用AI会变笨?|外刊

Business 板块

AI and the danger of cognitive surrender

AI及认知投降

【讲解视频】

【原文音频】

后台回复【思考】领取 注释版+原文音频

Calculators didn’t make everyone innumerate. GPS navigation systems made driving easier. In any conversation about the cognitive effects of artificial intelligence, these two earlier technologies are reasonably likely to come up. Each is a useful entry-point into two big questions. How might AI change the way people think, and should managers do anything in response?

计算器并没有让所有人变成不会算数的人，GPS导航系统让驾驶变得更容易。在任何关于人工智能对认知影响的讨论中，这两种早期技术都很可能被提及。它们分别是进入两个重大问题的切入点：人工智能会如何改变人类的思维方式，以及管理者是否应该对此采取行动。

Using calculators and GPS devices are examples of “cognitive offloading”—a deliberate decision to delegate a specific task to technology. In both cases, it has been worth it. Calculators improve students’ mathematical performance, helping to build problem-solving skills and self-confidence. GPS means drivers no longer have to pull over and faff about with maps. It’s harder to get completely lost; it’s easier to avoid terrible traffic.

用计算器和GPS设备是“卸载认知”的例子，也就是有意识地把某项具体任务交给技术来完成。在这两种情况下，这种做法都是值得的。计算器可以提升学生的数学表现，同时有助于培养问题解决能力和自信心。GPS意味着司机不再需要靠边停车然后对着地图一顿瞎折腾。人们很难完全迷路，也更容易避开糟糕的交通状况。

The use of GPS navigation devices can also sap people’s ability to think for themselves. A study conducted by Louisa Dahmani of Harvard Medical School and Véronique Bohbot of McGill University found that greater lifetime use of GPS by drivers was associated with worse spatial memory. Other research shows that pedestrians whonavigate with their phones take longer routes and make more stops than physical-map users. A similar pattern is also visible in online search. Using the internet to look up information is clearly efficient, but there are trade-offs. The “Google effect” refers to a research finding that people have worse recall of information they expect to be able to find online.

用GPS导航设备也会削弱人们独立思考的能力。哈佛医学院的Louisa Dahmani和麦吉尔大学的Véronique Bohbot进行的一项研究发现，司机用GPS越多，他们的空间记忆能力就越差。其他研究表明，用手机导航的人相比用纸质地图的人，走的路线更长、停顿次数更多。类似的现象也出现在在线搜索中。用互联网查找信息显然是高效的，但这也伴随着权衡。“谷歌效应”指的是一项研究发现：人们对于那些他们认为可以在网上轻易找到的信息，记忆反而更差。

AI supercharges these trade-offs. Handing specific tasks to models will often make sense: they are much better than humans at many things. But AI’s range of capabilities, allied to a convenient conversational interface and a seductively confident persona, raises the prospect less of delegation than of wholesale capitulation. Hence “cognitive surrender”, a term coined by Steven Shaw of the Wharton School of the University of Pennsylvania in a recent paper written with his colleague, Gideon Nave.

人工智能将这些权衡放大了。把具体任务交给AI是合理的，因为AI在很多方面都比人类更擅长。但人工智能广泛的能力，再加上便捷的对话式界面以及一种极具迷惑性的自信人设，使得这种情况与其说是任务委托，不如说更像是全面投降。因此就有了“认知投降”这一说法，这是宾夕法尼亚大学沃顿商学院的Steven Shaw与同事Gideon Nave在近期论文中提出的一个术语。

Messrs Shaw and Nave asked volunteers to answer demanding questions with the assistance of AI, and a little like Mr LaCour’s calculator experiment, randomly introduced errors into the machine’s answers. When the model gave accurate responses, the people using it outperformed a control group of people relying on their own brainpower. When the AI gave the wrong answers, the people using it did much worse than the control group. In other words, people stopped thinking for themselves. At the moment bosses are more focused on getting employees to use AI than fussing about its effects on how they think. But most employers also value critical thinking: models are still prone to embarrassing errors, for one thing, and novel situations require skilled humans to step in. So it is worth asking what managers can do to encourage cognitive resistance.

Shaw和Nave让志愿者在人工智能的辅助下回答高难度问题，并且有点类似于LaCour的计算器实验，他们随机在机器的答案中加入错误。当AI给出正确答案时，使用它的人表现优于依靠自身思考能力的对照组；而当AI给出错误答案时，使用它的人表现反而比对照组差得多。换句话说，人们停止了独立思考。目前，老板们更关注让员工使用AI，而不是过多担心它对思维方式的影响。但大多数雇主仍然重视批判性思维：一方面，AI仍然容易出现令人尴尬的错误；另一方面，在新情况中仍然需要有经验的人类介入。因此，值得思考的是，管理者可以做些什么来鼓励认知上的抵抗。

They can deliberately hire workers who enjoy thinking. People with high “need for cognition” (yes, dear reader, that means you) are somewhat, though not entirely, protected against the risk of cognitive surrender, says Mr Shaw. Incentives and feedback can help, too. One of the experiments in his paper introduced monetary rewards for getting things right, and also notified participants during the test whether an item had been answered correctly or not. These techniques encouraged AI users who were being fed the wrong answers to override the model more (though they still did worse than people who relied on their own judgment).

管理者可以有意识地招聘那些喜欢思考的员工。Shaw表示，具有较高“认知需求”的人（是的，亲爱的读者，说的就是你）在一定程度上（虽然并非完全）能够抵御认知投降的风险。激励和反馈同样有帮助。他论文中的一项实验为答对问题设置了金钱奖励，并在测试过程中告知参与者答案是否正确。这些方法促使那些被错误答案误导的AI使用者更频繁地去质疑和推翻模型（尽管他们的表现仍然不如依赖自身判断的人）。

Engineering AI-free periods may have value, too. Another recent study, by Stefanos Poulidis of INSEAD and his co-authors, recruited over 200 chess-club students to train on an AI-assisted platform. Some of the students were automatically given AI tips at a limited number of specific moments; others could click a button at any time to get advice. The students who had on-demand access achieved less than half the performance gains of those who had no say over when they got help. Offloading is fine. Giving up is another matter.

有意识地安排一些不用AI的时间或许也是有价值的。另一项最新研究由INSEAD的Stefanos Poulidis及其同事开展，他们招募了200多名国际象棋俱乐部的学生，在一个AI辅助平台上进行训练。其中一些学生会在特定且有限的时刻自动获得AI提示，而另一些学生则可以随时点击按钮获取建议。结果显示，那些可以随时获取帮助的学生，表现的提升还不到那些无法决定何时获得帮助的学生的一半。适度的认知外包是可以的，但彻底放弃思考就是另一回事了。

交流英语欢迎戳👇