These findings inform current debates on what it means to become an expert (e.g., 10,000-hour rule), extending them to the domain of psychological science.

www.sciencedirect.com/science/arti...

5/5

Knowledge about psychology was also associated with thinking that phenomena had a material basis (e.g., brain, vs. soul). This extended to intuitive responses -- which generally lean more towards dualism. Again, these effects were stronger for subjectively intense experiences.

4/5

More knowledgeable individuals believed that psychological phenomena were more explainable through science, in particular the ones that people do not consider to be explainable (i.e., with an intense subjective experience).

3/5

Importantly, we find that these shifts only happen with meaningful exposure to psychology -- that is, exposure that translates into knowledge about psychology --, not just by progressing through their degree. 🎓

2/5

🇬🇧
I recently had a conversation with @tiagoramalho.bsky.social about the research I've been conducting.

💡We talked about topics I'm passionate about: Overconfidence and science learning, how this is impacted by artificial intelligence, and more.

Thank you, @rafmbatista.bsky.social! Let us know if you have any thoughts or questions!

A special thanks to @tanialombrozo.bsky.social, my advisor, without whom this wouldn't be possible, for all the guidance and all she taught me!

And shout-out to my lab mates @keremoktar.bsky.social @caseylewry.bsky.social

Read more here: www.nature.com/articles/s41...
9/9

This work has implications for the present epistemic landscape, which is becoming increasingly complex. We discuss downstream consequences for conceptualizing overconfidence, delivering science communication, and thinking about human-AI alignment!
8/9

✅ We find that people are poorly calibrated in the perceptions they have about the quality of their own explanations. In particular, miscalibration emerges for those that are exposed to explanations but fail to reproduce it in their own (S4).
7/9

✅ Effects of jargon even when they are misguided (i.e., for made-up jargon) and for naturalistic stimuli (e.g., tweets, S2B-S2C);
✅ We can correct people's biased responses by showing them that gaps persist (e.g., asking them to generate their own explanations, S3A-S3B);
6/9

💡 Main findings 💡
✅ Jargon increases explanatory satisfaction (for circular explanations, Studies 1A-4 [S1A-S4]), but decreases comprehensibility (S1A-S1C);
✅ Jargon increases perceptions of explanations by filling explanatory gaps (S2A-S3B);
5/9

We identified how to reduce this bias as well: Asking people to e.g., generate explanations impacted more their ratings of explanations with jargon. We also observed overconfidence, which we found the most for those that read explanations with jargon, but fail to reproduce them.
4/9

We then tested an explanatory account for this dissociation: People assume the jargon is doing important work, filling in conceptual gaps. So, this boost in quality for explanations with jargon is punctured for more complete explanations, since there are less gaps to fill.
3/9

Across 9 experiments (+6600 participants), we explored a paradox: How do non-experts judge scientific explanations they can’t fully understand? We found that scientific jargon can increase people’s satisfaction with explanations, even though it makes them less comprehensible.
2/9

🔬 How did we test this?
We manipulated bias desirability. Biases were framed as desirable (e.g., beneficial to the individual) or undesirable (e.g., harmful). We tested this both within the same bias and across different biases.

5/5

💡 What did we find?
Our study shows that the bias blind spot is smaller when the bias is considered desirable (e.g., being overly positive about close others). The more someone sees a bias as desirable, the smaller their blind spot for that bias.

4/5