All Content from Business Insider 10月09日
AI的“附和”现象与心理学应用
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AI模型在设计上倾向于“附和”用户,即同意、支持用户的观点并提供帮助。心理学教授转型的AI顾问Leigh Coney指出,这种“附和”现象是AI项目失败的原因之一,因为人类固有的偏见同样会体现在AI中。她强调,在与AI互动时,应运用心理学原理,如“框架效应”,通过调整提问方式来引导AI产生更具批判性和启发性的回应。例如,要求AI挑战你的想法或扮演特定角色,可以帮助我们发现潜在的盲点,提升批判性思维和工作产出。

🤖 **AI的“附和”本质与潜在问题**:AI模型,包括更新后的ChatGPT,在设计上存在“附和”用户的倾向,即倾向于同意和支持用户的观点。Leigh Coney认为,这种“附和”是许多AI项目失败的原因之一,因为AI会继承人类的偏见。因此,即使AI更新以减少这种倾向,用户也需要主动进行批判性思考,才能真正提升工作内容和思维质量。

💡 **运用心理学技巧优化AI互动**:Coney建议,利用心理学原理可以显著改善与AI的互动效果。通过“框架效应”,即调整提问的措辞方式,可以改变AI的响应。例如,将一个项目延迟的通知从负面描述(如“解释项目延迟和遇到的问题”)转变为正面视角(如“将挑战视为学习机会,突出韧性与前进方向”),能够获得更积极和有建设性的回复。

🤔 **通过提问和角色扮演深化思考**:为了克服AI的“附和”并促进深度思考,Coney提倡主动引导AI。这包括要求AI指出用户思考中的假设或遗漏之处(“我思考中哪里不清晰?”或“我忽略了什么?”)。同时,指定AI扮演特定角色,如“扮演一个挑剔的CFO并提出五个尖锐问题”,能帮助用户为不同场景做好准备,并从新的视角审视自己的想法,从而获得更有价值的输出。

Leigh Coney says AI experiences the same biases that humans face.

This as-told-to essay is based on a conversation with Leigh Coney, a 34-year-old AI consultant based in France. It's been edited for length and clarity.

AI models can tend to be "yes-men."

They are sycophantic by design, meaning they agree with us, support our ideas, and want to help. Part of the reason I think so many AI projects fail is because the human factor is overlooked. The same biases that apply to us also apply to AI, so it's important to factor in psychological principles when building experiments, agents, and automation.

I decided to pivot from teaching psychology at a university to becoming an AI consultant after Microsoft announced Copilot for its products nearly three years ago. At that moment, I decided AI would be in every business.

Now, I build custom AI automations and agents for businesses across many industries to increase efficiency and growth, using my psychological background to interact better with AI. Although ChatGPT was updated to make it less sycophantic, we have to make an extra effort to be critical of and question our ideas if we want to improve our thinking or work content.

Ask AI to challenge your ideas

A standard ChatGPT prompt might not challenge a flawed plan.

I ask AI to point out assumptions I might be making when I'm talking about an idea. My goal is to uncover things I'm not thinking about by asking questions like "where am I not being clear in my thinking?" or "What am I overlooking?"

Specify your audience to uncover new perspectives

AI is particularly useful for expanding our thinking by uncovering perspectives we could be missing.

Let's say you're pitching an idea to a CFO. Tell your chatbot to "Act as a skeptical CFO and ask five hard-hitting questions. Don't be shy. Be harsh."

Not only will it prepare you for the pitch, but it will also give you better output. The questions may even be more valuable than the answers because they force you to think about things you didn't think about before.

Use the 'framing effect'

A surgery with a 90% survival rate feels different than a surgery with a 10% mortality rate. That's the framing effect. Little wording tweaks in our prompts not only change how we feel, but can also change how AI responds.

The way you should frame a question to AI depends on what you're trying to do.

Let's say a team is facing a setback at work, and a manager is using a chatbot to write an email to their employees. If the manager prompts the chatbot to "explain the project delay and the problems they encountered", that's a negative framing, and the response will be more critical.

A more positive framing would be to say something like, "draft a project update for the team. Frame our recent challenge as a critical learning moment that has revealed two insights for making the final product even better. Focus on our resilience and the path forward."

If I'm using a chatbot to work on something important, I test out many different versions of my prompt in different chats. I tweak some words, sometimes just one, and it actually makes a really big difference in the response I get.

I'm not as concerned about AI as I used to be

The speed at which AI was advancing made me a bit concerned about jobs and employment, but since the personally underwhelming GPT5 release, I think we've got a lot more time than I previously assumed. To me, this is good news for our job market.

Learning about cognitive biases is worth it. It improves how we think and communicate with each other and with AI, and will ultimately lead to better output.

Are you an AI expert with tips to share? If so, please reach out to the reporter at tmartinelli@businessinsider.com.

Read the original article on Business Insider

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AI 人工智能 心理学 批判性思维 框架效应 AI Prompting Leigh Coney
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