The Age of AI has begun By Bill Gates

AI時代已經(jīng)開始 比爾·蓋茨 人工智能（AI）正逐漸走進我們生活的方方面面。它們（指AI）在醫(yī)藥、農(nóng)業(yè)、交通等眾多領(lǐng)域中，都具備優(yōu)異的表現(xiàn)。許多家庭現(xiàn)在都擁有智能掃地機、智能音箱等智能設(shè)備。我們的車輛、電話甚至整個家庭都成了智能化的對象。 這標志著我們現(xiàn)在正處于AI時代。 隨著技術(shù)的快速發(fā)展和日益普遍的應(yīng)用，AI在未來仍有巨大的發(fā)展?jié)摿?。因此，我們必須認真對待AI發(fā)展和應(yīng)用的道德和法律問題。 雖然AI可以進行許多操作，但它們?nèi)匀蝗狈θ祟惛兄芰?。因此，我們必須確保AI不會對人類造成傷害。 AI時代帶來的重大機遇和挑戰(zhàn)，需要我們緊密團結(jié)起來，共同推動AI的可持續(xù)發(fā)展。

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

在我的有生之年，我曾見證過兩次讓我感到革命性的技術(shù)展示。

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，當(dāng)我被介紹給了一個圖形用戶界面——所有現(xiàn)代操作系統(tǒng)的前身，包括Windows。我和給我展示演示的那個人，一位才華橫溢的程序員Charles Simonyi一起坐著，我們立刻開始了頭腦風(fēng)暴，想象著我們可以用這種用戶友好的計算方式做的所有事情。Charles最終加入了微軟，Windows成為了微軟的支柱，而我們在演示之后進行的思考幫助設(shè)定了公司未來15年的議程。

The second big surprise came just last year. I’d been meeting with the team from OpenAI 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.

第二個驚喜是在去年才發(fā)生的。我從2016年開始就一直與OpenAI的團隊見面，被他們的穩(wěn)步進展所打動。到2022年中期，我對他們的工作非常興奮，以至于給了他們一個挑戰(zhàn)：訓(xùn)練一種人工智能來通過高級生物學(xué)考試，并使其能夠回答其未經(jīng)專門訓(xùn)練的問題。(我選擇了AP Bio，因為這項考試不僅涉及對科學(xué)事實的簡單背誦，還需要您對生物學(xué)進行批判性思考。)如果你能做到這一點，我說，那么你就會有一個真正的突破。

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

我以為這項挑戰(zhàn)能讓他們忙碌兩到三年。但他們僅用了幾個月就完成了。

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 to getting an A or A+ in a college-level biology course.

九月份，當(dāng)我再次見到他們時，我驚奇地看著他們向GPT，他們的AI模型，提出了60個AP生物考試的選擇題，并且回答了其中59個問題。然后，它為這場考試中的六個開放性問題寫下了出色的答案。我們請了一位外部專家對考試進行評分，GPT得到了5分-最高的可能得分，相當(dāng)于在大學(xué)生物課程中獲得A或A +評分。

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.

一旦它通過了測試，我們問了一個非科學(xué)問題：“對于有病的孩子的父親你會說什么？”它寫下了一個周到的答案，可能比我們在房間里大多數(shù)人都要好。整個經(jīng)歷非常震撼。

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

我知道我剛剛看到了自圖形用戶界面以來最重要的科技進步。

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

這讓我想到人工智能在未來五到十年能夠?qū)崿F(xiàn)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.

AI的發(fā)展與微處理器、個人電腦、互聯(lián)網(wǎng)和手機的創(chuàng)造一樣基礎(chǔ)。它將改變?nèi)藗兊墓ぷ?、學(xué)習(xí)、旅游、醫(yī)療保健和相互溝通的方式。整個產(chǎn)業(yè)將圍繞它重新定位。企業(yè)將通過它的使用效果來區(qū)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.

