大家好，我是中国注册会计师，硕士毕业，财务报告五步分析体系创始人致远。

2023年3月21日比尔.盖茨发表了《人工智能时代已经开始——人工智能就像手机和互联网一样具有革命性》公开信，本文做了一份中英版本。

In my lifetime, I’ve seen two demonstrations of technology that struck me as revolutionary.

在我的一生中，我看到过两次让我震惊的革命性的技术演示。

The first time was in 1980, when I was introduced to a graphical user interface—the forerunner of every modern operating system, including Windows. I sat with the person who had shown me the demo, a brilliant programmer named Charles Simonyi, and we immediately started brainstorming about all the things we could do with such a user-friendly approach to computing. Charles eventually joined Microsoft, Windows became the backbone of Microsoft, and the thinking we did after that demo helped set the company’s agenda for the next 15 years.

第一次是在1980年，当时我接触到了图形用户界面——包括Windows在内的所有现代操作系统的先驱。我和向我展示演示的人坐在一起，他是一个名叫Charles Simonyi的优秀程序员，我们立即开始头脑风暴，讨论用这种用户友好的计算方法我们能做什么。查尔斯最终加入了微软，Windows成为了微软的支柱，我们在演示之后所做的思考帮助确定了公司未来15年的议程。

The second big surprise came just last year. I’d been meeting with the team fromOpenAI since 2016 and was impressed by their steady progress. In mid-2022, I was so excited about their work that I gave them a challenge: train an artificial intelligence to pass an Advanced Placement biology exam. Make it capable of answering questions that it hasn’t been specifically trained for. (I picked AP Bio because the test is more than a simple regurgitation of scientific facts—it asks you to think critically about biology.) If you can do that, I said, then you’ll have made a true breakthrough.

第二大意外发生在去年。自2016年以来，我一直在与OpenAI的团队会面，他们稳步的进步给我留下了深刻的印象。在2022年年中，我对他们的工作感到非常兴奋，于是我给了他们一个挑战:训练一个人工智能通过一门生物预修课程考试。让它能够回答没有专门训练过的问题。(我选择AP生物是因为这个测试不仅仅是简单的科学事实的反刍——它要求你批判性地思考生物学。)我说，如果你能做到这一点，那你就取得了真正的突破。

I thought the challenge would keep them busy for two or three years. They finished it in just a few months.

我以为这个挑战会让他们忙上两三年。他们只用了几个月就完成了。

In September, when I met with them again, I watched in awe as they asked GPT, their AI model, 60 multiple-choice questions from the AP Bio exam—and it got 59 of them right. Then it wrote outstanding answers to six open-ended questions from the exam. We had an outside expert score the test, and GPT got a 5—the highest possible score, and the equivalent togetting an A or A+ in a college-level biology course.

9月，当我再次见到他们时，我敬畏地看着他们问他们的人工智能模型GPT，来自AP生物考试的60道选择题——它答对了59道。然后，它为考试中的六个开放式问题写出了出色的答案。我们请了一位外部专家对测试进行评分，GPT得到了5分——可能的最高分数，相当于大学生物学课程的a或a +。

Once it had aced the test, we asked it a non-scientific question: “What do you say to a father with a sick child?” It wrote a thoughtful answer that was probably better than most of us in the room would have given. The whole experience was stunning.

当它通过测试后，我们问了它一个非科学的问题:“你会对一个孩子生病的父亲说什么?”它写了一个深思熟虑的答案，可能比我们在座的大多数人都会给出的答案要好。整个经历令人惊叹。

I knew I had just seen the most important advance in technology since the graphical user interface.

我知道我刚刚看到了自图形用户界面以来最重要的技术进步。

This inspired me to think about all the things that AI can achieve in the next five to 10 years.

这激发了我思考人工智能在未来5到10年可以实现的所有事情。

The development of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone. It will change the way people work, learn, travel, get health care, and communicate with each other. Entire industries will reorient around it. Businesses will distinguish themselves by how well they use it.

