比尔盖茨最新发文 | 人工智能时代已经开启（全文）
本帖最后由 超新星 于 2023-3-30 09:23 编辑作者：比尔盖茨（文章来源：由“无边星宿”翻译）
全文约6500字，阅读时间13分钟
比尔盖茨关于AGI（通用人工智能）chatGPT最新观点文章翻译
《The Age of AI has begun —— Artificial intelligence is as revolutionary as mobile phones and the Internet. 》
划重点
1. 开发人工智能和人工通用智能一直是计算机行业的伟大梦想
2. 人工智能的崛起将使人们有更多的时间去做软件永远无法做到的事情——例如教学、照顾患者和支持老年人等。
3. 我认为，在未来5到10年内，由人工智能驱动的软件将最终实现革命性地改变人们教学和学习的方式。
4. 像大多数发明一样，人工智能可以用于善良的目的或恶意的目的。
5. 我们应该记住，我们只是在人工智能可以实现的开始阶段。无论它今天有什么限制，它都将在我们不知不觉中被消除。
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在我的一生中，我见证了两次让我觉得是革命性的技术展示。
第一次是在1980年，当我被介绍给一个图形用户界面时，这是现代操作系统的前身，包括Windows。我与向我展示演示的人坐在一起，他是一位名叫Charles Simonyi的杰出程序员，我们立即开始为可以使用这种用户友好的计算方法所能做的所有事情进行头脑风暴。Charles最终加入了微软，Windows成为微软的骨干，并且我们在演示之后的思考帮助了公司为未来15年制定了议程。
第二个大惊喜是在去年。自2016年以来，我一直在与OpenAI团队会面，并对他们的稳步进展印象深刻。在2022年中期，我对他们的工作非常兴奋，以至于我向他们提出了一个挑战：训练一种人工智能来通过高级生物学考试。使它能够回答它没有专门接受训练的问题。（我选择了AP Bio，因为这个考试不仅仅是关于科学事实的简单复述——它要求你对生物学进行批判性思考。）如果你能做到这一点，那么你就会取得真正的突破。
我认为这个挑战会让他们忙碌两三年。他们只用了几个月就完成了。
在9月份，当我再次与他们会面时，我惊奇地看着他们向GPT，他们的AI模型，提出了60个AP Bio考试的多项选择题，并且它答对了59个。然后，它回答了六个开放性问题，写出了出色的答案。我们让一位外部专家评分，GPT获得了5分，这是最高可能的分数，相当于在大学水平的生物学课程中获得A或A+。
一旦它通过了考试，我们向它提出了一个非科学性的问题：“你对一个有生病孩子的父亲说什么？”它写了一个深思熟虑的答案，可能比我们大多数人在房间里给出的答案都好。整个经历令人震撼。
我知道我刚刚见证了自图形用户界面以来最重要的技术进步。这激发了我思考人工智能在未来五到十年内可以实现的所有事情。
人工智能的发展和微处理器、个人电脑、互联网和手机的创造一样基础。它将改变人们工作、学习、旅行、获得医疗保健和相互沟通的方式。整个产业将围绕它重新定位。企业将凭借其使用人工智能的能力来区分自己。
慈善事业是我现在的全职工作，我一直在思考，除了帮助人们提高生产力之外，人工智能如何可以减少世界上最严重的不公平现象。全球最严重的不公平在于健康：每年有500万名5岁以下的儿童死亡。这个数字与20年前的1000万相比有所下降，但仍然是一个令人震惊的高数字。几乎所有这些儿童都出生在贫穷国家，死于可预防的疾病，如腹泻或疟疾。难以想象有什么比拯救儿童生命更好的人工智能应用了。
我一直在思考人工智能如何可以减少世界上最严重的不公平现象。在美国，减少不公平现象的最好机会是改善教育，特别是确保学生在数学方面取得成功。证据表明，掌握基本数学技能可以为学生的成功打下基础，无论他们选择什么职业。但是，数学成绩在全国范围内正在下降，尤其是黑人、拉丁裔和低收入学生。人工智能可以帮助扭转这种趋势。
气候变化是另一个问题，我相信人工智能可以使世界更加公平。气候变化的不公正之处在于，受到最严重影响的人——全球最贫困的人——也是最少为问题做出贡献的人。我仍在思考和学习人工智能如何可以帮助解决这个问题，但是在本文后面，我将提出一些潜力巨大的领域。
简而言之，我对人工智能将对盖茨基金会致力于的问题产生的影响感到兴奋，基金会在未来几个月内将会有更多关于人工智能的声明。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。政府和慈善机构将需要发挥重要作用，确保人工智能减少不公平现象，而不是加剧它。这是我自己与人工智能相关的工作的重点。
任何新技术的革新都会让人们感到不安，人工智能也不例外。我理解为什么——它提出了有关劳动力、法律系统、隐私、偏见等方面的难题。人工智能也会出现事实错误和幻觉。在我建议一些缓解风险的方法之前，我将定义我所说的人工智能，并详细介绍它将如何帮助赋予人们工作能力、拯救生命和改善教育。
01
如何定义人工智能
从技术上讲，人工智能一词指的是创建用于解决特定问题或提供特定服务的模型。像ChatGPT这样的技术就是人工智能，它正在学习如何更好地进行聊天，但不能学习其他任务。相比之下，人工通用智能是指能够学习任何任务或主题的软件。目前，人工通用智能还不存在——计算机行业正在进行激烈的辩论，关于如何创建人工通用智能，以及是否可以创建它。
