A machine can complete its assignment while making someone else’s job harder. An AI tool might produce code faster than a developer can meaningfully review it. A robot might follow its route while leaving nearby workers uncertain about where it will move next.
In both cases, apparent efficiency can conceal a poorly designed working relationship. As businesses consider how much work to delegate to AI and robots, I believe they should ask a broader question than how quickly a task gets done. Does the technology help people remain capable, informed, and in control?
That should be a condition of successful adoption. Research offers reason to examine that question. A 2025 study published in the proceedings of the Conference on Human Factors in Computing Systems (CHI), an international conference on human-computer interaction, surveyed 319 knowledge workers and found that greater confidence in generative AI was associated with less reported critical thinking.
This does not establish that AI causes lasting skill loss. It does suggest that confidence in a tool deserves scrutiny when people remain responsible for its results My concern is practical. When a system makes accepting an answer easier than understanding it, maintaining meaningful oversight can become harder.
Productivity measures should account for that burden. I encountered this problem after spending three-and-a-half years working manually on teleoperation and mission control systems for robotic quadrupeds; our software organization received an opportunity to try AI. As we rolled out AI and our team's mandate diverged from the work I was interested in doing, I made the mistake of over-relying on AI tools.
My work required more correction, and the apparent shortcut sometimes made delivery slower. I left shortly after to focus on my game studio that I was running on the side. Around the same time, while running the game studio, we began accepting AI-generated changes faster than we could thoroughly understand them.
Extract — continue reading at the source.
