The False Binary: Excellence vs. Inclusion (The Techno-Authoritarian Backlash, Part 2)

The False Binary: Excellence vs. Inclusion (The Techno-Authoritarian Backlash, Part 2)
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There’s an anecdote I love from the now-retired Reply All podcast, it starts with a problem-solving question that I invite you to try now:

Let's say you are just sitting down at home for a really delicious hamburger/cheeseburger/veggie burger and fries for dinner, and you realize that you've forgotten the ketchup. You get up and look for your ketchup, but you realize all too late that you've run out. What do you do?

Well, if you are like me, from the Northeastern United States, you might look in your fridge and, seeing no more ketchup, look for reasonable alternatives: mayo or mustard. (Obviously, these choices are not exclusive to Northeast Americans.)

If, however, you are British or African American from the South, you likely keep your ketchup in the cupboard. Your next best option, looking in the cupboard, will likely be malt vinegar.

Why does this matter? Cultural diversity creates environments where different experiences converge, leading to diverse thinking patterns and problem-solving approaches. The more diverse the team, the richer the associations and analytical perspectives—ultimately creating more interesting, efficient, and surprising solutions.

In my last post, “Inclusive Design is an Act of Resistance,” I explored how inclusive technology can, and is, an act of resistance against the growing techno-fascist movement.  In this next part, “The False Binary: Excellence vs. Inclusion,” I want to tackle one of the more frustrating myths that techno-fascism perpetuates: that quality and inclusivity cannot coexist.  This point of view is not only racist, classist, ableist, sexist (and all of the other “ists” that perpetuate the “isms”), it is deliberately misleading.  It’s a not-so-clever trick used to protect power structures while making inclusivity seem like a burden rather than a strength.  

By unpacking the loaded language of meritocracy, we can see how systems supposedly designed to reward talent actually work to keep certain people in control.  For those of us building technology, understanding these tactics isn’t just interesting – it’s crucial if we want to create digital spaces that not only serve everyone (not just the privileged few), but also work and exist in environments ourselves that are challenging, intellectually curious and rigorous.  

What we're witnessing take over our country is techno-fascism, bred from a philosophy called Dark Enlightenment. I won't delve too deeply into that here, as I covered it in my prior article. At its core, techno-fascism and its companion ideology of meritocracy create a false binary between excellence and inclusion. This world view assumes that we cannot achieve excellence if we include diverse perspectives and people from different backgrounds.  The ideology insists that there is an inherent hierarchy and rejects any notion of egalitarianism, advocating for a social order where certain groups are deemed inherently more deserving of power and privilege.  

By contrast DEIA, seeks to dismantle systemic barriers and create equitable opportunity for all. I emphasize the word “opportunity” here because it is critical to understand that it is not a guarantee of entry, but an unlocking of a door that was previously sealed shut.  The idea that it is some magic open-sesame that eliminates the need for hard work or qualifications is plainly false. 

This misconception is how Dark Enlightenment and techno-fascism weaponize “meritocracy.”  Its proponents use the idea of “meritocracy” to justify existing inequalities, arguing that DEIA efforts lower standards and prioritize unqualified candidates over more deserving ones.  This argument conveniently ignores the systemic biases that prevent diverse individuals from accessing opportunities in the first place.

Challenging The False Dichotomy

The notion that meritocracy and inclusion stand in opposition is perhaps the most pernicious myth propagated by Dark Enlightenment.  It asks us to make a choice between quality and diversity – which is a premise that collapses under the most minimal scrutiny.  It’s a convenient narrative to ignore that “merit” has historically been defined by a very narrow set of criteria, often favoring those from privileged backgrounds.  It’s about maintaining a system where the same people always win, not about genuine excellence.  

True meritocracy cannot exist without inclusion.

I’ll say it again: TRUE meritocracy cannot exist without inclusion.  A system that systematically excludes entire populations – whether through biased hiring practices, homogeneous networks, or inaccessible interfaces – by definition fails at meritocracy.  This is especially dangerous in AI development, where systems trained on non-representative data sets don’t just inconvenience excluded groups – they actively harm them.  (See below for some examples.)

It’s like claiming to find the best athlete in the world while only allowing people from one neighborhood to compete.  

The data demolishes the false choice.  McKinsey conducted several long-term studies, including one over 5 years, examining 1000 companies in 15 countries, that found that organizations in the top quartile for gender diversity were 25% more profitable than their less diverse peers. For ethnic diversity, that figure rises by 36%. If meritocracy and inclusion were truly opposed, these numbers would be impossible.  (McKinsey: The benefit of gender and ethnic diversity in leadership; Report: More Diverse Companies Outperform Financially)

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Some Examples of Harmful Bias within AI:
Facial Recognition Technology: Early facial recognition systems were notoriously bad at identifying darker-skinned faces, particularly women of color. Research by Joy Buolamwini and Timnit Gebru found error rates of up to 34.7% for darker-skinned women compared to 0.8% for lighter-skinned men. When these systems were restrained with more diverse datasets, accuracy improved dramatically across all demographics. (Study: Facial recognition software misidentifies dark-skinned women 35 percent of the time; Study finds gender and skin-type bias in commercial artificial-intelligence systems)

Speech Recognition: Early voice assistants had significantly higher error rates (up to 35% more) for speakers with accents or non-standard dialects. Companies like Google and Amazon have since diversified their training data to include a wider range of accents, dialects, and speech patterns, resulting in more equitable performance across different user groups. (Racial disparities in automated speech recognition)

Medical Imaging AI: Algorithms trained primarily on X-rays and scans from white patients performed poorly when diagnosing conditions in Black patients. For example, algorithms for detecting skin cancer were less effective on darker skin. When researchers at Stanford retrained these systems with diverse skin samples, they achieved more consistent accuracy across all skin types. ( [PDF Download] Mitigating Racial Bias in Healthcare AI Development)

Decoding the Weaponized Language

The terms “performance” and “excellence” have strategically been co-opted as coded language to justify exclusion.  When Elon Musk demands “hardcore” workers willing to be “extremely hardcore” while simultaneously dismantling Twitter’s accessibility team, the subtext becomes clear: “excellence” isn’t about quality work – it's about conforming to a narrowly defined ideal of a worker – young, male, able-bodied, and without caregiving responsibilities.  

