To begin a tour of research on implicit bias, the construct must be defined conceptually and operationally, and Section 1 does just that. As we shall see, the accumulated literature has been characterized by definitional divergences that merit investigation and resolution.

In this section, we reassess the value of explicit prejudice measures. P.J. Henry starts this discussion by reviewing critiques of implicit prejudice measures and points to the overwhelming evidence of the power of explicit measures to predict important outcomes. To date, implicit measures have not yet been shown to be similarly capable. Henry explains how the “implicit revolution” was founded on the claim that explicit measures are useless, yet this is clearly not so.

The concept of unconscious bias is firmly entrenched in American society, yet evidence has accumulated in recent years questioning widely accepted claims about the phenomenon, including assertions that it can be measured reliably, influences behavior and is susceptible to intervention. We adopt a two-pronged approach to investigating the state of affairs: First, assessing claims made about unconscious bias in the public sphere; and second, conducting a national public opinion survey – the first of its kind, to the extent we can ascertain – designed to measure public understanding of unconscious bias. Results show that broad majorities of Americans think unconscious biases are prevalent, influence behavior and can be mitigated through training. Confidence in its accurate measurement is lower. The public sees unconscious biases as more prevalent than biases that are consciously held, and as worthy of mitigation efforts by businesses and government. Our chapter assesses these attitudes and understandings and compares them with the state of the science on unconscious bias.

Despite twenty years of research, we have not yet reached a point of consensus about what might be considered the most important issue in the study of implicit bias: when and how strongly does it shape cognition and behavior? This section of this handbook reviews some of the relevant literature.

Recent decades have seen a series of attempts to further develop measures of implicit bias. Some observers have suggested drawing on lessons learned in the literature on optimal measurement of explicit bias to enhance implicit bias measures. Suggestions have also been made about how to improve meta-analyses of studies quantifying the strength of the link between implicit attitudes and behavior. For example, outdated statistical methods used in many meta-analyses of implicit bias may have led to incorrect inferences about the average effect sizes and can be avoided using newer techniques. Further improvement has been suggested to more effectively take into account omitted variables that may create spurious associations of implicit attitudes and behavior.

During the past century, racial attitudes in America have been radically transformed. One hundred years ago, this was a country of explicit racism, where separation of the races and discrimination against African Americans in particular were normative, formalized in laws, in the widespread practices of businesses and in the treatment of individuals by individuals every day. The civil rights movement of the 1960s brought about a landmark shift, eliciting widespread condemnation of racism, and setting the stage for the country’s embracing of multiculturalism and implementing policies in many arenas of life to level the playing field and compensate for past discrimination. These changes in public practices were accompanied by a gradual transformation of public opinion in the United States: surveys documented a steady growth of endorsement of racial equality and a decline in explicitly stated racial prejudice. More and more Americans endorsed principles of racial equality and expressed support for various policies preventing discrimination.

In contrast to most scientific research that goes largely unrecognized by the general public, the concept of implicit bias broke through into the public sphere. This success comes with the challenge that academic nuances and clearly stated limitations often get lost in translation. Moreover, given ongoing scientific debates about what implicit bias is and how to measure it, perhaps the phenomenon got out into public consciousness before scientists have fully understood it.