Joe vs José
There is a hidden tax we all pay. This tax does not build bridges. It doesn’t pave roads or pay for defense, but it is very real. In the United States, only the total combined federal tax revenue ($3.2 trillion) rivals it for scale. But it doesn’t stop at our borders. This tax is collected around the world, and every year vast amounts of money and productivity are lost as a result, impeding growth and stagnating economies. And while everyone pays this tax, its most direct burden is placed on those least able to pay it, defying any concept of fairness or economic inventiveness. This is The Tax on Being Different.
My introduction to this Tax started with the story of José Zamora. A few years ago, José wrote a blog post claiming that he was submitting over a hundred resumes a week without any response. So, José dropped the “s” out of his name and, so he claimed, everything changed. "Joe Zamora" was in demand in a way "José" could only envy.
Though José's claims might seem exaggerated, there is ample research suggesting that his experience is real. Given identical resumes, controlled studies find that
- male names are preferred of over female,
- "caucasian" names are preferred to "african american",
- bias exists in simple email introductions, and
- bias persists even for matching gender and ethnicity.
Given this large and growing body of research, the classic claim "I had to work twice as hard to get where I am" takes on a whole new character. In fact, a recent study showed that scientists from underrepresented populations did more innovative research and yet were less cited than their majority peers. Unfortunately, the broader world can be very suspicious of “research” that counters their personal beliefs. (Finger quotes being an important tool in undermining the credibility of valid research.) Beyond the skepticism, even if one accepts this research, it doesn’t actually tell us the real-world impact of this bias. To understand the Tax we need to quantify the cost for José to achieve the same career outcomes as Joe for the same work.
Fortunately, I had access to a powerful data set of 122 million professional profiles collected by the HR Tech company Gild, where I was Chief Scientist. From that data, I pulled out every single José and Joe (“Joe” only–not “Joseph” or any other variant). In the end, I found 151,604 Joes and 103,011 Josés, working professionals in the US and Canada. This set certainly lacks many people of both names who lack digital footprints on sites like LinkedIn, Facebook, Twitter, StackOverflow, or the 100 other sites from which Gild collected public data.
Even with just the simplest of statistics some interesting stories emerged. For example, José is more likely to become an MD than Joe, but Joe is four times as likely to reach the C-suite. But these simple comparisons cannot quantify the Tax because they do not control for the quality of work done by each individual.
To make a fair comparison between Joe and José I leveraged two things: Gild’s technology to score work performance and the economic concept of signalling cost. The former is a technology we developed to analyze thousands of data points that are predictive of quality of work (as opposed to quality of resume). The latter, signalling cost, has a classic story in the peacock's tail. Although a male peacock's tail affords it no real survival advantage, it is a signal of the male's fitness. The idea goes, since only the most fit males can waste energy on the biggest tails, females use it implicitly as a proxy for true fitness (much as many recruiters rely on Ivy League degrees). I leveraged the signalling cost concept to ask, "What does it cost José to achieve the same career outcomes as Joe?"
To further improve the accuracy of my estimates I restricted the Joe vs José comparison to software developers. Comparing only within a single job vertical removes variability associated with different job requirements. It turns out we still have over 7,000 Joe’s and nearly 5,000 José’s in our dataset, thousands of real people writing code for a living. I computed the probability that each was promoted from "software engineer" to "senior software engineer" (generic terms used to cover a broad range of related job titles) controlling for quality of work. I began by looking at one specific signal: college degrees.
To be equally likely to get a promotion, José needs a masters degree or higher compared to Joe with no degree at all. This means that, for similar work, José needs six additional years of education. That’s 6 years of tuition and six years opportunity cost, specifically missed earnings as a software engineer. This is the Tax on being different, and for José the Tax is $500,000-1,000,000 over his lifetime.
If that number sounds enormous, it should. Three-quarters of a million dollars is a huge sum. Although my methodology is only approximative and not a formal experiment, it reveals diverse sources of bias which accumulate to huge effect. As I looked into the many ways the x is levied, it is easy to see how such large numbers accumulate. José not only needs higher degrees, but he also needs them from more prestigious schools. Additionally, he must work at more prestigious companies for longer periods before opportunities equalize. Finally, José often needs to be more broadly exceptional, with accomplishments and personal histories which set him well apart from his peers, such as notable awards or unique backgrounds.
Of course, the Tax comes with compounding interest. Overtime, Joe receives few job offers, bonuses, raises, and project opportunities. It’s the little obstacles, year after year—undervalued by one percent each day. Though any given instance the bias might be small, they compound over time, even over generations. Some write off evidence of bias because they only look at it in the day-to-day1, but compounded bias over a lifetime and in the entire population is profound.
