Biases in Science
Idea and Motivation
One of the main obstacles of reliable scientific research is the occurrence of explicit or implicit biases. Well-known examples of such biases include the confirmation bias, the ingroup bias, and biases resulting from industry-sponsored research. Each of these biases may impede the objectivity of scientific inquiry by, among other things, influencing one’s judgement as to what counts as relevant evidence, or one's selection of research problems and methods of inquiry. All this, in turn, may ultimately affect the explanations, the predictions, as well as the broader theoretical accounts accepted by scientists. What is more, as research results often provide direct input for policy making, the problem of biases in science is also of socio-political relevance.
This conference aims at bringing together scholars from philosophy, the sciences, and science policy, to advance our understanding of biases in science by addressing questions such as:
- How do psychological mechanisms for scientific biases differ from those underpinning everyday biases in categorization, diagnosis, induction, etc.?
- What social mechanisms catalyse biased research?
- How can biased reasoning and information sharing be formally modelled?
- How are general hypotheses concerning bias supported by concrete cases of biased research?
- How are answers to the above questions helpful in mitigating the risks of biased research?