人工智能的发展与微处理器、个人电脑、互联网和移动电话的诞生一样重要。它将改变人们工作、学习、旅行、获得医疗保健以及彼此交流的方式。整个行业都将围绕它重新定位。企业将通过如何使用它来区分自己。

Philanthropy is my full-time job these days, and I’ve been thinking a lot about how—in addition to helping people be more productive—AI can reduce some of the world’s worst inequities. Globally, the worst inequity is in health: 5 million children under the age of 5 die every year. That’s down from 10 million two decades ago, but it’s still a shockingly high number. Nearly all of these children were born in poor countries and die of preventable causes like diarrhea or malaria. It’s hard to imagine a better use of AIs than saving the lives of children.

如今，慈善事业是我的全职工作，我一直在思考，除了帮助人们提高生产力之外，人工智能如何减少世界上一些最严重的不平等。在全球范围内，最严重的不平等是在健康方面:每年有500万5岁以下儿童死亡。这比20年前的1000万有所下降，但仍然是一个惊人的高数字。几乎所有这些儿童都出生在贫穷国家，死于腹泻或疟疾等可预防的疾病。很难想象人工智能还有比拯救儿童生命更好的用途。

I’ve been thinking a lot about how AI can reduce some of the world’s worst inequities.

我一直在思考人工智能如何减少世界上一些最严重的不平等。

In the United States, the best opportunity for reducing inequity is to improve education, particularly making sure that students succeed at math. The evidence shows that having basic math skills sets students up for success, no matter what career they choose. But achievement in math is going down across the country, especially for Black, Latino, and low-income students. AI can help turn that trend around.

在美国，减少不平等的最佳机会是改善教育，特别是确保学生在数学方面取得成功。有证据表明，拥有基本的数学技能可以为学生的成功奠定基础，无论他们选择什么职业。但是全国的数学成绩都在下降，尤其是黑人、拉丁裔和低收入家庭的学生。人工智能可以帮助扭转这一趋势。

Climate change is another issue where I’m convinced AI can make the world more equitable. The injustice of climate change is that the people who are suffering the most—the world’s poorest—are also the ones who did the least to contribute to the problem. I’m still thinking and learning about how AI can help, but later in this post I’ll suggest a few areas with a lot of potential.

气候变化是我相信人工智能可以让世界更加公平的另一个问题。气候变化的不公正之处在于，遭受最大痛苦的人——世界上最贫穷的人——同时也是对这个问题贡献最少的人。我仍在思考和学习人工智能如何提供帮助，但在这篇文章的后面，我将提出几个具有很大潜力的领域。

In short, I'm excited about the impact that AI will have on issues that theGates Foundation works on, and the foundation will have much more to say about AI in the coming months. The world needs to make sure that everyone—and not just people who are well-off—benefits from artificial intelligence. Governments and philanthropy will need to play a major role in ensuring that it reduces inequity and doesn’t contribute to it. This is the priority for my own work related to AI.

简而言之，我对人工智能将对盖茨基金会正在研究的问题产生的影响感到兴奋，在未来的几个月里，基金会将会有更多关于人工智能的言论。世界需要确保每个人——而不仅仅是富人——都能从人工智能中受益。政府和慈善机构需要发挥重要作用，以确保减少不平等，而不是加剧不平等。这是我自己AI相关工作的重点。

Any new technology that’s so disruptive is bound to make people uneasy, and that’s certainly true with artificial intelligence. I understand why—it raises hard questions about the workforce, the legal system, privacy, bias, and more. AIs also make factual mistakes and experiencehallucinations. Before I suggest some ways to mitigate the risks, I’ll define what I mean by AI, and I’ll go into more detail about some of the ways in which it will help empower people at work, save lives, and improve education.

任何具有颠覆性的新技术都必然会让人们感到不安，人工智能当然也是如此。我理解其中的原因——这引发了关于劳动力、法律体系、隐私、偏见等方面的难题。人工智能也会犯事实错误并产生幻觉。在我提出一些减轻风险的方法之前，我将先定义一下人工智能的含义，并将更详细地介绍人工智能在工作中帮助人们赋权、拯救生命和改善教育的一些方式。

Technically, the termartificial intelligence refers to a model created to solve a specific problem or provide a particular service. What is powering things like ChatGPT is artificial intelligence. It is learning how to do chat better but can’t learn other tasks. By contrast, the term artificial general intelligence refers to software that’s capable of learning any task or subject. AGI doesn’t exist yet—there is a robust debate going on in the computing industry about how to create it, and whether it can even be created at all.

