Despite decades of research and intervention, social inequality remains stubbornly persistent and effective solutions continue to elude academics, practitioners, and policymakers. In the target article, Chater & Loewenstein (C&L) highlight the distinction between individual and systemic (i.e., i-frame and s-frame) approaches to behavioral change and challenge the emphasis and overreliance on i-frame interventions. We extend their arguments to organizational policies and initiatives designed to increase equity, diversity, and inclusion (EDI), a theoretically and practically important domain of behavioral change. Using the frameworks described in the target article, we argue that, despite conventional focus on individual-level solutions (i-frame), behavioral policy and initiatives for increasing EDI are particularly well-suited to a systemic focus (s-frame).

A myriad of research and policy has attempted to mitigate inequality and improve EDI, but has focused almost exclusively on i-frame change – attempting to change discriminatory and exclusionary behavior by focusing on individuals. For example, the $8 billion/year diversity training industry claims to improve EDI outcomes by teaching individuals about their unconscious biases, with the hope that this will translate to behavioral change (Kochan et al., Reference Kochan, Bezrukova, Ely, Jackson, Joshi, Jehn and Thomas2003; Newkirk, Reference Newkirk2019). Similarly, workshops and trainings advocating for the “lean in” approach also target individuals, encouraging women and minorities to take personal responsibility for overcoming bias and advancing their careers (Sandberg, Reference Sandberg2013). Each of these approaches aim to “fix” individuals, either those who perpetuate bias and discrimination (e.g., via unconscious bias), or the women and minorities who suffer the consequences.

Although i-frame policies and practices are popular and lucrative, rigorous research demonstrates their limited effectiveness. For instance, although diversity training can improve attitudes toward EDI, there is very little empirical evidence of resulting behavioral change (Chang et al., Reference Chang, Milkman, Gromet, Rebele, Massey, Duckworth and Grant2019). Rather, seminal research points to negative repercussions including backlash and reactance (Kalev, Dobbin, & Kelly, Reference Kalev, Dobbin and Kelly2006). Similarly, although the “lean in” approach aims to empower women to take control and overcome discrimination by diligently pursuing ambition and achievement, a wealth of theory and evidence documents backlash against women who behave in counter-stereotypical, assertive ways (He & Kang, Reference He and Kang2021; Rudman & Glick, Reference Rudman and Glick2001; Rudman & Phelan, Reference Rudman and Phelan2008).

These unintended consequences make sense against the backdrop of i-frame policy effectiveness described by C&L: i-frame interventions often generate null, mixed, or modest effects. For EDI, the limitations of i-frame interventions are compounded because the psychological biases that drive inequality and discrimination are often difficult to control with conscious effort, and because converting attitudes (intention) to behaviors (implementation) is extremely challenging (Gollwitzer, Reference Gollwitzer1999).

Effectiveness aside, a more pernicious consequence of an i-frame focus in EDI is that it ultimately impedes progress by shifting responsibility away from organizations to make systemic changes. For instance, exposure to “lean in” messages creates and reinforces the belief that women can and should take responsibility for overcoming bias and closing gender gaps, ultimately undermining support for system-level change (Kim, Fitzsimons, & Kay, Reference Kim, Fitzsimons and Kay2018). Worse, this focus has spurred on entire industries dedicated to expanding and capitalizing on i-frame approaches, thus further entrenching the policies and systems that create and perpetuate these very problems.

The predominant i-frame focus in EDI research and practice seems especially misguided when one considers the wealth of scholarship illustrating that inequality is a structural problem arising from unequal access to opportunities, and seemingly “meritocratic” processes that advantage certain identities and marginalize others (Acker, Reference Acker2006; Amis, Mair, & Munir, Reference Amis, Mair and Munir2020; Cheryan & Markus, Reference Cheryan and Markus2020; Kang & Kaplan, Reference Kang and Kaplan2019). By focusing on i-frame solutions, the root of the problem remains buried; individuals are unjustly forced to figure out how to navigate a system that is stacked against them and, at times, designed in ways that underpin their failure. Inequality is not an individual-level issue, but rather a systemic problem that requires systemic solutions. Absent any other supporting systemic intervention, changing individual behaviors is unlikely to close inequality gaps; the systems in which individuals are nested must be fundamentally altered.

Our aim is not to eliminate i-frame solutions to EDI, but to echo C&L by asserting that i-frame solutions alone are unlikely to solve the problem. Rather, we underscore the need for a complementary focus on s-frame approaches. An emerging body of research has begun this shift by applying behavioral science tools such as framing and choice architecture to change organizational policies, processes, and structures that create and perpetuate bias (s-frame). For instance, Rivera and Tilcsik (Reference Rivera and Tilcsik2016) find that changing evaluation ratings from 10-point to 6-point scales help to mitigate evaluation bias against women. High-performing women were less likely than their male counterparts to receive 10 out of 10 (a number associated with brilliance, which is associated with men), but just as likely as men to receive 6 out of 6 (a number that is not associated with brilliance). In our own work, we demonstrate how changing defaults can mitigate gender inequality in competition and opportunities for advancement. We found that although women are less likely than men to compete and apply for promotions under a traditional “opt-in” frame that requires self-nomination, using an opt-out choice frame (i.e., competing or being considered for promotion by default with the choice to opt-out) substantially attenuated and, at times, eliminated the gender gap (He, Kang, & Lacetera, Reference He, Kang and Lacetera2021). Research and policies building on this body of work require organizations to re-examine their seemingly meritocratic and neutral policies, processes, and structures to determine whether and how their current systems advantage certain identities over others, and to experiment and re-design environments where bias and inequality are less able to hide.

An s-frame approach to behavioral science opens a new door of possibilities for behavioral change. Beyond the examples we provide here, other macro, structural perspectives must also be applied to design effective EDI interventions that foster more inclusive organizational outcomes and environments. Social inequality is a persistent, pressing issue for policymakers, scholars, and practitioners, the complexity of which calls for the design of multipronged interventions that shift away from overreliance on i-frame factors toward an s-frame mindset.