Human biases limit cumulative innovation

Bill Thompson, Thomas L. Griffiths

Research output: Contribution to journalArticlepeer-review

Abstract

Is technological advancement constrained by biases in human cognition? People in all societies build on discoveries inherited from previous generations, leading to cumulative innovation. However, biases in human learning and memory may influence the process of knowledge transmission, potentially limiting this process. Here, we show that cumulative innovation in a continuous optimization problem is systematically constrained by human biases. In a large (n = 1250) behavioural study using a transmission chain design, participants searched for virtual technologies in one of four environments after inheriting a solution from previous generations. Participants converged on worse solutions in environments misaligned with their biases. These results substantiate a mathematical model of cumulative innovation in Bayesian agents, highlighting formal relationships between cultural evolution and distributed stochastic optimization. Our findings provide experimental evidence that human biases can limit the advancement of knowledge in a controlled laboratory setting, reinforcing concerns about bias in creative, scientific and educational contexts.

Original languageEnglish (US)
Article number2752
JournalProceedings of the Royal Society B: Biological Sciences
Volume288
Issue number1946
DOIs
StatePublished - Mar 10 2021

All Science Journal Classification (ASJC) codes

  • Immunology and Microbiology(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Environmental Science(all)
  • Agricultural and Biological Sciences(all)

Keywords

  • Bayesian
  • cultural evolution
  • function learning
  • inductive bias
  • innovation
  • optimization

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