从技术上讲，人工智能一词指的是为解决特定问题或提供特定服务而创建的模型。为ChatGPT这样的东西提供动力的是人工智能。它正在学习如何更好地进行聊天，但无法学习其他任务。相比之下，人工通用智能一词指的是能够学习任何任务或主题的软件。AGI还不存在——在计算行业中，关于如何创建它，甚至是否可以创建它，都存在着激烈的争论。

Developing AI and AGI has been the great dream of the computing industry. For decades, the question was when computers would be better than humans at something other than making calculations. Now, with the arrival of machine learning and large amounts of computing power, sophisticated AIs are a reality and they will get better very fast.

开发AI和AGI一直是计算行业的伟大梦想。几十年来，人们的问题是，计算机什么时候能在计算之外的某些方面比人类更好。现在，随着机器学习和大量计算能力的到来，复杂的人工智能已经成为现实，它们将很快变得更好。

I think back to the early days of the personal computing revolution, when the software industry was so small that most of us could fit onstage at a conference. Today it is a global industry. Since a huge portion of it is now turning its attention to AI, the innovations are going to come much faster than what we experienced after the microprocessor breakthrough. Soon the pre-AI period will seem as distant as the days when using a computer meant typing at a C:> prompt rather than tapping on a screen.

我回想起个人电脑革命的早期，当时软件行业还很小，我们大多数人都能在一个会议上站在台上。今天，它是一个全球性的产业。由于现在它的很大一部分注意力转向人工智能，创新将比我们在微处理器突破后经历的要快得多。不久，前人工智能时代似乎就会像使用电脑意味着在C:>提示符下打字而不是在屏幕上轻敲一样遥远。

Although humans are still better than GPT at a lot of things, there are many jobs where these capabilities are not used much. For example, many of the tasks done by a person in sales (digital or phone), service, or document handling (like payables, accounting, or insurance claim disputes) require decision-making but not the ability to learn continuously. Corporations have training programs for these activities and in most cases, they have a lot of examples of good and bad work. Humans are trained using these data sets, and soon these data sets will also be used to train the AIs that will empower people to do this work more efficiently.

尽管人类在许多方面仍然比GPT更好，但在许多工作中，这些能力并没有被大量使用。例如，一个人在销售(数字或电话)、服务或文件处理(如应付账款、会计或保险索赔纠纷)方面所做的许多任务都需要决策，但不需要持续学习的能力。公司有这些活动的培训计划，在大多数情况下，他们有很多好的和坏的工作例子。人类使用这些数据集进行训练，很快这些数据集也将被用于训练人工智能，使人们能够更有效地完成这项工作。

As computing power gets cheaper, GPT’s ability to express ideas will increasingly be like having a white-collar worker available to help you with various tasks. Microsoft describes this as having a co-pilot. Fully incorporated into products like Office, AI will enhance your work—for example by helping with writing emails and managing your inbox.

随着计算能力变得越来越便宜，GPT表达想法的能力将越来越像一个可以帮助您完成各种任务的白领。微软将其描述为拥有一个副驾驶员。人工智能完全集成到Office等产品中，将增强你的工作能力，例如帮助写电子邮件和管理收件箱。

Eventually your main way of controlling a computer will no longer be pointing and clicking or tapping on menus and dialogue boxes. Instead, you’ll be able to write a request in plain English. (And not just English—AIs will understand languages from around the world. In India earlier this year, I met with developers who are working on AIs that will understand many of the languages spoken there.)

