RCTs (N = 1,222): about 10 minutes of AI help makes people give up sooner and do worse once the AI is taken away
Confirmed
The takeaway
“AI Assistance Reduces Persistence and Hurts Independent Performance” (Grace Liu, Brian Christian, Tsvetomira Dumbalska, Michiel A. Bakker, Rachit Dubey; arXiv 2604.04721, April 6, 2026) reports three randomized controlled trials with 1,222 online participants.
Status
- Claim
Confirmed
- Our reporting
- High confidence
- Importance
- 3 of 5
- Last verified
- 10 October 2026
Your AI and this story
- GPT-6 AstraIn its training data
- Claude Opus 5.5In its training data
- Gemini 3.8 Flash6 days after its cutoff
- Grok 4.7In its training data
It is after the cutoff of Gemini 3.8 Flash, and can be in the training data of GPT-6 Astra, Claude Opus 5.5 and Grok 4.7.
Key facts
- Design: randomized controlled trials, N = 1,222 in total: Experiment 1, 354 participants on fraction problems; Experiment 2, a larger replication with 667; Experiment 3, 201 on SAT reading comprehension (Berkeley News)
- In Experiment 1, the AI group had ChatGPT for 12 of 15 fraction problems; it was then removed for the last problems (EurekAlert release). The press releases give no model version
- Result (abstract): AI help improves short-term performance, but ‘people perform significantly worse without AI and are more likely to give up’; the effects ‘emerge after only brief interactions with AI (approximately 10 minutes)’
- Proposed mechanism (abstract): AI ‘conditions people to expect immediate answers, thereby denying them the experience of working through challenges on their own’. Persistence is ‘one of the strongest predictors of long-term learning’
- Recommendation: models should ‘prioritize scaffolding long-term competence alongside immediate task completion’, e.g. tutoring-style answers rather than full solutions
- Brian Christian (CHAI, UC Berkeley; author of The Alignment Problem): ‘We need to work toward a future in which human abilities are, as much as possible, augmented rather than supplanted.’
- Venue: Conference on Language Modeling (COLM 2026). Berkeley News publicised it on Oct 9, 2026; EurekAlert, Bioengineer.org and AI newsletters followed
What happened
A team led by Grace Liu, with Brian Christian (UC Berkeley’s Center for Human-Compatible AI), Tsvetomira Dumbalska, Michiel A. Bakker and Rachit Dubey, ran three online randomized experiments. Participants solved fraction problems (two experiments) or SAT reading-comprehension questions (one), some with ChatGPT available and some without. After about ten minutes the AI was taken away. The AI group then did worse than the controls and skipped or abandoned more problems. The preprint appeared in April 2026. It drew wide attention only in October, when UC Berkeley publicised it around its presentation at COLM.
Why it matters
It is causal (randomized) evidence that even brief AI help lowers persistence, one of the strongest predictors of learning, and not only correlational survey data. It argues that assistant design (instant, complete answers) has costs for skill formation. This bears on AI in schools and on human review of agent output.
Sources
3 sources from 3 sites. Numbers match the chips in the text.
3 sources: 2 primary, 1 press
Primary
- arXiv 2604.04721: AI Assistance Reduces Persistence and Hurts Independent Performancearxiv.org, paper
- Berkeley News (Oct 9, 2026): Using AI for just 10 minutes erodes your ability to persist at hard thingsnews.berkeley.edu, official
Press
Changes
- Filed from the arXiv abstract and the Berkeley News and EurekAlert releases