ISSN 0439-755X
CN 11-1911/B

Acta Psychologica Sinica ›› 2019, Vol. 51 ›› Issue (4): 395-406.doi: 10.3724/SP.J.1041.2019.00395

• Special Column: Behavioral decision-making is nudging China toward the overall revitalization •     Next Articles

Are we truly irrational and almost impossible to educate? Analyzing the scientific evidence behind libertine paternalism

Gerd GIGERENZER1,LUAN Shenghua2(),LIU Yongfang3   

  1. 1 Max Planck Institute for Human Development, Germany
    2 Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
    3 华东师范大学心理与认知科学学院, 上海 200062
  • Received:2017-11-14 Published:2019-04-25 Online:2019-02-22
  • Contact: Shenghua LUAN
  • Supported by:


Based on research in psychology, libertine paternalists argue that our mind is systematically flawed, which leads to many cognitive biases that are too deeply entrenched to eradicate through education. Thus, they suggest that authorities should take lead and nudge people into proper behaviors and good decisions. However, from the perspectives of ecological rationality, the outcomes of the so-called cognitive biases may not be bad, and in many instances, can be even better than those of the so-called rational reasoning as suggested by libertine paternalists. We analyze the evidence libertine paternalists use to justify nudging and find two major problems: (1) some of the supposed evidence is the product of researchers’ narrow interpretations of what qualify as human rationality and rational thinking; and (2) some libertine paternalists selectively reported scientific evidence, neglecting or sparsely reporting research that show findings contradictory to their belief. We conclude that there is lack of evidence to support the assertion that people are irrational and almost impossible to educate. To invest on education and make people risk savvy not only has been shown plausible and applicable, but also should be a more sustainable solution than nudging.

Key words: nudge, ecological rationality, risk, uncertainty, heuristics, framing effect, probability learning

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