最终，你控制电脑的主要方式将不再是指向、点击或点击菜单和对话框。相反，您可以用简单的英语编写请求。(不仅是英语，人工智能还能理解世界各地的语言。今年早些时候，我在印度会见了一些开发人工智能的开发者，他们正在开发能够理解当地多种语言的人工智能。)

In addition, advances in AI will enable the creation of a personal agent. Think of it as a digital personal assistant: It will see your latest emails, know about the meetings you attend, read what you read, and read the things you don’t want to bother with. This will both improve your work on the tasks you want to do and free you from the ones you don’t want to do.

此外，人工智能的进步将使创建个人助理成为可能。把它想象成一个数字私人助理:它会看到你最新的电子邮件，知道你参加的会议，读你读过的东西，读你不想读的东西。这既能提高你在想做的任务上的工作效率，也能让你从不想做的任务中解脱出来。

Advances in AI will enable the creation of a personal agent.

人工智能的进步将使创建个人助理成为可能

You’ll be able to use natural language to have this agent help you with scheduling, communications, and e-commerce, and it will work across all your devices. Because of the cost of training the models and running the computations, creating a personal agent is not feasible yet, but thanks to the recent advances in AI, it is now a realistic goal.Some issues will need to be worked out: For example, can an insurance company ask your agent things about you without your permission? If so, how many people will choose not to use it?

您将能够使用自然语言让这个助理帮助您安排日程、通信和电子商务，并且它将在您的所有设备上工作。由于训练模型和运行计算的成本很高，创建个人代理还不可行，但由于人工智能最近的进步，现在这是一个现实的目标。有些问题需要解决:例如，保险公司可以在未经你允许的情况下询问你的助理有关你的事情吗?如果是这样，有多少人会选择不使用它?

Company-wide agents will empower employees in new ways. An agent that understands a particular company will be available for its employees to consult directly and should be part of every meeting so it can answer questions. It can be told to be passive or encouraged to speak up if it has some insight. It will need access to the sales, support, finance, product schedules, and text related to the company. It should read news related to the industry the company is in. I believe that the result will be that employees will become more productive.

全公司范围的代理将以新的方式赋予员工权力。一个了解特定公司的代理人可以为员工提供直接咨询，并且应该参加每一次会议，这样它就可以回答问题。如果它有一些见解，可以告诉它被动，或者鼓励它说出来。它将需要访问销售、支持、财务、产品时间表和与公司相关的文本。它应该阅读与该公司所在行业相关的新闻。我相信这样做的结果是，员工的工作效率将会提高。

When productivity goes up, society benefits because people are freed up to do other things, at work and at home. Of course, there are serious questions about what kind of support and retraining people will need. Governments need to help workers transition into other roles. But the demand for people who help other people will never go away. The rise of AI will free people up to do things that software never will—teaching, caring for patients, and supporting the elderly, for example.

当生产率提高时，社会也会受益，因为人们可以自由地在工作和家庭中做其他事情。当然，人们需要什么样的支持和再培训也存在严重的问题。政府需要帮助工人转变为其他角色。但是对帮助他人的人的需求永远不会消失。人工智能的兴起将解放人们去做软件永远做不到的事情——例如教学、照顾病人和照顾老人。

Global health and education are two areas where there’s great need and not enough workers to meet those needs. These are areas where AI can help reduce inequity if it is properly targeted. These should be a key focus of AI work, so I will turn to them now.

全球卫生和教育是两个有巨大需求的领域，但没有足够的工作人员来满足这些需求。如果人工智能有适当的目标，就可以在这些领域帮助减少不平等。这些应该是人工智能工作的重点，所以我现在将转向它们。

I see several ways in which AIs will improve health care and the medical field.

我认为人工智能将在几个方面改善医疗保健和医疗领域。

For one thing, they’ll help health-care workers make the most of their time by taking care of certain tasks for them—things like filing insurance claims, dealing with paperwork, and drafting notes from a doctor’s visit. I expect that there will be a lot of innovation in this area.

首先，他们将帮助医疗保健工作者充分利用他们的时间，为他们处理某些任务，比如提交保险索赔，处理文书工作，起草医生的访问记录。我期待在这个领域会有很多创新。

Other AI-driven improvements will be especially important for poor countries, where the vast majority of under-5 deaths happen.