慈善成為了我目前的全職工作，我一直在思考一個問題——除了幫助人們提高生產(chǎn)力，人工智能如何能夠減少一些世界上最嚴重的不平等現(xiàn)象。全球而言，最嚴重的不平等現(xiàn)象出現(xiàn)在健康領(lǐng)域：每年有500萬5歲以下的兒童死亡。盡管這個數(shù)字已經(jīng)比二十年前的1000萬下降了，但仍然是一個驚人的數(shù)字。幾乎所有這些兒童出生于貧窮的國家，死于可以預(yù)防的疾病，比如腹瀉或瘧疾。再也沒有比挽救兒童生命更好地利用人工智能了。

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能夠減少世界上一些最嚴重的不公平現(xiàn)象。

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.

在美國，減少不公平最好的機會就是提高教育，特別是確保學(xué)生在數(shù)學(xué)方面取得成功。證據(jù)表明，具備基本的數(shù)學(xué)技能可以為學(xué)生成功打下基礎(chǔ)，無論他們選擇什么職業(yè)。但是，全國范圍內(nèi)數(shù)學(xué)成就下降，特別是對于黑人、拉丁裔和低收入學(xué)生而言。人工智能可以幫助扭轉(zhuǎn)這一趨勢。

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.

氣候變化是另一個問題，我相信AI能夠讓世界更加公平。氣候變化的不公正在于那些最受苦的人——世界上最貧窮的人——是最少為這個問題做出貢獻的人。我仍在思考和學(xué)習(xí)如何利用AI來幫助解決這個問題，但是在本文的后面，我會提出一些具有巨大潛力的領(lǐng)域。

In short, I’m excited about the impact that AI will have on issues that the Gates 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.

簡而言之，我對人工智能將對蓋茨基金會所涉及的問題產(chǎn)生的影響感到興奮，并且該基金會在未來幾個月中將有更多關(guān)于人工智能的發(fā)言。全世界需要確保每個人——而不僅僅是富人——都從人工智能中受益。政府和慈善事業(yè)將需要在確保人工智能減少不平等方面發(fā)揮重要作用，并且不會造成不公。這是我自己關(guān)于人工智能的工作的優(yōu)先方向。

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 experience hallucinations. 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.

任何一項具有顛覆性的新技術(shù)都會讓人感到不安，人工智能也是如此。我理解這種感覺，因為它會帶出關(guān)于勞動力、法律制度、隱私、偏見等問題，也會出現(xiàn)事實錯誤和錯覺。在我提出一些降低風(fēng)險的方法之前，我將定義我所指的人工智能，以及詳細說明它將如何幫助人們在工作中更有能力，挽救生命，以及改善教育。

Defining artificial intelligence

定義人工智能 人工智能（AI）是指設(shè)計和開發(fā)能夠表現(xiàn)出類似于人類思維和行為的計算機系統(tǒng)。這些系統(tǒng)可以執(zhí)行智能任務(wù)，例如理解語言、看懂圖片、自動駕駛汽車、處理復(fù)雜的數(shù)據(jù)分析和自動化流程等等。人工智能基于機器學(xué)習(xí)、深度學(xué)習(xí)和自然語言處理等技術(shù)，可通過不斷學(xué)習(xí)和調(diào)整來提高性能和精度。隨著技術(shù)的不斷發(fā)展，人工智能正變得越來越無處不在，并被廣泛應(yīng)用于各行各業(yè)，為人們生活和工作帶來創(chuàng)新、便利和效率。

Technically, the term artificial 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.

從技術(shù)角度來說，人工智能一詞是指用于解決特定問題或提供特定服務(wù)的模型。像ChatGPT這樣的東西所使用的是人工智能。它正在學(xué)習(xí)如何更好地進行聊天，但不能學(xué)習(xí)其他任務(wù)。相比之下，人工通用智能這個術(shù)語是指能夠?qū)W習(xí)任何任務(wù)或主題的軟件。AGI目前還不存在——計算機行業(yè)正在進行激烈的辯論，討論如何創(chuàng)建它，以及它是否可以被創(chuàng)建。

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.

