Here’s why that is no bad thing

这就是为什么这不是一件坏事

After decades of blue-collar jobs being snatched up by machines, advanced chatbots are now breathing down white collars. “Generative” artificial-intelligence (ai) tools, such as ChatGPT, have made significant progress in crafting human-sounding language and grasping context. So much so that they have leapfrogged humans in some tasks. This could make as many as 300m jobs redundant globally, according to Goldman Sachs, a bank.

经过几十年的蓝领工作被机器夺走后，先进的聊天机器人现在正在威胁到白领。像ChatGPT这样的“生成式”人工智能（AI）工具，在塑造类似于人类语言和理解上已经取得了重大进展。以至于它们在某些任务中已经超越了人类。根据高盛银行（Goldman Sachs）的说法，这可能会使全球多达3亿个就业岗位变得多余。

A recent study by OpenAI, the startup that created ChatGPT, looked at the potential for automation across 1,016 occupations. Humans and AI separately rated how well software powered by large-language models (llms), which are trained on vast chunks of the internet and then fine-tuned to specific functions, could undertake 19,000 tasks involved in the jobs. 创建ChatGPT的初创公司OpenAI最近的一项研究研究了1,016个职业的自动化潜力。人类和人工智能分别评估了由大型语言模型（llms）驱动的软件的性能，这些软件在互联网上进行了大量训练，然后根据特定功能进行了微调，可以承担19000项工作中涉及的任务。

If the software, such as OpenAI’s GPT-4, was deemed able to reduce the time it takes humans to complete the task by at least half, without a drop in quality, the task was considered ripe for AI replacement (a score of one meant that the whole occupation could be done in half the time).

如果像OpenAI的GPT-4这样的软件被认为能够将人类完成任务所需的时间减少至少一半，而不会降低质量，则该任务被视为适合由人工智能取代（得分为1表示整个职业可以在一半时间内完成）。

For other tasks the annotators imagined additional software that could be added to the model, such as computer tools that can automatically pull fresh data from the internet. They found that 80% of Americans could have at least 10% of their work tasks done by advanced AI tools.

对于其他任务，注释者们设想了可以添加到模型中的额外软件，比如可以自动从互联网上获取新数据的计算机工具。他们发现，80%的美国人可以通过先进的人工智能工具完成至少10%的工作任务。

The figure rises to 50% of tasks for an estimated 19% of workers.

这一数字上升到50%的任务，估计有19%的工人。

Most exposed are industries which rely on programming and writing skills.

最容易受到影响的是依赖编程和写作技能的行业。*

That echoes another study, published on March 1st by academics in America, which found that the industries most at risk of a shake-up were legal services and some areas of the financial and insurance industries.

这与美国学者3月1日发表的另一项研究相呼应，该研究发现，最有可能发生重组的行业是法律的服务业和金融保险业的某些领域。

They point to telemarketers as the occupation most likely to be made redundant. Teachers, especially those of languages, literature and history, are next on the list.

他们指出，电话推销员是最有可能被裁员的职业。教师，尤其是语言、文学和历史教师，排在第二位。

What is striking in both studies is that, unlike past breakthroughs in machine learning, it is skilled and high-paying jobs that are most exposed.

这两项研究中引人注目的是，与过去机器学习的突破不同，技术和高薪工作暴露最多。

This automation should not be feared. It could unshackle workers from mundane tasks and unleash greater labour productivity, which would be a boon for drum-tight labour markets in advanced economies. A study by Goldman Sachs, published on April 5th, suggests that generative AI could grow global gdp by 7% in the next decade.

这种自动化不应该被害怕。它可以使工人摆脱单调的任务，释放更大的劳动生产力，这对于先进经济体中紧缩的劳动力市场将是一个福音。高盛4月5日发布的一项研究表明，生成式人工智能在未来十年内可能会增加全球GDP 7%。

But studies like this may overstate the potential for automation. The annotators responsible for mapping overlaps between llms and human capabilities may omit some tacit skills in professions they know less about. Human qualities essential for some jobs, such as empathy or charisma, will be overlooked.

但像这样的研究可能夸大了自动化的潜力。负责映射llms和人类能力之间重叠的注释者可能会忽略一些他们不太了解的职业中的隐性技能。 对某些工作至关重要的人类品质，如同情心或魅力，将被忽视。

And not all tasks capable of being carried out by AI should be: Vanderbilt University in Tennessee had to apologise for using ChatGPT to write a condolence email to students after a shooting at another American university.

并非所有能够由AI执行的任务都应该是：田纳西州的范德比尔特大学不得不为在另一所美国大学发生枪击案后使用ChatGPT给学生写慰问电子邮件而道歉。

Many businesses may also lack the IT architecture or inclination to accommodate AI innovations. And those who embrace it will face practical and legal quandaries. When chatbots do not know what to say, they often fib (though so can humans).

许多企业也可能缺乏IT架构或倾向于适应人工智能创新。而那些拥护它的人将面临实际和法律的上的困境。当聊天机器人不知道该说什么时，他们经常撒谎（尽管人类也可以）。

The “creative” output they generate is based on a mashup of data sourced from the internet, raising thorny issues around accuracy, privacy and intellectual property. For all their conversational panache, in the real world, AI tools will still need handlers. That may even end up creating new jobs.

他们产生的“创造性”输出是基于来自互联网的数据混搭，这引发了围绕准确性，隐私和知识产权的棘手问题。在真实的世界中，人工智能工具仍然需要处理程序。这甚至可能最终创造新的就业机会。