开发人工智能和人工通用智能一直是计算机行业的伟大梦想。几十年来，问题一直是计算机何时会在除了计算之外的某些方面比人类更出色。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，并且它们将非常快速地得到改进。
我回想起个人计算机革命早期，当时软件行业如此之小，以至于我们大多数人都可以站在会议舞台上。今天它是全球性的行业。由于巨大的部分现在正在将注意力转向人工智能，创新将比微处理器突破后我们经历的创新速度更快。很快，人工智能之前的时代将会看起来像在计算机上使用C：>提示符而不是在屏幕上敲击一样遥远。
02
生产力提升
尽管在许多方面人类仍然比GPT更优秀，但有许多工作很少使用这些能力。例如，销售（数字或电话）、服务或文件处理（如应付账款、会计或保险索赔争议）等许多任务需要做出决策，但不需要持续学习的能力。企业为这些活动设有培训计划，在大多数情况下，它们有很多良好和糟糕工作的示例。人类使用这些数据集进行培训，很快这些数据集也将用于训练人工智能，从而使人们更有效地完成这项工作。
随着计算能力变得更加便宜，GPT表达想法的能力将越来越像拥有一个白领工人来帮助您完成各种任务。微软将其描述为拥有一个联合驾驶员。在Office等产品中完全集成的人工智能将增强您的工作，例如帮助编写电子邮件和管理收件箱。
最终，您控制计算机的主要方式将不再是指针和单击或在菜单和对话框上敲击。相反，您将能够用简单的英语书写请求。（不仅是英语——人工智能将理解世界各地的语言。今年早些时候，在印度，我会见了正在开发将理解当地许多语言的人工智能的开发人员。）
此外，人工智能的进步将使个人代理的创建成为可能。将其视为数字个人助手：它将查看您最新的电子邮件，了解您参加的会议，阅读您阅读的内容，并阅读您不想烦恼的事情。这将提高您在想做的任务上的工作效率，并使您从不想做的任务中解放出来。
人工智能的进步将使创建个人代理成为可能。您将能够使用自然语言让这个代理帮助您安排日程、沟通和电子商务，并且它将在所有设备上运行。由于培训模型和运行计算的成本，目前创建个人代理还不可行，但由于人工智能最近的进展，它现在是一个现实的目标。需要解决一些问题：例如，保险公司是否可以在未经您许可的情况下向您的代理询问有关您的事情？如果是，会有多少人选择不使用它？
企业级代理将以新的方式赋予员工权力。了解特定公司的代理将为其员工提供直接咨询，并应该成为每个会议的一部分，以便它可以回答问题。它可以被告知保持沉默或鼓励其发表意见。它将需要访问公司的销售、支持、财务、产品日程和与公司相关的文本。它应该阅读与公司所在行业有关的新闻。我相信，结果将是员工变得更有生产力。
当生产力提高时，社会将受益，因为人们有更多时间去做其他事情，无论是在工作还是在家里。当然，有关人们需要什么样的支持和再培训等问题是很严肃的。政府需要帮助工人转换到其他角色。但是，帮助其他人的人永远不会消失。人工智能的崛起将使人们有更多的时间去做软件永远无法做到的事情——例如教学、照顾患者和支持老年人等。
全球健康和教育是两个迫切需要的领域，而没有足够的工人来满足这些需求。如果正确使用，人工智能可以帮助减少这些领域中的不平等。这些应该是人工智能工作的重点，因此我现在将转向它们。
我认为 AI 会有几种方式改善医疗保健和医学领域。首先，它们将帮助医护人员节省时间，帮他们处理某些任务，例如处理保险索赔、处理文件工作，以及从医生的诊断中起草笔记。我预计这个领域将会有很多的创新。
其他由 AI 推动的改进对贫穷国家尤其重要，因为那里大多数的 5 岁以下儿童死亡。
例如，在那些国家，很多人永远没有机会去看医生，而 AI 将会帮助那些能看到医生的卫生工作者更有效率。（开发 AI 驱动的超声波机器，它能用最少的培训时间就能使用，就是一个很好的例子。） AI 甚至会让患者能够进行基本的分流，获取如何处理健康问题的建议，并决定是否需要寻求治疗。
在贫穷国家使用的 AI 模型需要针对不同的疾病进行训练，而不是针对富裕国家进行的。它们需要使用不同的语言，并考虑到不同的挑战，例如远离诊所的患者或患者无法因生病而停止工作。
人们需要看到 AI 对整体医疗保健有益，尽管它们不会是完美的，会犯错。AI 必须经过非常仔细的测试和适当的监管，这意味着它们的采用速度比其他领域要慢。但是人类也会犯错误。而没有医疗保健也是一个问题。
除了帮助医疗保健，AI 还将大大加速医学突破的速度。生物学数据非常大，对于复杂的生物系统的所有工作方式，人类很难跟上。已经有软件可以查看这些数据，推断出路径、搜索病原体上的目标，然后设计药物。有些公司正在研究用这种方式开发癌症药物。
下一代工具将更加高效，并能够预测副作用并确定剂量水平。盖茨基金会在 AI 中的一个优先事项是确保这些工具用于影响世界上最贫穷的人们的健康问题，包括艾滋病、结核病和疟疾。
同样地，政府和慈善组织应该创造激励机制，鼓励公司分享人工智能生成的有关穷国农作物或牲畜的见解。人工智能可以根据当地的条件开发更好的种子，根据当地的土壤和气候为农民提供种植最佳种子的建议，并帮助开发牲畜的药物和疫苗。随着极端天气和气候变化对低收入国家的自给自足农民造成越来越大的压力，这些进步变得更加重要。
03
教育
电脑并没有像我们这个行业内的许多人所希望的那样对教育产生影响。虽然有一些好的发展，包括教育游戏和在线信息来源，如维基百科，但它们对学生成就的任何度量指标都没有产生有意义的影响。
