Abstract:Artificial intelligence (AI) is being increasingly integrated into human problem-solving, yet its effects on individual skill development remain unclear. We examine how both AI usage and informativeness can shape learning in the context of a controlled logical reasoning task with on-demand access to AI assistance. We find that greater AI usage is associated with weaker skill development: heavy AI users underperform relative to comparable peers, whereas light AI users perform similarly to matched users who do not use AI. We also find in our study that these patterns are mediated by AI informativeness. Low-information AI neither improves immediate performance nor preserves performance after AI assistance is removed, and is linked to weaker learning overall. On the other hand, high-information AI was found to improve short-run performance without reducing post-AI outcomes on average in our experiments, but with heterogeneous effects. Our findings in general suggest that AI can, depending on context, either complement human skill development by amplifying independent reasoning or can act as a substitute that undermines such reasoning, with the implication that regulating AI access and usage will be important for promoting skill development in the presence of AI assistance.
| Comments: | Accepted at Hybrid Human Artificial Intelligence (HHAI) 2026 |
| Subjects: | Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC) |
| Cite as: | arXiv:2605.21695 [cs.AI] |
| (or arXiv:2605.21695v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2605.21695 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Shang Wu [view email]
[v1]
Wed, 20 May 2026 19:55:57 UTC (1,429 KB)