Your brain on AI

当大脑遇上人工智能

Many people find AI-based chatbots helpful in keeping up with news, but a study by Pattie Maes and her colleagues at the MIT Media Lab points to a big problem with this strategy. 许多人发现基于人工智能的聊天机器人有助于跟进新闻，但麻省理工学院媒体实验室（MIT Media Lab）的帕蒂·梅斯（Pattie Maes）及其同事进行的一项研究指出，这种策略存在一个重大问题。

Participants who evaluated paired news headlines and images over the course of four weeks were initially 21% percent more accurate at telling fake news from real when aided by a chatbot—but by week four, they’d become 15% worse at identifying fake news without AI than they were before (though roughly a quarter of them reported feeling better at it). 在为期四周的时间里，参与者对成对的新闻标题和图片进行了评估。在聊天机器人的辅助下，他们最初辨别真假新闻的准确率提高了 21%；但到了第四周，他们在没有人工智能辅助的情况下，辨别假新闻的能力比之前下降了 15%（尽管约有四分之一的参与者表示感觉自己辨别能力变强了）。

The result reflects an “AI dependency paradox” that has been observed in other domains, including medicine. 这一结果反映了在包括医学在内的其他领域中也观察到的“人工智能依赖悖论”。

“Users get excited about these ‘magical’ LLMs but forget that they’re just statistical models that predict the next ‘token’ in a sequence,” says Anku Rani, a PhD student in media arts and sciences and one of the lead authors of the study, along with fellow MAS PhD student Valdemar Danry, SM ’23. “用户对这些‘神奇’的大语言模型（LLM）感到兴奋，却忘记了它们仅仅是预测序列中下一个‘标记’（token）的统计模型，”媒体艺术与科学专业的博士生安库·拉尼（Anku Rani）说道。她是这项研究的主要作者之一，另一位主要作者是同为媒体艺术与科学专业博士生的瓦尔德马·丹里（Valdemar Danry，2023届理学硕士）。

The researchers also found, however, that certain AI styles were associated with stronger independent performance later on, even if they slowed people down at first. 然而，研究人员也发现，某些人工智能的交互风格与后期更强的独立表现相关，即使这些风格在初期会降低人们的处理速度。

“AIs that ‘tell’ by providing direct answers are more likely to foster reliance, while those that ‘ask’ via Socratic questioning are better at engaging someone to actually learn how to discern the truth on their own,” says Danry. “But it’s very much a trade-off between speed and effort.” “通过提供直接答案来‘告知’用户的人工智能更容易助长依赖性，而那些通过苏格拉底式提问来‘引导’用户的人工智能，则更能促使人们真正学会如何自行辨别真相，”丹里说，“但这在很大程度上是速度与努力之间的一种权衡。”