When Experts Argue: Explaining the Best and the Worst of Reasoning

Argumentation, Vol. 25, No. 3, pp. 313-327, 2011

21 Pages Posted: 6 Sep 2011

Date Written: September 6, 2010


Expert reasoning is responsible for some of the most stunning human achievements, but also for some of the most disastrous decisions ever made. The argumentative theory of reasoning has proven very effective at explaining the pattern of reasoning’s successes and failures. In the present article, it is expanded to account for expert reasoning. The argumentative theory predicts that reasoning should display a strong confirmation bias. If argument quality is not sufficiently high in a domain, the confirmation bias will make experts tap into their vast knowledge to defend whatever opinion they hold, with polarization and overconfidence as expected results. By contrast, experts should benefit even more from the power of group discussion to make the best of the confirmation bias — when they genuinely disagree that is, otherwise polarization is again likely to ensue. When experts interact with laymen other mechanisms can take the lead, in particular trust calibration and consistency checking. They can yield poor outcomes if experts do not have a sustained interaction with laymen, or if the laymen have strong opinions when they witness a debate between experts. Seeing reasoning as a mechanism of epistemic vigilance aimed at finding and evaluating arguments helps make better sense of expert reasoning performance, be it in individual ratiocination, in debates with other experts, or in interactions with laymen.

Keywords: Argumentation, Reasoning, Expertise, Group decision making

Suggested Citation

Mercier, Hugo, When Experts Argue: Explaining the Best and the Worst of Reasoning (September 6, 2010). Argumentation, Vol. 25, No. 3, pp. 313-327, 2011. Available at SSRN: https://ssrn.com/abstract=1923096

Hugo Mercier (Contact Author)

University of Neuchatel ( email )

Espace Louis Agassiz 1
Neuchâtel, 2000

Register to save articles to
your library


Paper statistics

Abstract Views
PlumX Metrics