(Johannes Kepler University)
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ABSTRACT: In this paper I explore the tension between the necessity of scientific input for complex political decisions that have a technical aspect (‘technical-political decisions’) and the inherent unreliability of expert judgement. While modern crises—such as climate change, pandemics, and socio-economic decline—require technical knowledge that citizens and politicians often lack, experts are frequently compromised by cognitive and motivational biases. Among the failings are:
- Cognitive Biases: Experts are prone to ‘confirmation bias’ and the ‘spiral of conviction’, where increased knowledge leads to greater dogmatism.
- Motivational Biases: Personal, financial, and political interests often colour scientific recommendations, particularly in medicine and economics.
- Numerical Illiteracy: Experts frequently struggle with statistical concepts, such as confusing relative and absolute risk reductions or committing the prevalence fallacy.
To address these failures, I take up Jürgen Habermas’s democratic models but reject both technocratic approaches that grant experts a political monopoly, and Habermas’ own democratic approach. Instead, I advocate a decisionist model characterised by competition. By consulting multiple competing experts, the political system can better identify the spectrum of scientific discourse while incentivising experts to reduce their individual biases.
This LMS Centre talk is financially supported by the project OP JAK: Knowledge in the Age of Distrust, CZ.02.01.01/00/23_025/0008711.