If you are José growing up in the heart of Silicon Valley, wealth, power, and academic accomplishment surrounds you. In a region that often considers itself to be the world’s greatest meritocracy, it seems irrational for an intelligent and capable teenage boy to “drop out” of the system, and yet these seemingly irrational decisions are shockingly common. High-performing students of color dropout of school at disturbingly high rates despite reporting feeling entirely capable and qualified. In the context of the Tax, though, this seeming irrational behavior takes on a completely new light. José isn’t being irrational; he is rationally looking at a world in which he will work twice as hard for less recognition and learning that his hard work will not pay off. It’s not just a matter of figuring out the right marketing strategy to make kids understand the value of an education. It’s about creating schools and companies where the value of a student’s investment in their own human capital will be fully and fairly realized.
After diving into José's story, I immediately applied the same analysis to other groups. Female software engineers in America typically need a Master’s degree to compare equally with male's bachelor’s degree. The difference is not as stark as for José, but it still means the women pay a Tax of $100,000-300,000 just for a chance at the same career outcomes. Just as with José we see the Tax on being different having profound real-world consequences2.
Research has shown that women leave the business world rather than pursue executive positions at much higher rates than men. They viewed positions of leadership as “equally attainable” yet “less desirable”, full of “conflict” and “sacrifice”. Some have taken this to mean women have less interest in being executives, but the Tax shows that like José, women’s personal investment in their careers are being undervalued. With disincentives like these, the choice to leave the career ladder becomes rational and universal. Their male counterparts would also leave, should similar career attrition have a similar disincentive. People won’t follow a pipeline which won’t take them anywhere.
One policy proposal to reduce the wage gap, and therefore the Tax, is the passing laws to bar asking women about previous salaries. Because women are systematically paid less, basing negotiations of future salary on past wages harms women. Following new laws around the US, recent research seemed to suggest that this is true, but a hard look at the findings tells a different story. The positive effect was entirely driven by older women at high stages of their careers. They were negotiating a salary based on their long individual history in the job market. For younger women without extensive work histories, bias dominated and the new laws actually reduced their earnings. With less data to correct people's biases, the Tax actually increased3.
The Tax is not unique to America. In fact, looking at the Tax on women in the east Asian tech industry shows some strong cultural differences. Women often need to have PhDs to be equally competitive for jobs which do not require them, and progression up through the industry is slower and requires more “brand name” resumes. For them the Tax can rise to between $800,000-$1,200,000. Fascinatingly, in conversations with recruiters and managers at one of the companies I analyzed in detail, they are seemingly completely unaware of the bias. They swore that they hired equal numbers of women without PhDs for those roles. I think they believed it…right up until I showed them that they’d never hired a woman without a PhD for their top technical roles.
There is also evidence that the Tax is superlinear. That is to say that intersectionality, the bridging of two different minority identities, comes with a greater Tax than either identity in isolation4. For example, the average professional Black woman pays more Tax than white woman and Black man combined. Lesbians earn less for being women and so do their spouses.
Even differences which are not necessarily immediately observable can lead to a measurable Tax. For example, the cost for a gay professional in the UK compared to straight colleagues is roughly $70,000. While this is quite modest compared to the groups described above, imagine if we randomly selected one out of every ten boys and garnished their family’s earnings $5000/year for 14 years. This would meaningfully harm those families and their children. If fact, we were able to measure a subtle difference between gay men in the US growing up in inclusive communities and those that didn't. Even if both spend their professional careers in relatively inclusive NYC, the kid from Austin appears to experience a smaller Tax than the one from Dallas.
The Tax on being different provides a very different face on issues of bias and discrimination. The Tax is largely implicit. People needn't act maliciously for the Tax to be levied. In fact, at its heart it is (to a scientist like me) a laudable idea: “prove it to me”. The problem is that we are requiring substantially different levels of proof without realizing it. "I'll hire José... when he's sufficiently proved his value." Imagine how many Josés gave up long before that point in the process, disincentivized by the enormous Tax they sensed ahead of them.
I once served on a board that had a pronounced lack of women and Black or brown directors. Several directors joined with me to insist on a slate of only underrepresented board candidates.This produced a strong reaction from one director in particular who said that such a quota was insulting to candidates. I responded that he had entirely misunderstood; the quota wasn’t for the candidates. They were already qualified. It was for us. We had failed, not the candidates.
The most important things to understand about the Tax on being different is that we all pay it. We all pay this Tax collectively in lost potential, lost productivity, and lost lives. Companies and communities that fail to recognize and elicit the full potential of their workforce will not remain competitive. In modern economies, as automation increases, the value of human capital will increasingly come only from self-motivated, adaptable problem-solvers. This value is lost when we fail to recognise the fair value of others. While there are costs in addressing bias5, the medium- and long-term gains represent massive untapped potential in the economy, potential that might even eclipse the Tax itself.
This isn’t just a social justice issue. It doesn’t fall under “corporate responsibility”. The Tax is a drag on the economy and to the growth of our companies. Stop making your employees pay it. Stop paying it yourselves. Never accept “the pipeline” as an excuse for your talent problems. Discrimination isn’t done by villains. It’s done by humans, by us. We haven’t failed because we are biased. We fail when we do nothing about it.
See also: the Financial Times and HR Magazine.