I mean, clearly, Mark Zuckerberg’s lament that the Meta workforce has been “neutered” in the past few years and that it needs more “masculine energy” isn’t a statement about gender values.  Instead, what he’s actually doing is signaling traditional “feminine” values like collaboration, emotional intelligence, and inclusive decision-making that are considered antithetical to “performance.” 

It’s a linguistic sleight of hand.  It allows tech leaders to appear “meritocratic” while reinforcing existing power structures. The definition of “excellence” is so narrow it can only be met by those already privileged within the system.  

It’s circular by design.  Excellence is defined by the traits of those already deemed excellent.

Next time you hear “we hire the best” from a company with a startlingly homogeneous workforce, recognize this for what it is: not a commitment to quality, but a commitment to comfortable sameness disguised as merit.  

And we’ve seen the consequences of this narrow vision playing out in real-time.  Twitter’s functionality deteriorated after Musk’s mass layoffs eliminated diversity and accessibility teams, while Meta’s pivot to the metaverse has struggled to gain traction beyond a homogeneous user base precisely because these products now reflect the limited perspectives of their increasingly uniform workforce.

Even more concerning, I’m astonished and scared of how Musk is using this same ethos to demolish the workforce and access to federal government services in the exact same manner. Just this past week, there have been Social Security office closures and the dismantling of Social Security help center phone lines – all needed for greater accessibility to the service by our elderly population. These actions reveal the broader cost of exclusionary thinking as it spreads beyond corporate boundaries into public services that millions depend on.

The Cost of Exclusion

When we exclude entire groups of people, we're not just being unfair; we're missing out on talent, innovation, and perspectives that could make our technology better for everyone. 

Think about it: if everyone building our technology comes from the same background, we're only solving problems that affect people from that background. We are, in effect, designing in an echo chamber that only amplifies our blind spots and limits our potential. This isn't charity – it's smart business. Think about the early fitness trackers that didn't accurately measure heart rates for people with darker skin – they missed a huge market and delivered a subpar product to many users. You simply can't build effective, successful products for users you don't understand or include on your team.

Products designed with inclusion from the start reach wider markets and demonstrate higher user satisfaction.  AI systems trained on diverse data sets make fewer errors and demonstrate higher accuracy across different populations.  Similarly, algorithmic fairness measures which were implemented to prevent discrimination against marginalized groups, ultimately improve accuracy and reliability for all users.  

My argument has always been that DEIA is not only morally and ethically necessary, but it also makes good business sense.  When we design inclusively, we create superior products for everyone.

Conclusion

The false binary between excellence and inclusion isn’t just wrong; it’s dangerous. It represents a calculated effort to maintain power structures while disguising exclusion as merit. When tech leaders frame “excellence” as inherently exclusive, they’re not pursuing quality; they are preserving comfortable homogeneity and classism at the expense of true innovation. 

Diverse teams make better products.  Inclusive design reaches wider markets.  Representative AI makes fewer errors.  

This is a moral position,  an economic position, and a position of resistance – and it’s backed by the data.  Every accessible interface we build, every diverse team we assemble, and every inclusive process we implement, challenges the techno-authoritarian vision of the world.

Identifying the problem is not enough.  In the face of growing techno-fascist influence, we need practical strategies of resistance.  We need examples that prove inclusion and excellence are not just compatible but inseparable.  We need to move beyond critique into action.  

In the final part of this series, “Building the Resistance,” I’ll share some concrete approaches for implementing inclusive design under pressure.  We’ll look at case studies of products that succeeded because of their inclusivity, explore how to build coalitions across technical disciplines and look at resistance efforts happening globally.  This isn’t just an American struggle; the fight for technology that serves all of humanity is worldwide.  

The stakes are high.  As technologists navigating an increasingly hostile landscape, we must recognize that inclusive design isn’t just good practice, it is a powerful form of resistance.

But resistance doesn’t just belong to those of us who build the technology.  If you are reading this and are not a technologist, know you are part of the fight, too.  You have a powerful voice as a consumer.  You can seek out and support products from companies with demonstrated commitments to diversity and accessibility.  Look for apps and services that provide privacy, offer robust accessibility features, and consider diverse user needs.  

When you encounter inaccessible websites or exclusionary products speak up through reviews, feedback forms and social media.

Demand better.

You can proactively ask companies about their diversity practices, accessibility standards, and ethical frameworks.  Support advocacy organizations fighting for digital equity and technology justice.  Share resources about inclusive design with your networks.  How we collectively embrace or reject technology shapes its future as much as those who build it.

Join me soon for Part 3, as we turn understanding into action. 


[Article image prompt: Create an illustration representing the false binary between excellence and inclusion in technology. Show feminine hands collaboratively building or holding up a complex, beautiful structure or digital interface. The structure should have elements that clearly represent different cultural approaches and solutions coming together to create something more innovative than any single approach could achieve. Create a sense of human warmth and possibility. The image should convey that diversity leads to superior solutions rather than compromising quality. Include subtle tech elements like circuit patterns or code fragments integrated throughout the composition to represent how inclusive design strengthens technological innovation.]