The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers
As Bainbridge [7] noted, a key irony of automation is that by mechanising routine tasks and leaving exception-handling to the human user, you deprive the user of the routine opportunities to practice their judgement and strengthen their cognitive musculature, leaving them atrophied and unprepared when the exceptions do arise.
In response, research has begun looking closely at how different activities are impacted by GenAI and the extent to which cognitive offloading [8] occurs, and whether this may be an undesirable thing. Some work has focused, for instance, on studying the effects of GenAI use on memory (e.g., [1, 106]) and on creativity (e.g., [28, 100]). Moreover, design research has also been developing interventions that improve the ability of people to think in certain ways (e.g., [24]). We review these lines of work in Section 2.
Lines of inquiry this paper opens 24
Research framings built by reading the notes related to this paper — the questions it feeds into.
What structural properties of attention create systematic model biases? When should work require human-AI partnership versus full automation?- Which workplace tasks see productivity gains when AI and users align?
- Which task characteristics determine whether AI can displace them first?
- How should productivity metrics change to account for shifts in activity type rather than total time?
- How does bottleneck automation differ from accessory work displacement?
- What economic role remains for human labor after bottleneck automation?
- How does uneven access to AI tools shape who benefits from productivity gains?
- Which firms capture the cost advantages from labor-to-AI substitution?
- Why does AI-improved task performance fail to transfer to independent work?
- Does AI assistance actually reduce neural processing and brain connectivity over time?
- Does constraining AI access during early task phases preserve skill formation?
- Does outsourcing tasks to AI reduce opportunities for skill development?
- How does AI assistance affect human cognitive development over time?
- How does AI assistance change learning outcomes across different cognitive engagement levels?
- Do workers become dependent on AI when they stop using it for the same task?
- Can explicit reflection during AI-assisted work improve transfer of learning?
- Why might AI that improves immediate task performance harm long-term skill development?
- Do AI tools save total time or just shift work between different activities?
- Does interaction time with AI systems displace time spent on active task work?