人工智能不是人的敌人-联通智能客服 转人工

原文标题：

How to worry wisely about AI

Rapid progress in AI is arousing fear as well as excitement. How concerned should you be?

如何明智地看待人工智能

人工智能的迅猛发展既带来了兴奋，也引发了担忧。你应该有多担忧呢？

Technology and society

科技与社会

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“SHOULD WE AUTOMATE away all the jobs, including the fulfilling ones? Should we develop non-human minds that might eventually outnumber, outsmart...and replace us? Should we risk loss of control of our civilisation?”

“我们是否应该将所有的工作都自动化，包括有意义的工作？我们是否应该开发那些最终超过、胜过...并取代我们的非人类大脑？我们是否有失去人类文明的风险？"

These questions were asked last month in an open letter from the Future of Life Institute, an NGO.

上个月，非政府组织“未来生命研究所”在一封公开信中提出了这些问题。

It called for a six-month “pause” in the creation of the most advanced forms of artificial intelligence (AI), and was signed by tech luminaries including Elon Musk.

它呼吁在创造最先进的人工智能方面“暂停”6个月，公开信由埃隆.马斯克等多位科技名人签署。

It is the most prominent example yet of how rapid progress in AI has sparked anxiety about the potential dangers of the technology.

这是迄今为止最突出的例子，说明人工智能的快速发展已经引发了对该技术潜在危险的担忧。

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In particular, new “large language models” (LLMs)—the sort that powers ChatGPT, a chatbot made by OpenAI, a startup—have surprised even their creators with their unexpected talents as they have been scaled up.

特别是，新的“大型语言模型”(LLM)——为初创公司 OpenAI 开发的聊天机器人 ChatGPT 提供动力的那种——在规模扩大时以其意想不到的才能让其创造者感到惊讶。

Such “emergent” abilities include everything from solving logic puzzles and writing computer code to identifying films from plot summaries written in emoji.

这种“新兴”能力包括解决逻辑难题的能力、编写计算机代码的能力、从表情包的情节摘要中识别电影的能力。

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These models stand to transform humans’ relationship with computers, knowledge and even with themselves.

这些模型将改变人类与计算机、知识、甚至与人类自身的关系。

Proponents of AI argue for its potential to solve big problems by developing new drugs, designing new materials to help fight climate change, or untangling the complexities of fusion power.

人工智能的支持者认为它有解决重大问题的潜力，如开发新药、设计新材料以帮助应对气候变化、解开核聚变发电的复杂问题。

To others, the fact that AIs’ capabilities are already outrunning their creators’ understanding risks bringing to life the science-fiction disaster scenario of the machine that outsmarts its inventor, often with fatal consequences.

反对者认为，人工智能的能力已经超过了其创造者的理解力，这有可能使科幻片中机器胜过其发明者的灾难场景成为现实，通常会带来致命的后果。

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This bubbling mixture of excitement and fear makes it hard to weigh the opportunities and risks.

这种兴奋和恐惧的混合体使我们难以权衡机会和风险。

But lessons can be learned from other industries, and from past technological shifts.

但是可以从其他行业及曾经的技术变革中吸取教训。

So what has changed to make AI so much more capable? How scared should you be? And what should governments do?

那么是什么样的改变让 AI 变得如此强大？你应该有多恐惧呢？政府应该做什么呢？

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In a special Science section, we explore the workings of LLMs and their future direction.

在特别的科学章节中，我们研究了大型语言模型的工作原理及其未来方向。

The first wave of modern AI systems, which emerged a decade ago, relied on carefully labelled training data.

10年前出现的第一波现代AI系统，依靠的是精心标记的训练数据。

Once exposed to a sufficient number of labelled examples, they could learn to do things like recognise images or transcribe speech.

一旦接触到足够数量的标记实例，它们就能学会做一些事情，比如识别图像或转录语音。

Today’s systems do not require pre-labelling, and as a result can be trained using much larger data sets taken from online sources.

如今的AI系统不需要预先标记，因此可以使用在线资源里的大规模数据集进行训练。

LLMs can, in effect, be trained on the entire internet—which explains their capabilities, good and bad.

实际上人工智能不是人的敌人，大型语言模型可以在整个互联网上进行训练——这就是他们为什么如此强大的原因，有好有坏。

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Those capabilities became apparent to a wider public when ChatGPT was released in November. A million people had used it within a week; 100m within two months.

当ChatGPT在11月发布时，大众对这种能力的认可也显而易见。一周内有100万人使用；两个月内有1亿用户。

It was soon being used to generate school essays and wedding speeches.

它很快就被用于生成学校论文和婚礼演讲稿等方面。

ChatGPT’s popularity, and Microsoft’s move to incorporate it into Bing, its search engine, prompted rival firms to release chatbots too.