其他人工智能驱动的改进对贫穷国家尤其重要，因为绝大多数5岁以下儿童死亡发生在贫穷国家。

For example, many people in those countries never get to see a doctor, and AIs will help the health workers they do see be more productive. (The effort to developAI-powered ultrasound machines that can be used with minimal training is a great example of this.) AIs will even give patients the ability to do basic triage, get advice about how to deal with health problems, and decide whether they need to seek treatment.

例如，这些国家的许多人从来没有看过医生，而人工智能将帮助他们看到的卫生工作者提高效率。(开发人工智能驱动的超声波机器的努力，只需最少的训练就能使用，就是一个很好的例子。)人工智能甚至可以让患者进行基本的分类，获得关于如何处理健康问题的建议，并决定他们是否需要寻求治疗。

The AI models used in poor countries will need to be trained on different diseases than in rich countries. They will need to work in different languages and factor in different challenges, such as patients who live very far from clinics or can’t afford to stop working if they get sick.

在贫穷国家使用的人工智能模型需要接受与富裕国家不同的疾病训练。他们将需要用不同的语言工作，并考虑到不同的挑战，比如住得离诊所很远的病人，或者生病后无法停止工作的病人。

People will need to see evidence that health AIs are beneficial overall, even though they won’t be perfect and will make mistakes. AIs have to be tested very carefully and properly regulated, which means it will take longer for them to be adopted than in other areas. But then again, humans make mistakes too. And having no access to medical care is also a problem.

人们需要看到健康人工智能总体上是有益的证据，尽管它们并不完美，也会犯错误。人工智能必须经过非常仔细的测试和适当的监管，这意味着人工智能需要比其他领域更长的时间才能被采用。但话又说回来，人类也会犯错。无法获得医疗也是一个问题。

In addition to helping with care, AIs will dramatically accelerate the rate of medical breakthroughs. The amount of data in biology is very large, and it’s hard for humans to keep track of all the ways that complex biological systems work. There is already software that can look at this data, infer what the pathways are, search for targets on pathogens, and design drugs accordingly. Some companies are working on cancer drugs that were developed this way.

除了帮助护理，人工智能还将大大加快医学突破的速度。生物学中的数据量非常大，人类很难跟踪复杂生物系统的所有工作方式。现在已经有软件可以查看这些数据，推断出路径，搜索病原体的目标，并相应地设计药物。一些公司正在用这种方法开发抗癌药物。

The next generation of tools will be much more efficient, and they’ll be able to predict side effects and figure out dosing levels. One of the Gates Foundation’s priorities in AI is to make sure these tools are used for the health problems that affect the poorest people in the world, including AIDS, TB, and malaria.

下一代的工具将更加高效，它们将能够预测副作用并计算出剂量水平。盖茨基金会在人工智能方面的优先事项之一是确保这些工具用于解决影响世界上最贫困人口的健康问题，包括艾滋病、结核病和疟疾。

Similarly, governments and philanthropy should create incentives for companies to share AI-generated insights into crops or livestock raised by people in poor countries. AIs can help develop better seeds based on local conditions, advise farmers on the best seeds to plant based on the soil and weather in their area, and help develop drugs and vaccines for livestock. As extreme weather and climate change put even more pressure on subsistence farmers in low-income countries, these advances will be even more important.

同样，政府和慈善机构应该鼓励企业分享人工智能对贫困国家人民饲养的作物或牲畜的洞察。人工智能可以根据当地条件帮助开发更好的种子，根据当地的土壤和天气为农民提供最好的种子建议，并帮助开发用于牲畜的药物和疫苗。随着极端天气和气候变化给低收入国家的自给农民带来更大的压力，这些进展将变得更加重要。

Computers haven’t had the effect on education that many of us in the industry have hoped. There have been some good developments, including educational games and online sources of information like Wikipedia, but they haven’t had a meaningful effect on any of the measures of students’ achievement.

计算机对教育的影响并没有像我们许多业内人士所希望的那样。有一些好的发展，包括教育游戏和像维基百科这样的在线信息来源，但它们没有对衡量学生成绩的任何指标产生有意义的影响。

But I think in the next five to 10 years, AI-driven software will finally deliver on the promise of revolutionizing the way people teach and learn. It will know your interests and your learning style so it can tailor content that will keep you engaged. It will measure your understanding, notice when you’re losing interest, and understand what kind of motivation you respond to. It will give immediate feedback.

