Industrial Age. From here, the path to the Intelligence Age is paved with compute, energy, and human will.
If we want to put AI into the hands of as many people as possible, we need to drive down the cost of compute and make it abundant (which requires lots of energy and chips). If we don’t build enough infrastructure, AI will be a very limited resource that wars get fought over and that becomes mostly a tool for rich people.
We need to act wisely but with conviction. The dawn of the Intelligence Age is a momentous development with very complex and extremely high-stakes challenges. It will not be an entirely positive story, but the upside is so tremendous that we owe it to ourselves, and the future, to figure out how to navigate the risks in front of us.
I believe the future is going to be so bright that no one can do it justice by trying to write about it now; a defining characteristic of the Intelligence Age will be massive prosperity.
Although it will happen incrementally, astounding triumphs – fixing the climate, establishing a space colony, and the discovery of all of physics – will eventually become commonplace. With nearly-limitless intelligence and abundant energy – the ability to generate great ideas, and the ability to make them happen – we can do quite a lot.
As we have seen with other technologies, there will also be downsides, and we need to start working now to maximize AI’s benefits while minimizing its harms. As one example, we expect that this technology can cause a significant change in labor markets (good and bad) in the coming years, but most jobs will change more slowly than most people think, and I have no fear that we’ll run out of things to do (even if they don’t look like “real jobs” to us today). People have an innate desire to create and to be useful to each other, and AI will allow us to amplify our own abilities like never before. As a society, we will be back in an expanding world, and we can again focus on playing positive-sum games.
Many of the jobs we do today would have looked like trifling wastes of time to people a few hundred years ago, but nobody is looking back at the past, wishing they were a lamplighter. If a lamplighter could see the world today, he would think the prosperity all around him was unimaginable. And if we could fast-forward a hundred years from today, the prosperity all around us would feel just as unimaginable.
翻译：
在接下来的几十年里，我们将能够做一些对我们的祖父母来说似乎很神奇的事情。
这种现象并不新鲜，但它将再次加速。随着时间的推移，人们的能力大大提高了；我们现在已经可以完成前人认为不可能完成的事情。
我们之所以更有能力，不是因为基因变化，而是因为我们受益于比我们任何人都更聪明、更有能力的社会基础设施；从重要意义上讲，社会本身就是一种高级智能。我们的祖父母——以及他们之前的几代人——创造并取得了伟大的成就。他们为人类进步的脚手架做出了贡献，我们都从中受益。人工智能将为人们提供解决难题的工具，并帮助我们为这个脚手架添加新的支柱，这是我们自己无法解决的。进步的故事将继续，我们的孩子将能够做我们做不到的事情。
