Dorothy Bishop: The psychology of scientists: The role of cognitive biases in sustaining bad science
Much has been written about how we might tackle the so-called “replication crisis”. There have been two lines of attack. First, there are those who emphasise the need for better training in experimental design and statistics. Second, it is recognised that we need a radical overhaul of the incentive structure of science.
I shall argue, however, that to improve scientific practices we need to go deeper, to understand and counteract the mechanisms that maintain bad practices – not just at the institutional level, but in individual people. Misunderstanding of statistics, and the incentive structure that has evolved, have their roots in human cognition. I shall discuss how scientific thinking is not natural for humans: biased attention in conditions of information overload, use of cognitive schemata, and asymmetric moral reasoning all play a part in sustaining maladaptive scientific practices.
Professor of Developmental Neuropsychology, University of Oxford
Dorothy Bishop is a psychologist who holds a Wellcome Trust Principal Research Fellowship at the Department of Experimental Psychology, University of Oxford, where she heads an ERC-funded programme of research into cerebral lateralisation for language. She is a supernumerary fellow of St John’s College Oxford, a Fellow of the Royal Society, Fellow of the British Academy and Fellow of the Academy of Medical Sciences. Her main research interests are in the nature and causes of developmental language difficulties, with a particular focus on psycholinguistics, neurobiology and genetics. In 2015 Dorothy chaired a symposium on Reproducibility in Biomedical Science organised by the Academy of Medical Sciences, Wellcome Trust, MRC, and BBSRC, and she is chairing the advisory board of the recently-formed UK Reproducibility Network. She has a popular blog, Bishopblog, which features posts on a wide range of topics, including those relevant to reproducibility. She is on Twitter as @deevybee.