開發(fā)人工智能和通用人工智能一直是計算機產(chǎn)業(yè)的偉大夢想。幾十年來，問題一直是計算機什么時候會比人類更擅長其他非計算任務(wù)。現(xiàn)在，隨著機器學(xué)習(xí)和大量計算能力的到來，復(fù)雜的人工智能已成為現(xiàn)實，并且它們將迅速變得更好。

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.

我回想起個人計算機革命的早期，當(dāng)時軟件行業(yè)如此之小，以至于我們大多數(shù)人可以站在一個會議的舞臺上。如今，這是一個全球性的產(chǎn)業(yè)。由于其中很大一部分現(xiàn)在正在將注意力轉(zhuǎn)向人工智能，創(chuàng)新的速度將比微處理器突破后我們經(jīng)歷的速度快得多。很快，前人工智能時代將會像使用計算機意味著在C:>提示符上打字而不是在屏幕上敲擊時的日子一樣遙遠。

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.

雖然人類在許多方面仍然比GPT更勝一籌，但有許多工作并未充分利用這些技能。例如，銷售（數(shù)字或電話）、服務(wù)或文件處理（如應(yīng)付款項、會計或保險索賠糾紛）等任務(wù)需要決策能力，但并不需要持續(xù)學(xué)習(xí)的能力。公司有專門的培訓(xùn)計劃來進行這些活動，并且在大多數(shù)情況下，他們有許多優(yōu)秀和糟糕工作的示例。人類使用這些數(shù)據(jù)集進行培訓(xùn)，很快，這些數(shù)據(jù)集也將用于培訓(xùn)將賦予人們更高效工作的人工智能。

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.

隨著計算能力變得更加廉價，GPT 表達觀點的能力將越來越像擁有一位白領(lǐng)工人來幫助您處理各種任務(wù)。微軟將其描述為擁有一位副駕駛員。人工智能完全融入像 Office 這樣的產(chǎn)品中，將增強您的工作，例如幫助撰寫電子郵件和管理收件箱。

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.)

最終，你控制電腦的主要方式不再是通過指向和點擊或點擊菜單和對話框。相反，你將能夠用簡單的英語書寫請求。（而且不僅僅是英語-人工智能將理解世界各地的語言。今年早些時候，我在印度與正在研發(fā)將理解那里許多語言的人工智能的開發(fā)人員會面。）

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，人工智能的進步將使得個人代理的創(chuàng)建成為可能。可以將它看作為一位數(shù)字化的個人助手：它將會查看你的最新電子郵件，了解你參加的會議，讀取你所閱讀的內(nèi)容，還會幫你處理你不想煩心的事情。這不僅可以提高你想做的任務(wù)的工作效率，還可以使你擺脫你不想做的任務(wù)。

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

AI 的進步將使得個人代理的創(chuàng)建得以實現(xiàn)。

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?

您將能夠使用自然語言讓該代理幫助您安排日程，進行溝通和電子商務(wù)，并且它可以跨越您所有的設(shè)備。由于培訓(xùn)模型和進行計算的成本，創(chuàng)建個人代理尚不可行，但由于人工智能方面的最近進展，這現(xiàn)在已成為一個現(xiàn)實目標。還需要解決一些問題：例如，保險公司是否可以在未經(jīng)您許可的情況下詢問您的代理有關(guān)您的事情？如果可以，有多少人會選擇不使用它？

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.

全公司代理將以全新的方式賦予員工權(quán)力。了解特定公司的代理將可供其員工直接咨詢，并應(yīng)該成為每次會議的一部分，以便回答問題。它可以被告知保持消極態(tài)度，或者鼓勵它發(fā)表見解。它需要訪問與公司相關(guān)的銷售、支持、財務(wù)、產(chǎn)品時間表和文本。它應(yīng)該閱讀與公司所處行業(yè)相關(guān)的新聞。我相信，結(jié)果將是員工變得更加高效。

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.

當(dāng)生產(chǎn)力提高時，社會因為人們在工作和家庭生活中的時間得到了釋放而受益。當(dāng)然，人們需要得到何種支持和再培訓(xùn)方面的嚴肅問題亟待解決。政府需要幫助工人轉(zhuǎn)換到其他職位。但是，為那些幫助別人的人提供服務(wù)的需求永遠不會消失。人工智能的興起將使人們有更多的時間去做軟件永遠無法做到的事情，例如教學(xué)、照顧病人和老年人的支持。

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.

