Assessing the implicit bias research program: Comments on Brownstein, Gawronski, and Madva versus Machery

Michael Brownstein, Alex Madva, and Bertram Gawronski articulate a careful defense of research on implicit bias. They argue that though there is room for improvement in various areas, when we set the bar appropriately and when we are comparing relevant events, the test–retest stability and predictive ability of implicit bias measures are respectable. Edouard Machery disagrees. He argues that theories of implicit bias have failed to answer four fundamental questions about measures of implicit bias, and this undermines their utility in further scientific research and policy making. In this article, I offer my perspective on this important debate. I argue that there is a theoretical mismatch in debating the merits of a research program on the terms of a specific theory within the research program. Nevertheless, the discussion allows us to see which questions are answered from within the perspective of a particular theory. I argue that the emphasis should be on whether implicit bias theories predict novel facts.