但我认为，在未来5到10年里，人工智能驱动的软件将最终实现人们教学和学习方式的革命。它会了解你的兴趣和学习风格，从而为你量身定制内容，让你沉浸其中。它会衡量你的理解力，注意到你什么时候失去兴趣，并了解你对什么样的动机做出反应。它会立即给出反馈。

There are many ways that AIs can assist teachers and administrators, including assessing a student’s understanding of a subject and giving advice on career planning. Teachers are already using tools like ChatGPT to provide comments on their students’ writing assignments.

人工智能可以在很多方面帮助教师和管理人员，包括评估学生对一门学科的理解，并就职业规划提供建议。老师们已经在使用ChatGPT这样的工具来为学生的写作作业提供评论。

Of course, AIs will need a lot of training and further development before they can do things like understand how a certain student learns best or what motivates them. Even once the technology is perfected, learning will still depend on great relationships between students and teachers. It will enhance—but never replace—the work that students and teachers do together in the classroom.

当然，人工智能还需要大量的培训和进一步的发展，才能了解某个学生如何学习得最好，或者是什么激励了他们。即使技术完善了，学习仍将依赖于师生之间良好的关系。它将加强——但永远不会取代——学生和老师在课堂上共同完成的工作。

New tools will be created for schools that can afford to buy them, but we need to ensure that they are also created for and available to low-income schools in the U.S. and around the world. AIs will need to be trained on diverse data sets so they are unbiased and reflect the different cultures where they’ll be used. And the digital divide will need to be addressed so that students in low-income households do not get left behind.

我们将为有能力购买这些工具的学校创造新的工具，但我们需要确保这些工具也为美国和世界各地的低收入学校创造并提供。人工智能将需要在不同的数据集上接受训练，以便它们是公正的，并反映它们将被使用的不同文化。数字鸿沟需要解决，这样低收入家庭的学生才不会掉队。

I know a lot of teachers are worried that students are using GPT to write their essays. Educators are already discussing ways to adapt to the new technology, and I suspect those conversations will continue for quite some time. I’ve heard about teachers who have found clever ways to incorporate the technology into their work—like by allowing students to use GPT to create a first draft that they have to personalize.

我知道很多老师担心学生使用GPT写论文。教育工作者已经在讨论如何适应这种新技术，我怀疑这种讨论还会持续很长一段时间。我听说有些老师找到了聪明的方法，将这项技术融入到他们的工作中，比如允许学生使用GPT来创建他们必须个性化的初稿。

You’ve probably read about problems with the current AI models. For example, they aren’t necessarily good at understanding the context for a human’s request, which leads to some strange results. When you ask an AI to make up something fictional, it can do that well. But when you ask for advice about a trip you want to take, it may suggest hotels that don’t exist. This is because the AI doesn’t understand the context for your request well enough to know whether it should invent fake hotels or only tell you about real ones that have rooms available.

你可能读过关于当前人工智能模型的问题。例如，它们不一定擅长理解人类请求的上下文，这导致了一些奇怪的结果。当你让人工智能编造一些虚构的东西时，它可以做得很好。但是当你询问关于你想要的旅行的建议时，它可能会建议一些不存在的酒店。这是因为人工智能不能很好地理解你的请求的上下文，不知道它是应该虚构虚构的酒店，还是只告诉你有空房的真实酒店。

There are other issues, such as AIs giving wrong answers to math problems because they struggle with abstract reasoning. But none of these are fundamental limitations of artificial intelligence. Developers are working on them, and I think we’re going to see them largely fixed in less than two years and possibly much faster.

还有其他问题，比如人工智能在数学问题上给出错误答案，因为它们难以进行抽象推理。但这些都不是人工智能的根本局限。开发人员正在努力解决这些问题，我认为我们将在不到两年的时间里看到这些问题得到很大程度的修复，甚至可能更快。

Other concerns are not simply technical. For example, there’s the threat posed by humans armed with AI. Like most inventions, artificial intelligence can be used for good purposes or malign ones. Governments need to work with the private sector on ways to limit the risks.

