episcope

Definition

A validated trait measuring how much a person enjoys and seeks effortful thinking. The only person-level trait in this glossary.

What is at stake

Designed friction does not land the same on everyone. In Buçinca and colleagues' 2021 study of AI-assisted decisions, the benefit ran at d = 0.57 for high need for cognition against 0.15 for low. If the trait does the work, an augmentation programme is selecting rather than teaching.

Where the word came from

  1. First useCohen, Stotland and Wolfe, 1955
  2. The validated scaleJohn Cacioppo and Richard Petty, 1982, who together built the Elaboration Likelihood Model
  3. Reaches episcope by three independent routesZana Buçinca and colleagues in 2021 on who benefits from designed friction, Yu and colleagues in 2026 on who misjudges what AI saved them and David Brooks in The Atlantic the same year

How episcope came to it

John Cacioppo and Richard Petty, 1982, social psychologists then at the University of Iowa and the University of Missouri, in a peer-reviewed article in the Journal of Personality and Social Psychology. They built the scale that is still used, and it has held up for forty years across languages and samples, which is rare for a trait measure.

What to watch for

A trait is a tendency, not a verdict on a person. The scale describes how much someone reaches for hard thinking when nothing forces them to. It says nothing about how well they think once they do, and it moves with context more than the word trait suggests.

Papers and articles behind it

Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology, 42(1), 116-131.

Peer reviewed

Buçinca, Z., Malaya, M. B., & Gajos, K. Z. (2021). To Trust or to Think: Cognitive Forcing Interventions Can Reduce Overreliance on AI in AI-assisted Decision-making. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW1), article 188.

Peer reviewed

Yu, S., Jurafsky, D., Hawkins, R. D., et al. (2026). The efficiency-gain illusion: People underestimate the rate of AI use and overestimate its benefits on simple tasks. arXiv:2605.22687.

PreprintPreprint. All tasks ran under five minutes.

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