Musings on Information Security and Data Privacy: Dunning-Kruger After AI: the Gap That No Longer Closes

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Dunning-Kruger After AI: the Gap That No Longer Closes

or Dunning-Kruger doesn't self-correct anymore.

> TL;DR. The Dunning-Kruger effect, that is, the difference between what people think they can do<br>and what they can actually do, used to close and self corrects with experience. My hypothesis that I introduce in this post is that AI keeps it open: it increases confidence and splits real capability into "with the tool" and "without the tool." For companies, that turns intrinsic capability from a productivity question into a governance one, and it is the capability that quietly erodes.

The ending that used to be guaranteed (more or less)

About the Dunning Kruger curve

What AI changes

The Gap that no longer closes

Does it really matter?

What it means for companies

1. The ending that used to be guaranteed (more or less)

Everyone knowns "Mount Stupid ". Whether it’s the co-worker who’s researched a single online thread and wants to completely upend the operations of the team, or the new hire who’s watched a tutorial video and is convinced that everyone was doing everything incorrectly, we’ve all been there at one point or another.

The great thing about Dunning-Kruger is that there really is an ending to it. In the battle of experience vs. confidence, experience always wins. The difference between what you think you can do and what you can do is going to close on its own. There’s a simple, and really quite boring iteration that explains what happens: you do it, you break things, you mess up, but you figure it out. Until the day that your perception aligns with reality, the reality of the situation is going to keep the lights on.

Figure 1. The classic picture. Perceived capability runs ahead, crashes, then converges on actual capability. The gap closes.[Thierry ZOLLER]

2. About the Dunning-Kruger curve

Here's the thing: the chart that everyone think they know is actually not what it seems. The famous Dunning-Kruger curve, with its peak of confidence and valley of despair, didn't actually come from Dunning and Kruger. You won't find it in their 1999 paper, or in any of Dunning's later work. So, where did it come from? It started spreading like wildfire through management training and the internet in the mid-2000s. But the real study is actually pretty different. It compared how people thought they'd do with how they actually scored, and it was divided into four groups. The interesting thing is, the line on the chart just keeps going up - it doesn't peak and then drop like everyone thinks.<br>There's a lot of debate about this effect, and experts can't seem to agree on what it really means. Some researchers think it's just a statistical illusion, a combination of people naturally rating themselves higher than average and the phenomenon of regression to the mean. They point to studies that suggest this pattern is just a mirage, not really telling us anything significant. In my opinion, the key takeaway is that the pattern itself is real - that's what matters most to my hypothesis. What it actually signifies, however, is still up for debate.<br>I'm using this well-known chart on purpose, because it's familiar to everyone, not because it's the 1999 data. I guess, the point I'm making doesn't rely on the curve being entirely accurate. It only needs one thing that nobody disagrees with: people are not good at judging their own abilities, and the difference between what they can actually do and what they think they can do is significant. This gap is made even wider by a tool that affects how we perceive ourselves.

3. What AI changes

Two things change according to me. Let's go through them one after the other.

1. First, the confidence goes up. A beginner with an AI assistant produces work that looks from an expert.

The delivery is the proof, and the proof says "good". That's why the early peak of overconfidence climbs higher than it ever did on its own. The dip isn't as deep either. The moment of getting caught comes later and is softer, because the AI usage papers over the gaps that used to show you up. And the line never really drops, t here is no longer a reliable point where harsh reality (failure, mistakes etc) forces a reality check, because the output keeps looking fine.

Figure 2a shows the one line changing.

Figure 2a. Same chart, one line changed. Perceived capability peaks higher, dips less, and no longer comes back to meet actual. The gap that used to close stays open. [Thierry ZOLLER]

2. Second, "what you can really do" stops being one thing. Before AI, your ability was a single number. Now it splits in two (Figure 2b).

Let me explain, there is what you can produce...