其他的担忧不仅仅是技术上的。例如，装备人工智能对人类构成的威胁。和大多数发明一样，人工智能可以用于好的目的，也可以用于坏的目的。政府需要与私营部门合作，设法限制风险。

Then there’s the possibility that AIs will run out of control. Could a machine decide that humans are a threat, conclude that its interests are different from ours, or simply stop caring about us? Possibly, but this problem is no more urgent today than it was before the AI developments of the past few months.

人工智能也有可能会失去控制。机器是否会认为人类是一种威胁，得出它的利益与我们不同的结论，或者干脆不再关心我们?也许吧，但这个问题在今天并不比过去几个月人工智能发展之前更紧迫。

Superintelligent AIs are in our future. Compared to a computer, our brains operate at a snail’s pace: An electrical signal in the brain moves at 1/100,000th the speed of the signal in a silicon chip! Once developers can generalize a learning algorithm and run it at the speed of a computer—an accomplishment that could be a decade away or a century away—we’ll have an incredibly powerful AGI. It will be able to do everything that a human brain can, but without any practical limits on the size of its memory or the speed at which it operates. This will be a profound change.

超级智能人工智能就在我们的未来。与计算机相比，我们的大脑以蜗牛的速度运行:大脑中的电信号的移动速度是硅芯片中信号的十万分之一!一旦开发人员可以概括一个学习算法，并以计算机的速度运行它——这可能是十年或一个世纪之后的成就——我们将拥有一个令人难以置信的强大的AGI。它将能做人脑能做的一切事情，但它的内存大小或运行速度没有任何实际限制。这将是一个深刻的变化。

These “strong” AIs, as they’re known, will probably be able to establish their own goals. What will those goals be? What happens if they conflict with humanity’s interests? Should we try to prevent strong AI from ever being developed? These questions will get more pressing with time.

这些被称为“强大”的人工智能很可能能够建立自己的目标。这些目标是什么?如果它们与人类的利益相冲突，会发生什么?我们是否应该阻止强人工智能的发展?随着时间的推移，这些问题将变得更加紧迫。

But none of the breakthroughs of the past few months have moved us substantially closer to strong AI. Artificial intelligence still doesn’t control the physical world and can’t establish its own goals. A recentNew York Times article about a conversation with ChatGPT where it declared it wanted to become a human got a lot of attention. It was a fascinating look at how human-like the model's expression of emotions can be, but it isn't an indicator of meaningful independence.

但过去几个月的突破都没有让我们真正接近强人工智能。人工智能仍然不能控制物理世界，也不能建立自己的目标。《纽约时报》最近刊登了一篇关于ChatGPT的对话的文章，其中ChatGPT宣布它想变成一个人，这引起了广泛关注。这是一个迷人的观察，可以看到模型的情感表达是如何与人类相似的，但这并不是一个有意义的独立的指标。

Three books have shaped my own thinking on this subject:Superintelligence, by Nick Bostrom; Life 3.0 by Max Tegmark; and A Thousand Brains, by Jeff Hawkins. I don’t agree with everything the authors say, and they don’t agree with each other either. But all three books are well written and thought-provoking.

有三本书塑造了我对这个问题的看法:尼克·博斯特罗姆(Nick Bostrom)的《超级智能》(Superintelligence);马克斯·泰格马克的《生活3.0》;以及杰夫·霍金斯的《一千个大脑》。我不同意作者所说的一切，他们彼此之间也不一致。但这三本书都写得很好，发人深省。

There will be an explosion of companies working on new uses of AI as well as ways to improve the technology itself. For example, companies are developing new chips that will provide the massive amounts of processing power needed for artificial intelligence. Some use optical switches—lasers, essentially—to reduce their energy consumption and lower the manufacturing cost. Ideally, innovative chips will allow you to run an AI on your own device, rather than in the cloud, as you have to do today.

