研究：AI 让人感觉更高效，实际收益甚微
MIT, Stanford, New York Univ, Princeton paper says AI can make people feel more…
MIT, Stanford, New York Univ, Princeton paper says AI can make people feel more efficient even when they are not actually becoming much more efficient.
麻省理工学院、斯坦福大学、纽约大学和普林斯顿大学的论文指出，人工智能可以让人感觉效率更高，即使实际上效率并未显著提升。
that people often use AI for simple tasks because it feels like it saves time and effort, but the measured benefit is often tiny, missing, or even negative.
人们常因感觉节省时间和精力而使用AI处理简单任务，但实测收益往往微乎其微，甚至为零或负值。
The biggest point is the feedback loop: once people use AI, they become more likely to use it again, even for easy tasks where doing it themselves would often be just as fast or faster.
最核心的一点是反馈循环：一旦人们使用AI，就更倾向于再次使用，即使对于自己动手往往同样快甚至更快的简单任务也是如此。
i.e. AI dependence can grow from a mistaken feeling of convenience, not just from real productivity gains.
也就是说，对AI的依赖可能源于错误的便利感，而不仅仅是实际生产力的提升。
Across three preregistered studies with 2,691 participants, people used AI for basic arithmetic, spelling, recall, and short rewriting at higher rates than they predicted, especially on easy tasks.
在涉及2691名参与者的三项预注册研究中，人们使用AI进行基础算术、拼写、回忆和短文改写，其使用率高于他们自己的预测，尤其是在简单任务上。
They also expected AI to save 55.7 seconds on average, when the measured saving was only 7.5 seconds.
他们还预期AI平均节省55.7秒，而实测节省仅为7.5秒。
For simple work, the hidden cost is not intelligence but interface friction: writing the prompt, waiting, reading, checking, and deciding whether the answer is acceptable.
对于简单工作，隐藏成本并非智力，而是界面摩擦：编写提示词、等待、阅读、检查以及判断答案是否可接受。
Once that loop begins, it can feel like effort has been outsourced, even when effort has only been rearranged.
一旦这种循环开始，就会感觉努力已被外包，即使努力只是被重新安排。
Here’s the key part: the study suggests that AI use can train its own justification.
关键部分在于：研究表明，AI的使用可以训练其自身的合理性。
After using AI on just two tasks, participants became more likely to use it again, even when independent completion was faster.
仅在两项任务中使用AI后，参与者就更倾向于再次使用，即使独立完成更快。
The danger is not dramatic dependence, but quiet recalibration.
危险并非戏剧性的依赖，而是悄无声息的重新校准。
A person who asks AI for a trivial answer today may not become less capable tomorrow, but they may become less accurate at judging when their own mind is already the faster tool.
今天向AI询问琐碎答案的人，明天未必能力下降，但他们可能对何时自己的思维已是更快工具的判断变得不那么准确。
- arxiv. org/abs/2605.22687
- arxiv.org/abs/2605.22687
更进一步：量化金融体系
看懂新闻只是起点——沿量化金融路径，把它变成能交付的工程能力