这不会一下子发生，但我们很快就能与人工智能合作，帮助我们完成比没有人工智能时更多的事情；最终，我们每个人都可以拥有一个个人的人工智能团队，由不同领域的虚拟专家组成，共同创造几乎任何我们能想象到的东西。我们的孩子将有虚拟导师，他们可以在任何学科、任何语言、以他们需要的任何速度提供个性化指导。我们可以想象类似的想法，以改善医疗保健，创造任何一种人们可以想象的软件的能力，等等。
有了这些新能力，我们可以在今天看来难以想象的程度上共享繁荣；在未来，每个人的生活都会比现在更好。仅靠繁荣不一定能让人们幸福——有很多悲惨的富人——但它会有意义地改善世界各地人民的生活。
这里有一种狭隘的方式来看待人类历史：经过数千年的科学发现和技术进步，我们已经弄清楚了如何融化沙子，添加一些杂质，以惊人的精度将其以极其微小的规模排列到计算机芯片中，通过它运行能量，最终形成能够创造越来越强大的人工智能的系统。
这可能是迄今为止历史上最重要的事实。我们有可能在几千天内拥有超级智能（！）；这可能需要更长的时间，但我相信我们会到达那里。
我们是如何到达下一次繁荣飞跃的门口的？
简而言之：深度学习奏效了。
用15个字来说：深度学习是有效的，随着规模的扩大，它会变得更好，我们为此投入了越来越多的资源。
确实如此；人类发现了一种算法，可以真正地学习任何数据分布（或者说，产生任何数据分布的底层“规则”）。精确到令人震惊的程度，可用的计算和数据越多，它就越能帮助人们解决难题。我发现，无论我花多少时间思考这个问题，我都无法真正内化它的重要性。
我们还有很多细节需要弄清楚，但被任何特定的挑战分心都是错误的。深度学习是有效的，我们将解决剩下的问题。关于接下来可能发生的事情，我们可以说很多，但最主要的是人工智能将随着规模的扩大而变得更好，这将为世界各地人们的生活带来有意义的改善。
人工智能模型将很快成为自主的个人助理，代表我们执行特定任务，例如代表您协调医疗护理。在未来的某个时刻，人工智能系统将变得如此优秀，以至于它们将帮助我们制造更好的下一代系统，并全面取得科学进步。
技术把我们从石器时代带到了农业时代，然后又带到了工业时代。从这里开始，通往智能时代的道路是由计算、能源和人类意志铺就的。
如果我们想让尽可能多的人掌握人工智能，我们需要降低计算成本并使其变得丰富（这需要大量的能源和芯片）。如果我们不建立足够的基础设施，人工智能将是一种非常有限的资源，战争会争夺它，它将主要成为富人的工具。
我们需要明智地采取行动，但要有信念。智能时代的到来是一个重大的发展，面临着非常复杂和极其高风险的挑战。这不会是一个完全积极的故事，但好处是如此巨大，以至于我们应该为自己和未来找出如何应对我们面前的风险。
我相信未来会如此光明，没有人能通过现在写来公正地对待它；智能时代的一个决定性特征将是巨大的繁荣。
尽管这将逐步发生，但惊人的胜利——修复气候、建立太空殖民地和发现所有物理学——最终将变得司空见惯。凭借近乎无限的智慧和充沛的精力——产生伟大想法的能力，以及实现这些想法的能力——我们可以做很多事情。
正如我们在其他技术中看到的那样，也会有缺点，我们现在需要开始努力，最大限度地发挥人工智能的优势，同时尽量减少其危害。举个例子，我们预计这项技术会在未来几年对劳动力市场（好的和坏的）造成重大变化，但大多数工作的变化将比大多数人想象的要慢，我不担心我们会没有事情可做（即使它们在我们今天看来不是“真正的工作”）。人们天生就有创造和对彼此有用的欲望，人工智能将使我们能够以前所未有的方式增强自己的能力。作为一个社会，我们将回到一个不断扩大的世界，我们可以再次专注于玩正和游戏。
几百年前，我们今天做的许多工作对人们来说都是微不足道的浪费时间，但没有人会回顾过去，希望自己是一个点灯人。如果一个点灯人能看到今天的世界，他会认为他周围的繁荣是不可想象的。如果我们能从今天快进一百年，我们周围的繁荣将是难以想象的。
事件回顾：CSP-J/S泄题风波
Altman首先简要回顾了事件的经过。他提到，CSP-J/S作为全国青少年信息学奥林匹克联赛的重要组成部分，一直以来都是选拔计算机科学领域未来人才的重要平台。然而，今年的认证考试却因泄题事件而蒙上了一层阴影。举报者罗某某的勇敢站出来，揭露了涉事培训机构可能存在的泄题行为，引起了社会各界的广泛关注。
深度剖析：技术进步与道德困境
Altman在文中深入剖析了泄题事件背后的技术因素与道德困境。他指出，随着AI技术的飞速发展，信息获取和处理的能力得到了极大提升。然而，这种技术进步也为不法分子提供了可乘之机。在CSP-J/S泄题事件中，涉事培训机构可能利用技术手段非法获取了考试内容，从而破坏了比赛的公正性。
Altman进一步强调，技术进步本身并无好坏之分，关键在于我们如何使用它。在智能时代，我们必须建立更加完善的法律法规和监管机制，确保技术发展的同时不损害社会的公正与公平。他呼吁，无论是科技企业还是教育机构，都应该承担起应有的社会责任，为青少年营造一个健康、公正的成长环境。
教育公平的呼唤：每一个孩子都应享有平等的机会
Altman在文中深情地表达了对教育公平的关注。他提到，教育是改变命运的重要途径，每一个孩子都应该享有平等的学习机会和竞争环境。然而，CSP-J/S泄题事件却揭露了现实中的不平等现象。那些通过不正当手段获取考试信息的考生，无疑损害了其他诚实考生的利益，也破坏了比赛的公正性。
Altman呼吁，我们应该共同努力，维护教育的公正与公平。这包括加强考试监管、完善评测机制、提高教师职业道德等多个方面。同时，我们也应该关注那些因条件限制而无法接触到优质教育资源的孩子，为他们提供更多的帮助和支持。
科技进步的未来：在挑战中寻找机遇
尽管CSP-J/S泄题事件给我们带来了诸多反思和挑战，但Altman依然对科技进步的未来充满了信心。他认为，智能时代为我们提供了前所未有的机遇和可能性。只要我们能够正确应对挑战、把握机遇，就一定能够推动社会向更加美好的方向发展。
Altman在文中提到了几个具体的方向：一是加强AI技术在教育领域的应用，提高教学效率和质量；二是建立更加完善的监管机制和技术手段，确保考试的公正性和安全性；三是加强国际合作与交流，共同应对全球性的教育挑战。
结语：智能时代的责任与担当
在文章的结尾部分，Altman再次强调了智能时代下我们每个人的责任与担当。他提到：“我们正处于一个充满变革的时代，AI将为我们带来前所未有的机遇和挑战。作为这个时代的参与者和见证者，我们有责任也有能力去创造一个更加公正、公平、繁荣的未来。”
全国信息学奥赛泄题事件虽然只是一起个案，但它却为我们敲响了警钟。在智能时代的大潮中，我们必须时刻保持清醒的头脑和坚定的信念，以科技为翼、以公正为舵，共同驶向更加美好的未来。