AI is quietly becoming a Dunning-Kruger amplifier, enabling people with little expertise to produce outputs that appear highly knowledgeable—while they remain unable to separate fact from confident nonsense.
This isn't about malice or laziness. It's about a dangerous mismatch: AI generates fluent results faster than users can build the expertise to evaluate them. Fluency, in turn, is mistaken for quality.
Real-world examples are already emerging. In organizations, untrained staff produce professional-looking training materials riddled with pedagogical errors. In coaching, those without certification use AI to simulate sessions that would fail basic standards. The outputs look convincing, but the producers lack the domain knowledge to spot the flaws.
Perhaps the most troubling long-term effect is the quiet erosion of cognitive skills. Each time AI shortcuts a task, the mental muscle for that task weakens—not in one dramatic loss, but through thousands of small decisions that felt efficient at the time.