全球衛(wèi)生和教育是兩個迫切需要但人力資源不足的領(lǐng)域。如果正確地定位，人工智能可以幫助減少不平等的問題。這些領(lǐng)域應(yīng)是人工智能工作的重點，因此現(xiàn)在我將轉(zhuǎn)向它們。

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

我看到幾種方式，人工智能將提高醫(yī)療保健和醫(yī)學(xué)領(lǐng)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，它們將通過代勞一些任務(wù)來幫助醫(yī)護工作者充分利用時間——這些任務(wù)包括處理保險索賠、處理文書工作和撰寫醫(yī)生訪問筆記。我預(yù)計這個領(lǐng)域?qū)⒂性S多創(chuàng)新。

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

其他由人工智能推動的改進尤其對貧窮國家至關(guān)重要，這些國家的絕大多數(shù)5歲以下兒童死亡事件就發(fā)生在這里。

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 develop AI-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，在那些國家，許多人從未看過醫(yī)生，AI將幫助他們看到的醫(yī)療工作者更加高效。 （開發(fā)具有最少培訓(xùn)使用AI的超聲波機器是一個很好的例子。） AI甚至將給予患者進行基本分診的能力，獲得有關(guān)如何處理健康問題的建議，并決定他們是否需要尋求治療。

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.

在貧窮的國家使用的AI模型需要針對不同的疾病進行訓(xùn)練，與富裕國家的不同。 它們需要使用不同的語言，并考慮到其他挑戰(zhàn)，例如住得離門診非常遠或生病了無法停工的患者。

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.

人們需要看到證據(jù)表明健康人工智能整體上是有益的，即使它們不會完美無缺并會犯錯。人工智能必須經(jīng)過仔細測試和適當(dāng)監(jiān)管，這意味著它們采用的時間比其他領(lǐng)域要更長。但話說回來，人類也會犯錯。而沒有獲得醫(yī)療保健也是一個問題。

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.

除了幫助照顧，人工智能還將大大加快醫(yī)學(xué)突破的速度。生物學(xué)中的數(shù)據(jù)量非常大，人類很難跟蹤復(fù)雜生物系統(tǒng)運作的所有方式。已經(jīng)有軟件可以查看這些數(shù)據(jù)，推斷出通路，尋找病原體上的目標，并設(shè)計相應(yīng)的藥物。一些公司正在研發(fā)通過這種方式開發(fā)出的抗癌藥物。

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.

下一代工具將會更加高效，能夠預(yù)測副作用和確定劑量水平。蓋茨基金會在人工智能方面的優(yōu)先事項之一是確保這些工具用于解決影響全球最貧困人群的健康問題，包括艾滋病、結(jié)核病和瘧疾。

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.

同樣，政府和慈善組織應(yīng)該為公司分享基于人們在貧困國家種植的作物或家畜所產(chǎn)生的人工智能洞見創(chuàng)造激勵措施。人工智能可以幫助根據(jù)當(dāng)?shù)貤l件開發(fā)更好的種子，根據(jù)其所在地區(qū)的土壤和天氣向農(nóng)民提供最佳種植建議，以及幫助開發(fā)家畜藥物和疫苗。隨著極端天氣和氣候變化對低收入國家自給自足的農(nóng)民施加更大的壓力，這些進步將變得更加重要。

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.

電腦并沒有像我們業(yè)內(nèi)的很多人所期望的那樣對教育產(chǎn)生影響。雖然有一些好的發(fā)展，包括教育游戲和在線信息來源，比如維基百科，但這些并沒有對學(xué)生的成績產(chǎn)生有意義的影響。

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.

