The Divide over DEI: Meritocracy vs. Diversity, Equity, and Inclusion
The tech industry is currently divided over the concept of DEI (diversity, equity, and inclusion). The recent post by Scale AI founder Alexandr Wang on X sparked a heated debate. Wang argued that his company embraces “MEI” (merit, excellence, and intelligence) instead of DEI. While influential figures like Elon Musk, Palmer Luckey, and Brian Armstrong praised Wang’s perspective, the startup community on LinkedIn responded less favorably.
Critics pointed out that meritocracy, as Wang suggests, is subjective and fails to account for structural barriers that certain groups face. Mutale Nkonde, an AI policy founder, emphasized the importance of diverse teams, noting that they have been proven to be more effective. Emily Witko, an HR professional, called Wang’s post a dangerous oversimplification that undermines the conversation about underrepresentation in tech.
Wang is not alone in his attack on DEI. Many in Silicon Valley believe that these programs have negatively impacted corporate profitability. However, DEI is not simply about hiring based on skin color; it aims to ensure representation from all backgrounds and address disparities in recruitment processes.
Recent data reveals concerning trends related to DEI. The number of women recruits in the U.S. data industry dropped by two-thirds in 2023. Furthermore, job listings related to DEI decreased by 44% in the same year. The AI industry experienced high attrition rates among women due to unequal treatment and pay discrepancies.
Despite being a data-driven industry, Silicon Valley clings to the idea of meritocracy, despite research showing its flawed outcomes and biased nature. The belief that hiring the “best person for the job” without considering diversity leads to pattern-matching and homogeneous teams. Experts warn that this approach perpetuates inequalities and raises suspicions about who the industry considers excellent.
Natalie Sue Johnson, co-founder of a DEI consulting firm, explains that meritocracy can increase bias and hinder efforts to achieve fairness. Underrepresented groups face systemic barriers that meritocracy fails to acknowledge. Treating candidates as faceless entities without considering their unique experiences and backgrounds is a mistake.
While creating a new term that reflects fairness and inclusivity is not a bad idea, Wang’s endorsement of meritocracy overlooks the complexities of achieving diversity, equity, and inclusion. Scale AI’s treatment of its data annotators, who work long hours for low pay, raises questions about the company’s commitment to disrupting the status quo.
Ultimately, leaders and companies must consider whether having meritocratic ideals alone is enough to promote diversity or if intentional efforts are necessary to create truly inclusive work environments.