ChatGPT的流行以及微软将其整合到其搜索引擎“必应”的举措，促使竞争对手公司也发布了聊天机器人。

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Some of these produced strange results. Bing Chat suggested to a journalist that he should leave his wife.

其中有些AI生成了奇怪的结果。必应聊天机器人建议记者应该离开他的妻子。

ChatGPT has been accused of defamation by a law professor. LLMs produce answers that have the patina of truth, but often contain factual errors or outright fabrications.

ChatGPT被一名法学教授指控为诽谤。大型语言模型产生的答案看起来具有真实的外衣，但实际上经常包含与事实不相符或完全胡编乱造的内容。

Even so, Microsoft, Google and other tech firms have begun to incorporate LLMs into their products, to help users create documents and perform other tasks.

即便如此，微软、谷歌和其他科技公司已经开始将大型语言模型整合到他们的产品，以帮助用户创建文档和执行其他任务。

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The recent acceleration in both the power and visibility of AI systems, and growing awareness of their abilities and defects, have raised fears that the technology is now advancing so quickly that it cannot be safely controlled.

最近，AI系统的算力和知名度都在加速发展，人们对其能力和缺陷的认识也在不断提高，这引发了人们对该技术发展如此之快以至于无法安全控制的担忧。

Hence the call for a pause, and growing concern that AI could threaten not just jobs, factual accuracy and reputations, but the existence of humanity itself.

因此人们呼吁暂停，而且人们越来越担心人工智能不仅会威胁到工作、事实的准确性和声誉，还会威胁到人类自身的生存。

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Extinction? Rebellion?

灭亡？叛乱？

The fear that machines will steal jobs is centuries old. But so far new technology has created new jobs to replace the ones it has destroyed.

人们对机器会抢走工作的担忧由来已久。但到目前为止，新技术已经创造了新的工作岗位，以取代它所破坏的工作。

Machines tend to be able to perform some tasks, not others, increasing demand for people who can do the jobs machines cannot.

机器往往能够完成一些任务，而不能完成一些其他任务，这增加了人们对于那些机器无法胜任工作的需求。

Could this time be different? A sudden dislocation in job markets cannot be ruled out, even if so far there is no sign of one.

这次会有所不同吗？尽管到目前为止就业市场还没有出现突然混乱的迹象，但不能排除这种情况的可能性。

Previous technology has tended to replace unskilled tasks, but LLMs can perform some white-collar tasks, such as summarising documents and writing code.

以前的科技倾向于取代体力工作，但大型语言模型可以做一些脑力工作，例如总结文件和编写代码。

（恭喜读完，本篇英语词汇量709/1406左右）

原文出自：2023年4月22日《The Economist》Leaders版块。

精读笔记来源于：自由英语之路

本文翻译整理: Irene

本文编辑校对: Irene

仅供个人英语学习交流使用。

【补充资料】（来自于网络）

Future of Life Institute（未来生命研究所）是一个非营利组织，成立于2014年，总部位于美国马萨诸塞州剑桥市。其使命是通过推动智能、机器人和其他新兴技术的研究和发展，确保这些技术对人类和全球环境的长期利益产生积极影响。该机构由一群科学家和企业家共同创立，包括物理学家Max Tegmark、Elon Musk等知名人士。该机构致力于推进相关领域的研究，制定政策和道德准则，以确保人工智能和相关技术的安全性、透明度和可控性，并在公众中提高对这些新兴技术的认知度和理解。

大型语言模型（Large Language Model）是一种基于深度学习的自然语言处理技术。它是由大规模文本数据集训练出来的能够生成自然语言文本的模型。这些模型可以接受一个输入，并根据其内部权重和结构产生一个输出结果，通常是一段人类可读的文本。目前最知名的大型语言模型之一是OpenAI的GPT系列模型（Generative Pre-trained Transformer）。GPT模型以Transformer架构为基础，通过预训练数据来学习语言模型。在预训练中，模型被暴露给大量的文本数据，从而学习到单词和短语之间的关系人工智能不是人的敌人，以及语言的其他特征。然后，通过对任务特定的微调，例如生成文本、问答或机器翻译等，GPT模型可以产生高质量的自然语言文本，并在多个领域取得了令人印象深刻的成果。

【重点句子】（3个）

It is the most prominent example yet of how rapid progress in AI has sparked anxiety about the potential dangers of the technology.

这是迄今为止最突出的例子，说明人工智能的快速发展已经引发了对该技术潜在危险的担忧。

These models stand to transform humans’ relationship with computers, knowledge and even with themselves.

这些模型将改变人类与计算机、知识、甚至与人类自身的关系。

The fear that machines will steal jobs is centuries old. But so far new technology has created new jobs to replace the ones it has destroyed.

人们对机器会抢走工作的担忧由来已久。但到目前为止，新技术已经创造了新的工作岗位，以取代它所破坏的工作。

自由英语之路