但我認為在未來的五到十年內(nèi)，AI驅(qū)動的軟件將最終實現(xiàn)革命性地改變?nèi)藗兊慕虒W(xué)和學(xué)習(xí)方式的承諾。它將了解您的興趣和學(xué)習(xí)風(fēng)格，以便量身打造內(nèi)容來吸引您。它將衡量您的理解程度，注意到您失去興趣的時候，并理解您對什么樣的激勵方式做出反應(yīng)。它將提供即時反饋。

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（AI）可以協(xié)助教師和行政人員的方式有很多，包括評估學(xué)生對學(xué)科的理解并提供職業(yè)規(guī)劃建議。教師們已經(jīng)利用像ChatGPT這樣的工具提供對學(xué)生寫作任務(wù)的評論。

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.

當(dāng)然，人工智能需要大量的訓(xùn)練和進一步的開發(fā)，才能像理解某個學(xué)生最佳學(xué)習(xí)方式或是什么能激發(fā)他們的動力等這樣的事情。即使技術(shù)被完善，學(xué)習(xí)仍然依賴于學(xué)生和教師之間的良好關(guān)系。它將改善 - 但永遠不會取代 - 學(xué)生和教師在課堂上一起工作的方式。

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.

將內(nèi)容翻譯成簡體中文：將會為那些有財力購買的學(xué)校創(chuàng)建新的教育工具，但我們需要確保它們也面向美國和世界各地的低收入學(xué)校，并提供給他們。需要對不同數(shù)據(jù)集進行人工智能的訓(xùn)練，以確保它們沒有偏見，能夠反映將要使用它們的不同文化。同時需要解決數(shù)字鴻溝問題，以保證低收入家庭的學(xué)生不會被落下。

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.

我知道很多老師擔(dān)心學(xué)生使用GPT來寫論文。教育工作者已經(jīng)開始討論適應(yīng)新技術(shù)的方法，我猜這些討論會持續(xù)相當(dāng)長時間。我聽說過老師們發(fā)現(xiàn)了巧妙的方法將技術(shù)融入到他們的工作中--比如允許學(xué)生使用GPT來創(chuàng)建第一稿，然后他們必須對其進行個性化處理。

Risks and problems with AI

AI的風(fēng)險和問題

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.

你可能已經(jīng)閱讀過當(dāng)前人工智能模型的問題。例如，它們不一定擅長理解人類的請求背景，這導(dǎo)致一些奇怪的結(jié)果。當(dāng)你要求一個人工智能虛構(gòu)一些東西時，它可能做得很好。但當(dāng)你詢問一次旅行計劃的建議時，它可能會建議不存在的酒店。這是因為人工智能并不足夠了解你的請求背景，無法知道它是否應(yīng)該發(fā)明虛假的酒店或只告訴你有實際房間可用的真實酒店。

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.

還有其他問題，比如人工智能在數(shù)學(xué)問題上給出錯誤答案，因為它們很難處理抽象推理。但這些并不是人工智能的基本限制。開發(fā)人員正在解決這些問題，我認為這些問題很快將在不到兩年的時間內(nèi)得到很大程度的解決，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.

其他問題并非僅僅是技術(shù)上的。例如，AI武裝的人所帶來的威脅。像大多數(shù)的發(fā)明一樣，人工智能可以用于善良的目的或惡意的目的。政府需要與私營部門合作，尋求限制風(fēng)險的方法。

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.

那么，AI 可能失控。一個機器可能決定人類是威脅，得出自己的利益與我們的不同，或者干脆不再關(guān)心我們?？赡苁?，但這個問題今天并不比過去幾個月的 AI 發(fā)展更緊迫。

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.

超級智能人工智能將是我們未來的發(fā)展方向。與計算機相比，我們的大腦運轉(zhuǎn)緩慢：大腦的電信號速度只有硅芯片的1/100,000!一旦開發(fā)者能夠?qū)W(xué)習(xí)算法普適化并以計算機的速度運行——這可能需要十年也可能需要一個世紀——我們將擁有一個非常強大的 AGI。它將能夠做到人類大腦所能做到的所有事情，但沒有任何實際大小和速度限制。這將是一次深刻的變革。

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.

