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arXiv:2604.04721cs.AI

AI Assistance Reduces Persistence and Hurts Independent Performance

Grace Liu, Brian Christian, Tsvetomira Dumbalska, Michiel A. Bakker, Rachit Dubey

Abstract

People often optimize for long-term goals in collaboration: A mentor or companion doesn't just answer questions, but also scaffolds learning, tracks progress, and prioritizes the other person's growth over immediate results. In contrast, current AI systems are fundamentally short-sighted collaborators -- optimized for providing instant and complete responses, without ever saying no (unless for safety reasons). What are the consequences of this dynamic? Here, through a series of randomized controlled trials on human-AI interactions (N=1,222), we provide causal evidence for two key consequences of AI assistance: reduced persistence and impairment of unassisted performance. Across a variety of tasks, including mathematical reasoning and reading comprehension, we find that although AI assistance improves performance in the short-term, people perform significantly worse without AI and are more likely to give up. These findings are particularly concerning because persistence is foundational to skill acquisition and is one of the strongest predictors of long-term learning. We posit that persistence is reduced because AI conditions people to expect immediate answers, thereby denying them the experience of working through challenges on their own. These results add to the growing literature on cognitive offloading and AI-induced deskilling, and suggest the need for AI model development to prioritize scaffolding long-term competence alongside immediate task completion.

arXiv comments
Journal reference
DOI
Subjects
cs.AIArtificial Intelligence

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Linked by 7 identifiable commenters in 9 comments across 6 threads, from Apr 2026 to Oct 2026. Found in 6 HN submissions from Apr 2026 to Oct 2026. Open submission discussions.

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Discussed in comments6 threads

  1. Using AI for just 10 minutes erodes your ability to persist at hard things 2 comments

    • Link to the paper: https://arxiv.org/pdf/2604.04721

      atkristaView on HNParent context

    • The article title is not supported by the evidence presented in the paper (https://arxiv.org/pdf/2604.04721). The evidence for reduced persistence is kinda weak. The strongest experimental result in the paper is: if people use AI to help solve a series of problems, and then the…

      rahimnathwaniView on HNParent context

  2. The LLM Critics Are Right. I Use LLMs Anyway 2 comments

    • Your suspicion is already being studied with increased effort, and the starting point has solid bones: https://arxiv.org/pdf/2604.04721 For what it is worth, my colleagues who use these tools more liberally see a much higher regression rate and are left refactoring more as well.…

      dannersyView on HNParent context

    • I think folks ITT are trivializing the issue here. Many keep drawing parallels to LLMs being akin to the loom or calculator. That seems intellectually dishonest to me. Those tools were not anthropomorphized interfaces, nor were they instant gratification. To do significant…

      dannersyView on HNParent context

  3. AI has a multiplying effect on existing technical skills 1 comment
  4. Codex for almost everything 1 comment
  5. AI Assistance Reduces Persistence and Hurts Independent Performance 1 comment
  6. There's yet another study about how bad AI is for our brains 2 comments

    • Link to the preprint paper: https://arxiv.org/pdf/2604.04721 Worth reading the conclusion - makes a good point or two regarding the cumulative effect of using AI and not only the loss of the learning through struggle/time, but also the reference point of how long tasks should…

      keysersoze33View on HNParent context

    • Source: https://arxiv.org/abs/2604.04721 (https://news.ycombinator.com/item?id=47682908)

      ChrisArchitectView on HNParent context

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