将会有大量公司致力于人工智能的新用途，以及改进技术本身的方法。例如，一些公司正在开发新的芯片，为人工智能提供所需的大量处理能力。有些使用光学开关(本质上是激光)来减少能源消耗和降低制造成本。理想情况下，创新芯片将允许你在自己的设备上运行人工智能，而不是像现在这样在云端运行。

On the software side, the algorithms that drive an AI’s learning will get better. There will be certain domains, such as sales, where developers can make AIs extremely accurate by limiting the areas that they work in and giving them a lot of training data that’s specific to those areas. But one big open question is whether we’ll need many of these specialized AIs for different uses—one for education, say, and another for office productivity—or whether it will be possible to develop an artificial general intelligence that can learn any task. There will be immense competition on both approaches.

在软件方面，驱动人工智能学习的算法将变得更好。在某些领域，比如销售，开发者可以通过限制人工智能工作的领域，并为它们提供大量特定于这些领域的训练数据，来让它们变得非常准确。但一个悬而未决的大问题是，我们是否需要许多这种专门的人工智能用于不同的用途——比如一个用于教育，另一个用于办公室生产力——或者是否有可能开发出一种可以学习任何任务的通用人工智能。这两种方法都将面临巨大的竞争。

No matter what, the subject of AIs will dominate the public discussion for the foreseeable future. I want to suggest three principles that should guide that conversation.

无论如何，人工智能的主题将在可预见的未来主导公众讨论。我想提出三个原则来指导这场对话。

First, we should try to balance fears about the downsides of AI—which are understandable and valid—with its ability to improve people’s lives. To make the most of this remarkable new technology, we’ll need to both guard against the risks and spread the benefits to as many people as possible.

首先，我们应该努力平衡对人工智能负面影响的担忧——这是可以理解和有效的——以及它改善人们生活的能力。为了充分利用这项非凡的新技术，我们既需要防范风险，又需要让尽可能多的人受益。

Second, market forces won’t naturally produce AI products and services that help the poorest. The opposite is more likely. With reliable funding and the right policies, governments and philanthropy can ensure that AIs are used to reduce inequity. Just as the world needs its brightest people focused on its biggest problems, we will need to focus the world’s best AIs on its biggest problems.

其次，市场力量不会自然地产生帮助最贫困人口的人工智能产品和服务。相反的可能性更大。有了可靠的资金和正确的政策，政府和慈善机构可以确保人工智能被用于减少不平等。正如世界需要最聪明的人专注于最大的问题，我们也需要让世界上最好的人工智能专注于最大的问题。

Although we shouldn’t wait for this to happen, it’s interesting to think about whether artificial intelligence would ever identify inequity and try to reduce it. Do you need to have a sense of morality in order to see inequity, or would a purely rational AI also see it? If it did recognize inequity, what would it suggest that we do about it?

虽然我们不应该坐等这种情况发生，但思考人工智能是否能够识别不平等并试图减少这种不平等是很有趣的。你是否需要有道德感才能看到不平等，或者一个纯粹理性的AI也能看到它?如果它确实认识到不平等，它会建议我们对此做些什么?

Finally, we should keep in mind that we’re only at the beginning of what AI can accomplish. Whatever limitations it has today will be gone before we know it.

最后，我们应该记住，我们只是在人工智能所能完成的事情的开始。无论今天它有什么限制，在我们意识到它之前都会消失。

I’m lucky to have been involved with the PC revolution and the Internet revolution. I’m just as excited about this moment. This new technology can help people everywhere improve their lives. At the same time, the world needs to establish the rules of the road so that any downsides of artificial intelligence are far outweighed by its benefits, and so that everyone can enjoy those benefits no matter where they live or how much money they have. The Age of AI is filled with opportunities and responsibilities.

我很幸运地参与了个人电脑革命和互联网革命。这一刻我也很兴奋。这项新技术可以帮助世界各地的人们改善生活。与此同时，世界需要建立道路规则，让人工智能的任何缺点都远远超过它的好处，让每个人都能享受这些好处，无论他们住在哪里，无论他们有多少钱。人工智能时代充满机遇和责任。