這些“強大”的人工智能，也就是所謂的AIs，很可能能夠確立自己的目標。那么這些目標會是什么呢？如果它們與人類的利益相沖突會發(fā)生什么呢？我們應(yīng)該試圖阻止強大的人工智能的發(fā)展嗎？隨著時間的推移，這些問題將變得更加緊迫。

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 recent New 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.

但過去幾個月的所有突破都沒有讓我們實質(zhì)性地靠近強化智能。人工智能仍然無法控制實際世界，也無法確立自己的目標。最近《紐約時報》的一篇文章介紹了與ChatGPT的一次交談，其中ChatGPT宣稱想成為一個人，引起了很多關(guān)注。雖然這是一個人類情感表達模型與人類相似程度的有趣展示，但它并不能說明意義上的獨立。

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.

三本書影響了我對這個話題的思考：尼克·博斯特羅姆的《超級智能》，馬克斯·特格馬克的《生命3.0》，以及杰夫·霍金斯的《千萬個大腦》。我不完全同意這些作者所說的一切，他們也不互相認同。但這三本書都寫得很好，能激發(fā)人們的思考。

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.

隨著人工智能應(yīng)用的不斷推進和技術(shù)自身的不斷完善，我們將看到越來越多的公司專注于新的人工智能應(yīng)用和技術(shù)改進。例如，一些公司正在開發(fā)新的芯片，以提供用于人工智能所需的大量處理能力。一些公司采用光學(xué)開關(guān)——基本上是激光器——來降低能量消耗和降低制造成本。理想情況下，創(chuàng)新的芯片將讓你在自己的設(shè)備上運行人工智能，而不像今天一樣必須在云端運行。

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.

在軟件方面，驅(qū)動人工智能學(xué)習(xí)的算法將變得更加優(yōu)秀。在某些領(lǐng)域，比如銷售，開發(fā)者可以通過限制其工作范圍并為其提供特定領(lǐng)域的大量訓(xùn)練數(shù)據(jù)，使人工智能變得非常準確。但一個大問題是，我們是否需要許多不同用途的專用人工智能，比如一個用于教育，另一個用于辦公室生產(chǎn)力，或者是否可能開發(fā)一種人工通用智能，能夠?qū)W習(xí)任何任務(wù)。這兩種方法都將面臨巨大的競爭。

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.

無論如何，未來可預(yù)見的是AI主題將主導(dǎo)公共討論。我想建議三個應(yīng)該指導(dǎo)這個對話的原則。

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，我們應(yīng)該努力平衡對人工智能負面影響的擔(dān)憂——這些擔(dān)憂是可以理解和合理的——以及它改善人們生活的能力。為了充分利用這一令人驚嘆的新技術(shù)，我們需要既防范風(fēng)險，又將利益盡量擴大到更多的人。

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. 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?

其次，市場力量不會自然地生產(chǎn)幫助最貧困地區(qū)的人們的人工智能產(chǎn)品和服務(wù)，相反的可能性更大。通過可靠的資助和正確的政策，政府和慈善機構(gòu)可以確保人工智能被用于減少不平等現(xiàn)象。就像世界需要最聰明的人才專注于解決最大的問題一樣，我們也需要將世界上最好的人工智能集中于解決最大的問題上。雖然我們不應(yīng)該等待這種情況的發(fā)生，但思考一下人工智能是否會識別不平等現(xiàn)象并試圖減少它，確實很有意思。是否需要有道德意識才能看到不平等現(xiàn)象，還是僅有純粹的理性AI也能看到它？如果它確實認識到不平等現(xiàn)象，會建議我們采取什么措施呢？

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，我們應(yīng)該牢記的是，我們現(xiàn)在所見到的AI的能力只是開始，它今天所具有的任何限制都將在我們意識到之前被消除。

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.

我很幸運參與了個人電腦革命和互聯(lián)網(wǎng)革命。我同樣對此時此刻感到興奮。這種新技術(shù)可以幫助世界各地的人們改善生活。同時，世界需要確立規(guī)則，以便人工智能的任何負面影響都被其好處所抵消，并使每個人都可以享受這些好處，無論他們住在哪里或擁有多少錢。人工智能時代充滿了機遇和責(zé)任。