What Happened
When it comes to large language model-powered tools, there are generally two broad categories of users.
Why It Matters
On one side are those who treat AI as a powerful but sometimes faulty service that needs careful human oversight and review to detect reasoning or factual flaws in responses.
Key Details
- On the other side are those who routinely outsource their critical thinking to what they see as an all-knowing machine.
- Recent research goes a long way to forming a new psychological framework for that second group, which regularly engages in "cognitive surrender" to AI's seemingly authoritative answers.
- That research also provides some experimental examination of when and why people are willing to outsource their critical thinking to AI, and how factors like time pressure and external incentives can affect that decision.
- Just ask the answer machine In "Thinking—Fast, Slow, and Artificial: How AI is Reshaping Human Reasoning and the Rise of Cognitive Surrender," researchers from the University of Pennsylvania sought to build on existing scholarship that outlines two broad categories of decision-making: one shaped by "fast, intuitive, and affective processing" (System 1); and one shaped by "slow, deliberative, and analytical reasoning" (System 2).
Background Context
When it comes to large language model-powered tools, there are generally two broad categories of users. On one side are those who treat AI as a powerful but sometimes faulty service that needs careful human oversight and review to detect reasoning or factual flaws in responses. On the other side are those who routinely outsource their critical thinking to what they see as an all-knowing machine. Recent research goes a long way to forming a new psychological framework for that second group, which regularly engages in "cognitive surrender" to AI's seemingly authoritative answers. That research also provides some experimental examination of when and why people are willing to outsource their cri
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Source: Ars Technica – All content – Original Link
Source: Ars Technica – All content
