Silicon Valley leaders are once more declaring ‘DEI’ bad and ‘meritocracy’ good — but they’re improper

Who’s afraid of the Big Bad DEI? The acronym is near-poisonous now — a word that creates almost fast tension between those that embrace it and those that want it dead.

A major example of this divide was the response to startup Scale AI founder Alexandr Wang’s post on X last week. He wrote about moving away from DEI (diversity, equity, and inclusion) to as a substitute embrace “MEI” — merit, excellence, and intelligence. 

“Scale is a meritocracy, and we must all the time remain one,” Wang wrote. “It’s a giant deal each time we invite someone to hitch our mission, and people decisions have never been swayed by orthodoxy or virtue signaling or regardless of the current thing is.”

The commenters on X — which included Elon Musk, Palmer Luckey, and Brian Armstrong — were thrilled. On LinkedIn, nevertheless, the startup community gave a less-than-enthusiastic response. Those commenters identified that Wang’s post made it seem as if “meritocracy” was the definitive benchmark to seek out qualified hiring candidates — without making an allowance for that the concept of meritocracy is itself subjective. In the times which have followed the post, an increasing number of people have shared their thoughts and what Wang’s comments reveal concerning the current state of DEI in tech. 

“The post is misguided because individuals who support the meritocracy argument are ignoring the structural reasons some groups usually tend to outperform others,” Mutale Nkonde, a founder working in AI policy, told TechCrunch. ”All of us want the very best people for the job, and there may be data to prove that diverse teams are more practical.” 

Emily Witko, an HR skilled at AI startup Hugging Face, told TechCrunch that the post was a “dangerous oversimplification,” but that it received a lot attention on X since it “openly expressed sentiments that usually are not all the time expressed publicly and the audience there may be hungry to attack DEI.” Wang’s MEI thought “makes it really easy to refute or criticize any conversations regarding the importance of acknowledging underrepresentation in tech,” she continued.  

But Wang is way from the one Silicon Valley insider to attack DEI in recent months. He joins a chorus of those that feel that DEI programs implemented at businesses over the past several years, peaking with the Black Lives Matter movement, caused a backslide in corporate profitability — and that a return to “meritocratic principles” is overdue. Indeed, much of the tech industry has worked to dismantle recruitment programs that considered candidates who, under previous hiring regimes, were often missed within the hiring process. 

Looking for to make a change, in 2020, many organizations and power players got here together to vow more of a give attention to DEI, which, contrary to the mainstream discussion, is just not simply about hiring someone based on the colour of their skin but is about ensuring qualified people from all walks of life — no matter skin, gender, or ethnic background — are higher represented and included in recruitment funnels. It’s also about taking a have a look at disparities and pipeline issues, analyzing the reasoning behind why certain candidates are always missed in a hiring process. 

In 2023, the U.S. data industry saw latest women recruit levels drop by two-thirds, from 36% in 2022 to simply 12%, in line with a report from HR staffing firm Harnham. Meanwhile, the proportion of Black, Indigenous, and professionals of color in VP or above data roles stood at just 38% in 2022. 

DEI-related job listings have also fallen out of favor, declining 44% in 2023, in line with data from the job site Indeed. Within the AI industry, a recent Deloitte survey of girls found that over half said they ended up leaving not less than one employer due to how men and girls were treated in another way, while 73% considered leaving the tech industry altogether as a result of unequal pay and an inability to advance of their careers. 

Yet, for an industry that prides itself on being data-driven, Silicon Valley cannot let the concept of a meritocracy go — despite all the information and research showing how such pondering is only a belief system and one which can result in biased outcomes. The concept of going out and hiring “the very best person for the job” without taking into consideration any human sociology is how pattern-matching occurs — teams and corporations of people who find themselves alike, when the research has long shown that more diverse teams perform higher. Furthermore, it has only raised suspicions about who the Valley considers excellent and why. 

Experts we spoke to said this subjectiveness revealed other issues with Wang’s missive — mostly that he presents MEI as a revolutionary idea and never one which Silicon Valley and most of corporate America have long embraced. The acronym “MEI” appears to be a scornful nod to DEI, intended to drive home the notion that an organization must choose from hiring diverse candidates or candidates that meet certain “objective” qualifications.  

Natalie Sue Johnson, co-founder of the DEI consulting firm Paradigm, told TechCrunch that research has shown meritocracy to be a paradox and that organizations that focus an excessive amount of on it actually see a rise in bias. “It frees people up from pondering that they need to try hard to be fair of their decision-making,” she continued. “They think that meritocracy is inherent, not something that should be achieved.” 

As Nkonde mentioned, Johnson noted that Wang’s approach doesn’t acknowledge that underrepresented groups face systemic barriers society continues to be struggling to handle. Satirically, probably the most meritorious person could possibly be the one who has achieved a skill set for a job despite such barriers which will have influenced their educational background or prevented them from filling their résumé with the form of college internships that impresses Silicon Valley. 

Treating an individual as a faceless, nameless candidate, without understanding their unique experiences, and due to this fact their employability, is a mistake, Johnson said. “There’s nuance.” 

Witko added to that: “A meritocratic system is built on criteria that reflect the establishment, and due to this fact, it is going to perpetuate existing inequalities by repeatedly favoring those that have already got benefits.”

To be somewhat charitable to Wang, given how acidic the term DEI has turn into, developing a brand new term that also represents the worth of fairness to all candidates, isn’t a terrible idea — even when “meritocracy” is misguided. And his post suggests that Scale AI’s values could align with the spirit of diversity, equity, and inclusion even when he may not know it, Johnson said. 

“Casting a large net for talent and making objective hiring decisions that don’t drawback candidates based on identity is strictly what diversity, equity, and inclusion work seeks to do,” she explained. 

But again, where Wang undermines that is endorsing the mistaken belief that meritocracy will produce outcomes based on one’s abilities and merits alone. 

Perhaps it’s all a paradox. If one looks at Scale AI’s treatment of its data annotators — lots of whom live in third-world countries and scrape by on little pay — it suggests the corporate has scant real interest in disrupting the establishment. 

Scale AI’s annotators work on tasks for multiple eight-hour workdays — no breaks — for pay ranging as little as $10 (per the Verge and NY Mag). It’s on the backs of those annotators that Scale AI has built a business price over $13 billion and with greater than $1.6 billion in money within the bank. 

When asked for comment on the allegations made within the Verge and NY Mag piece, a spokesperson pointed to this blog post, by which it described its human annotator jobs as “gig work.” The spokesperson didn’t address TechCrunch’s request for clarification on Scale AI’s MEI policy.  

Johnson said Wang’s post is a fantastic example of the box many leaders and corporations find themselves trapped in. 

She pondered, can they trust that having meritocratic ideals is sufficient to lead to really meritocratic outcomes, and promote diversity? 

“Or, do they acknowledge that ideals usually are not enough, and to really construct more diverse workforces where everyone has the identical access to opportunities and might do their best work requires intention?”