Abstract:
Once one abandons the ideal of value-free, impartial science, the question of how to distinguish biased from legitimately value-laden science arises. To approach this \"new demarcation problem\", I argue that one should distinguish different uses of \"bias\" in a first step: a narrow sense of bias as systematic deviation from the truth, and a wider sense that covers any kind of tendency impacting scientific reasoning. Secondly, the narrow sense exemplifies an ontological notion of bias, which understands bias in terms of a deviation from an impartial ideal outcome. I propose to replace it with an epistemic notion of bias, which understands biased research as research that we have good reasons to suspect could have been (done) systematically better. From a socio-epistemic perspective, such good reasons to expect better can be found in a lack of responsiveness to conventional standards and/or critical discourse in the scientific community. In short, bias in an epistemic sense consists in a deviation, not from truth but from current best practice. While this turns bias into something that is dependent on time and context, it allows for value-laden research to be unbiased, if there are no good reasons to expect this research to be better.