What’s missing from the push to diversify tech
Focusing on hiring pipelines or career pathways alone won’t solve tech’s diversity and inclusion problems. Here’s what will.
Last year, in response to Black Lives Matter, many US organizations published diversity statements and made bold claims about fostering social change. As Black scholars in computing, we saw these statements and pledges as reactionary and largely ineffective.
Corporate America pledged $50 billion to address racial justice but allocated only a fraction of a percent of those funds to direct grants, the best way to bring about systemic change. Meanwhile, at least 230 higher-education institutions issued statements within two weeks of George Floyd’s murder. Many mentioned solidarity, equality, and greater inclusion, but only one in 10 included concrete action items to address racial issues.
The track record of these institutions does not engender confidence that they will follow through on whatever promises they did make. There is little accountability, and no way to assess whether these commitments have actually improved the lives and livelihoods of Black people.
Diversity and inclusion (especially of Black people) can improve product development, spur innovation, and spark creativity and entrepreneurship, all of which drive the nation’s economy. Research shows that more diverse teams are more innovative and generate more revenue.
We often hear the path to a technology career described as a pipeline. Most diversity efforts in our field have focused on getting more people from diverse backgrounds into this pipeline. And yet representation remains stubbornly low. Between 2014 and 2020, the proportion of Black and Hispanic tech professionals at Facebook increased by less than two percentage points.
Why? The pipeline metaphor ignores the realities of racism, classism, and sexism faced by those historically excluded from technology careers. Individuals who leak out are often deemed deficient. This kind of thinking screams: “‘Fix’ the people and not the system.”
Enter the “pathway” model, an alternative to the pipeline metaphor. Pathway advocates try to create multiple entry points that can lead someone to a technology career. The idea is that people will flow in from other fields, such as engineering, the arts, mathematics, and even the humanities. One way to promote this flow is for two-year and four-year schools to make it easy for people to start in one program and finish in a different one.
Even when pathways provide more entry points, getting through remains challenging, particularly for minorities in America. One still has to be familiar with the opportunities for academic success and career readiness—and aware of the barriers that can stand in the way. Those vary between schools, and even between departments within the same school. And students must also be able to apply that knowledge to navigate antiquated processes and complex power structures.
The question is, what would be better? We advocate for an ecosystem approach in which many organizations work together to address the lack of representation in tech. The tech ecosystem should involve K–12 schools, higher-education institutions, companies, nonprofits, government agencies, and venture capitalists. Public-private partnerships could help design environments that would be inclusive from the time people start their education to the day they finish their careers.
This might require us to rebuild systems like gateway mathematics courses (classes such as pre-calculus that students must pass in order to continue their program of study) and registration holds (which prevent a student from registering for classes until tuition and fees are fully paid). These systems slow student progress and perpetuate disparate outcomes.
Universities and technology companies could provide professional development opportunities for students from underrepresented groups. But these organizations would have to first change their own cultures to be more inclusive. That means reimagining recruitment practices, which typically rely on professional networks and result in a homogeneous pool of applicants, and addressing sources of algorithmic bias, such as automated résumé screeners that select candidates from particular schools and avoid those with ethnic-sounding names.
Organizations and fields of study that adopt this approach will foster excellence, innovation, and creativity. Georgia State University is a good model. The university has eliminated achievement gaps by introducing meta-majors that students select when they enroll. A biology major who chooses a meta-major like STEM takes classes together with students who are pursuing careers in other STEM fields, like medicine or math. Today, African-American and Hispanic students at Georgia State graduate at the same rate as white students.
Ecosystems depend on both universities and companies to go beyond diversity statements. What we need is sustainable, intentional change. Donating money to a cause can help, but it must be paired with policies that can make technology more equitable.
Most important, we must hold today’s leaders accountable by implementing policies and procedures that emphasize transparency, compliance, and enforcement. The best way to fix systems that benefit some and exclude others is to address the underlying structures, not just the people.
Fay Cobb Payton is a University Faculty Scholar professor at North Carolina State University. Lynette Yarger is an associate professor and assistant dean at Pennsylvania State University. Victor Mbarika is Stallings Distinguished Scholar at East Carolina University.
Learning to code isn’t enough
Historically, learn-to-code efforts have provided opportunities for the few, but new efforts are aiming to be inclusive.
IBM wants to build a 100,000-qubit quantum computer
The company wants to make large-scale quantum computers a reality within just 10 years.
The inside story of New York City’s 34-year-old social network, ECHO
Stacy Horn set out to create something new and very New York. She didn’t expect it to last so long.
Making the world a data-driven place with the cloud
Cloud data modernizations is a key enabler to spur innovation and get real value out of your data, says PwC’s Anil Nagaraj and Microsoft’s Kim Manis.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.