Implicit measures – the results of indirect computerized reaction-time attitude measurements such as the Implicit Associations Task (the “IAT”, Greenwald, McGhee, & Schwartz, 1998) – are often described as reflecting “attitudes that people are unable or unwilling to report” (e.g., www.projectimplicit.org). This suggests that people are either entirely unaware of their “unconscious” attitudes, or unwilling to reveal them honestly. I will present a series of projects that questions the utility and veracity of both of those explanations and show that under many circumstances people are both willing and able to report on the evaluations reflected in implicit measures. Instead, I will present a model that can explain divergences between implicit bias and explicit attitudes in terms of other psychological (attention, failures in affective forecasting) and methodological (stimulus effects, calibration) factors. These findings have implications for cognitive and applied social psychology. Theoretically, they can lead to a better understanding of automaticity and consciousness in social cognition, suggesting a distinction between three types of conscious awareness of one’s own cognitions. From an applied perspective, a better understanding of the underlying cognitions can lead applied researchers to design more effective interventions targeted at acknowledgement of racial biases. Discussion will focus on how simplified and inaccurate explanations of implicit bias may not only be inaccurate, but thwart the way for social-cognitive research to have an impact on important societal issues.