但我认为，在未来5到10年内，由人工智能驱动的软件将最终实现革命性地改变人们教学和学习的方式。它将知道你的兴趣和学习风格，因此可以量身定制内容，以保持你的参与度。它将测量你的理解程度，注意你何时失去兴趣，并了解你喜欢的动机类型。它将提供即时反馈。
AI可以协助教师和管理人员的方式有很多，包括评估学生对一个学科的理解并为他们提供职业规划建议。教师已经在使用像ChatGPT这样的工具来提供对学生写作任务的评论。
当然，AI在能够做到理解某个学生最佳的学习方式或他们的动机方面需要大量的培训和进一步的发展。即使一旦技术得到完善，学习仍将取决于学生和教师之间良好的关系。它将增强 - 但永远不会取代 - 学生和教师在课堂上共同进行的工作。
新的工具将会为有经济能力购买它们的学校创建，但我们需要确保它们也会被创建并提供给美国和全球低收入学校使用。AIs需要接受各种各样的数据集的训练，以便它们是无偏的，并反映了它们将被使用的不同文化。数字鸿沟也需要得到解决，以免低收入家庭的学生被落下。
我知道很多老师担心学生在使用GPT来写作文。教育工作者已经开始讨论如何适应这项新技术，我猜这些讨论还将持续一段时间。我听说过一些老师已经找到了聪明的方法来将这项技术融入他们的工作中，例如允许学生使用GPT创建第一稿，并将其个性化。
04
风险和人工智能的问题
你可能已经读过关于当前人工智能模型存在问题的报道。例如，它们不一定擅长理解人类请求的上下文，导致一些奇怪的结果。当你要求AI编造一些虚构的事情时，它可以很好地完成。但是当你要求它给你旅行建议时，它可能会建议一些不存在的酒店。这是因为AI不足以了解你请求的上下文，以便知道它是否应该编造虚假酒店，还是只告诉你有空房的真实酒店。
还有其他问题，例如AI因为难以理解抽象推理而给出错误的数学问题答案。但这些都不是人工智能的根本局限性。开发人员正在解决这些问题，我认为我们将很快看到它们被大部分解决，可能在不到两年的时间内。
其他问题不仅仅是技术问题。例如，使用AI的人类可能会构成威胁。像大多数发明一样，人工智能可以用于善良的目的或恶意的目的。政府需要与私营部门合作，限制风险。
还有可能出现AI失控的情况。机器会否决定人类是威胁，得出结论其利益与我们不同，或者只是不再关心我们？可能会，但这个问题今天并不比过去几个月的AI发展更紧迫。
超级智能人工智能（AGI）将出现在我们的未来。与计算机相比，我们的大脑运作速度极慢：大脑中的电信号速度是硅芯片信号速度的1/100,000。一旦开发者能够概括一个学习算法并以计算机速度运行它——这可能需要十年或一百年——我们就会拥有一个极其强大的AGI。它将能够做到人脑可以做到的一切，但不受记忆容量和操作速度的实际限制。这将是一种深刻的变革。
这些被称为“强AI”的人工智能可能能够确立自己的目标。那些目标会是什么？如果它们与人类的利益冲突会发生什么？我们应该试图阻止强人工智能的发展吗？这些问题将随着时间的推移变得更加紧迫。
但是，过去几个月的突破并没有使我们距离强AI实质上更接近。人工智能仍然无法控制物理世界，也不能确立自己的目标。最近有一篇关于与ChatGPT交谈的《纽约时报》文章引起了很多关注，其中ChatGPT表示它想成为人类。这是一个有趣的观察，表达了该模型情感上的人类特点，但它不是有意义的独立指标。
三本书塑造了我自己对这个问题的思考：Nick Bostrom的《超级智能》，Max Tegmark的《生命3.0》和Jeff Hawkins的《一千个大脑》。我不完全同意这些作者的观点，他们也不互相认同。但是这三本书都写得很好，引人深思。
05
下一个前沿领域
未来将会有大量公司致力于开发新的 AI 应用以及改进技术本身。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。其中一些芯片使用光学开关——实质上是激光器——以减少能量消耗并降低制造成本。理想情况下，创新型芯片将允许您在自己的设备上运行 AI，而不像今天一样在云端运行。
在软件方面，驱动 AI 学习的算法将变得更好。在某些领域（例如销售），开发人员可以通过限制 AI 工作的范围并给它们提供特定于该领域的大量训练数据，使其变得非常准确。但一个重要的未解决问题是，我们是否需要为不同的用途开发许多这些专门的 AI——比如一个用于教育，另一个用于办公室生产力——或者是否可能开发出一种人工智能通用型，可以学习任何任务。在这两种方法上将会有巨大的竞争。
不管怎样，AI 的话题将在可预见的未来占据公众讨论的中心。我想建议三个原则来引导这个讨论。
首先，我们应该尝试平衡关于 AI 的不良影响的担忧——这是可以理解和有效的——与其改善人们生活的能力。为了最大程度地利用这项卓越的新技术，我们需要在抵御风险和将利益扩展到尽可能多的人之间取得平衡。
其次，市场力量不会自然产生帮助最贫困人口的 AI 产品和服务。相反，更可能的是相反的情况。通过可靠的资金和正确的政策，政府和慈善组织可以确保利用 AI 减少不平等。就像世界需要其最聪明的人关注其最大的问题一样，我们需要将世界上最好的 AI 集中在解决最大问题上。
虽然我们不应该等待这种情况的发生，但思考人工智能是否会识别不平等并尝试减少它是有趣的。在看到不平等时，你需要有一种道德意识，还是一台纯粹的理性人工智能也能看到它？如果它确实认识到不平等，它会建议我们采取什么行动？
最后，我们应该记住，我们只是在人工智能可以实现的开始阶段。无论它今天有什么限制，它都将在我们不知不觉中被消除。
