Two decades ago, the introduction of the Implicit Association Test (IAT) sparked enthusiastic reactions. With implicit measures like the IAT, researchers hoped to finally be able to bridge the gap between self-reported attitudes on one hand and behavior on the other. Twenty years of research and several meta-analyses later, however, we have to conclude that neither the IAT nor its derivatives have fulfilled these expectations. Their predictive value for behavioral criteria is weak and their incremental validity over and above self-report (...) measures is negligible. In our review, we present an overview of explanations for these unsatisfactory findings and delineate promising ways forward. Over the years, several reasons for the IAT’s weak predictive validity have been proposed. They point to four potentially problematic features: First, the IAT is by no means a pure measure of individual differences in associations but suffers from extraneous influences like recoding. Hence, the predictive validity of IAT-scores should not be confused with the predictive validity of associations. Second, with the IAT, we usually aim to measure evaluation (“liking”) instead of motivation (“wanting”). Yet, behavior might be determined much more often by the latter than the former. Third, the IAT focuses on measuring associations instead of propositional beliefs and thus taps into a construct that might be too unspecific to account for behavior. Finally, studies on predictive validity are often characterized by a mismatch between predictor and criterion (e.g., while behavior is highly context-specific, the IAT usually takes into account neither situation nor domain). Recent research, however, also revealed advances addressing each of these problems, namely (1) procedural and analytical advances to control for recoding in the IAT, (2) measurement procedures to assess implicit wanting, (3) measurement procedures to assess implicit beliefs, and (4) approaches to increase the fit between implicit measures and behavioral criteria (e.g., by incorporating contextual information). Implicit measures like the IAT hold an enormous potential. In order to allow them to fulfill this potential, however, we have to refine our understanding of these measures, and we should incorporate recent conceptual and methodological advancements. This review provides specific recommendations on how to do so. (shrink)

Identification of propositions as the core of attitudes and beliefs (De Houwer, 2014) has resulted in the development of implicit measures targeting personal evaluations of complex sentences (e.g., the IRAP or the RRT). Whereas their utility is uncontested, these paradigms are subject to limitations inherent in their block based design, such as allowing assessment of only a single belief at a time. We introduce the Propositional Evaluation Paradigm (PEP) for assessment of multiple propositional beliefs within a single experimental block. Two (...) experiments provide first evidence for the PEP’s validity. In Experiment 1 endorsement of racist beliefs measured with the PEP was related to criterion variables such as explicit racism assessed via questionnaire and indicators of behavioral tendencies. Experiment 2 indicates that the PEP’s implicit racism scores may predict actual behavior over and above explicit, self-report measures. Finally, Experiment 3 tested the PEP's applicability in the domain of hiring discrimination. Whereas general PEP based gender stereotypes were not related to hiring bias, results suggest a possible role of female stereotypes in hiring discrimination. In the context of these findings, we discuss both the potential and possible challenges in adopting the PEP to different beliefs. In sum, these initial findings suggest that the PEP may offer researchers a reliable and easily administrable option for the indirect assessment of propositional evaluations. (shrink)

Recently, Fahrbach and Park have argued that the pessimistic meta-induction about scientific theories is unsound. They claim that this very argument does not properly take into account scientific progress, particularly during the twentieth century. They also propose amended arguments in favour of scientific realism, which are supposed to properly reflect the history of science. I try to show that what I call the argument from scientific progress cannot explain satisfactorily why the current theories should have reached a degree of success (...) that excludes their future refutations and allows the inference to their truth. I further argue that this line of argumentation dismisses the burden of proof in a rather unfair manner by using a delaying tactic to postpone the question about the validity of the PMI in the future. (shrink)