One way to think about AI note-takers is as a productivity tool for humans. You might be unable to attend a gathering, but you can still find out what happened by reading a summary later. You can receive a set of specific action points rather than operating on the vague assumption that Doris will follow up on something or other.

我们可以把AI笔记功能看作是帮人类提高效率的工具。 你可能无法亲自去开会，但是之后通过阅读会议总结，你仍然可以了解发生了什么。 你可以收到一套具体的行动要点，而不是基于“多丽丝会跟进这件事”的模糊假设来做事。

But another way to think about AI note-takers is as a data-gathering exercise for other machines. Transcripts can be scoured for previously unseen patterns: how much individuals are contributing; where coaching is needed. And as offhand remarks are turned into permanent records, more employee communication becomes available as training material for AI models.

但是我们还可以把AI笔记功能看作是为其他机器收集数据的活动。 机器可以搜索语音转录文本，找出此前未被看到的规律：每个人的贡献有多少，哪些地方需要辅导。 由于随口说出的话变为永久记录，越来越多的员工沟通内容可用作AI模型的训练材料。

The idea that the sorts of conversations you are having with your colleagues could pave the path to superintelligence may seem laughable. But consider the court battle in America over Google's purchase of data from Spirit Airlines, a bankrupt low-cost carrier. The tech giant bid $10m to get hold of Spirit's data, including 100m email messages and 500m Teams titbits. Buying Spirit's data gives a model-maker such as Google not just aviation-specific information on pricing and fuel costs, but also more general training data on negotiations, strategy and more. This kind of material is not generally available on the wider internet. "Reddit threads are not a good way to learn how to run a business," says Greg Ewing of Spencer Fane, a law firm.

你与同事的这些对话竟可能为超级智能铺平道路，这种想法或许显得可笑。 但是请想一想美国那场关于谷歌购买精神航空公司（已破产廉航公司）数据的法庭之争。 谷歌出价1000万美元购买精神航空公司的数据，其中包括1亿封电子邮件和5亿条Teams聊天记录。 购买精神航空公司的数据，能让像谷歌这样的AI模型开发者不仅获得航空领域特有的定价和燃油成本等信息，还能获得关于谈判、策略等更通用的训练数据。 这种材料在一般的互联网上通常找不到。 比如斯宾塞·法恩律师事务所的格雷格·尤因就表示：“Reddit论坛帖子并不是关于企业经营的好数据。”

The Google/Spirit transaction is being challenged by, among others, a rival bidder called Micro1, which also fancies getting its hands on the airline's data, and Springshot, a software firm that reckons its intellectual property is being sold on. But it is also being challenged by a trade union representing Spirit flight attendants, which argues that the deal includes confidential employee data. (The next court hearing is due to take place on October 14th.)

谷歌与精神航空公司的交易受到多方反对，其中包括一个名为Micro1的竞争出价方（该公司同样渴望获得这家航空公司的数据），以及一家名为Springshot的软件公司（该公司认为其知识产权正在被出售）。 但是该交易也受到了代表精神航空公司空乘人员的工会的反对，该工会认为，该交易包含机密员工数据。 （下次法庭听证会定于10月14日举行。）

If Spirit had been a European airline, says Jeremias Adams-Prassl, a law professor at Oxford University, this transaction would already have run into big privacy-related obstacles. Under GDPR, a European data-protection law, data collected for one reason cannot then be used for a different one, a concept known as "purpose limitation". That makes it difficult to train AI models on employee correspondence whose original purpose was to help an airline perform better. Expectations of employee privacy are baked into wider European law, too. In 2017 the European Court of Human Rights considered the case of Bogdan Barbulescu, a Romanian sales engineer sacked after his employer had downloaded correspondence from an instant-messaging account, including some "of an intimate nature". Mr Barbulescu had signed forms agreeing that the account was for work purposes, and flatly denied using it for personal reasons. Even so, in a precedent-setting judgment, the court concluded that "an employer's instructions cannot reduce private social life in the workplace to zero."

牛津大学法学教授耶利米亚斯·亚当斯-普拉斯尔表示，如果精神航空是一家欧洲航空公司，这笔交易早就遭遇重大隐私相关障碍了。 根据《通用数据保护条例》（欧洲数据保护法律），为某一目的而收集的数据不得再用于其他目的，这一概念被称为“目的限制”。 这使得很难用员工往来对话来训练AI模型，因为这些往来对话的最初目的就是帮助提升航空公司的表现。 对员工隐私的保护也内嵌在更宽泛的欧洲法律之中。 2017年，欧洲人权法院审理了博格丹·巴尔布列斯库一案，巴尔布列斯库是一名罗马尼亚销售工程师，其雇主从即时通讯账户中下载了他的聊天记录，发现其中包括一些“私密内容”，随后以此为由将巴尔布列斯库解雇。 巴尔布列斯库当初签署了表格，同意该账户仅用于工作目的，他也断然否认曾将账户用于私人事务。 即便如此，在这起作为判例的审判中，法庭得出结论：“雇主的命令无法将工作场所的私人社交生活降至零。”

Some might smirk at this. While Europeans assert their fundamental human right to send intimate messages to each other at work, American frontier labs are acquiring more internal data and stretching their lead. But even if the legal environment is more permissive across the Atlantic, turning employee interactions into AI feedstock imposes other costs. Lawyers warn, for example, that AI meeting transcripts greatly expand the amount of material that is discoverable in litigation. Wherever they are based, employees tend not to warm to the idea of being monitored. Meta, for example, suffered a well-publicised internal backlash earlier this year when it tried to roll out a programme that recorded employees' mouse clicks and keystrokes. "The argument that privacy and competitiveness are in conflict is too simple," says Mr Adams-Prassl.

有些人可能会对这个判决感到洋洋得意。 欧洲人坚决维护自己在工作中互发私密信息的基本人权，而美国前沿实验室却在获取更多内部数据，并不断扩大领先优势。 但是即便欧洲的法律环境更为宽松，将员工互动记录转化为AI训练素材也会带来其他代价。 例如，律师们警告说，AI会议记录会大幅增加在诉讼中可被找到的资料。 员工无论身处何地，往往都不太喜欢自己的聊天被监控。 例如，Meta试图启动一项计划，记录员工的鼠标点击和键盘敲击，并因此在今年早些时候遭到内部员工的强烈抨击，这次抨击被广为报道。 “隐私与竞争力之间存在冲突，这个论点过于简单。”亚当斯-普拉斯尔表示。

AI is nonetheless likely to change the way employees behave. At the moment workplace communication is a melange of private and professional messages. Even people at the top don't necessarily distinguish between work and personal life: one tech boss recalls being given access to a client's data and finding a CEO's passwords in a Word document. But if people assume internal corporate data are going to train smarter models, outlasting even the firms in which they were generated, employees will become more guarded. The workplace will be more professional, and more dull.

然而，AI仍有可能改变员工的行为方式。 目前，职场沟通是私人信息与专业信息的混合体。 即使是高级领导也不一定区分工作和个人生活：一位科技公司老板回忆说，他曾获准访问一位客户的数据，并在Word文档中发现了某位CEO的密码。 但是如果人们认为企业内部数据将被用于训练更智能的模型，而且模型甚至比生成这些数据的公司能存续更久，那么员工们就会变得更加警惕。 到那时，职场将变得更加专业化，也更加沉闷乏味。