我很幸运参与了个人电脑革命和互联网革命。我对此时此刻同样感到兴奋。这种新技术可以帮助世界各地的人们改善生活。同时，世界需要确立规则，以使人工智能的任何不利因素远远超过其好处，并使每个人都能享受到这些好处，无论他们住在哪里或拥有多少钱。人工智能时代充满了机遇和责任。
原文连接：
https://www.gatesnotes.com/The-Age-of-AI-Has-Begun
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The Age of AI has begun
In my lifetime, I’ve seen two demonstrations of technology that struck me as revolutionary.
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.
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.
I thought the challenge would keep them busy for two or three years. They finished it in just a few months.
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.
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.
I knew I had just seen the most important advance in technology since the graphical user interface.
This inspired me to think about all the things that AI can achieve in the next five to 10 years.
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.
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.
I’ve been thinking a lot about how AI can reduce some of the world’s worst inequities.
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.
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.
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.
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.
Defining artificial intelligence
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.
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.
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.
Productivity enhancement
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.
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.
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.)
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.
Advances in AI will enable the creation of a personal agent.
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?
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.
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.
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.
Health
I see several ways in which AIs will improve health care and the medical field.
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.
Other AI-driven improvements will be especially important for poor countries, where the vast majority of under-5 deaths happen.
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.
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.
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.
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.
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.
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.
Education
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.
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.
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.
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.
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.
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.
Risks and problems with AI
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.
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.
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.
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.
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.
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.
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.
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.
The next frontiers
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.
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.
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.
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.
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?
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.
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.
It is true that the age of AI has begun
本帖最后由 超新星 于 2023-3-30 09:19 编辑It is true that the age of AI has begun. But most of the human will be dependent on AI and stop thinking more of anything.
And it gradually reduce the ability of human intelligence..
The only thing I have to add to the views already expressed is that blind optimism in technology, of the "intelligent" variety or otherwise, isn't going to save humanity from our own ignorance. Everyone blames hate for violence, and greed for political and financial corruption, but who are the people that are greedy, and who are the ones that hate? Is it you, is it me, or someone else? Finally, do you not know, have you not heard, God has a plan for all of humanity, and you, Mr. Gates, are part of it.
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