How is it that public health has delivered on its promise to improve the lives of millions, while failing to resolve the dramatic health disparities of people of color in the US? And what can the movement for tech governance learn from these failures?
Through 150 years of public institutions that serve the common good through science, public health has transformed human life. In just a few generations, some of the world’s most complex challenges have become manageable. Millions of people can now expect safe childbirth, trust their water supply, enjoy healthy food, and expect collective responses to epidemics. In the United States, people born in 2010 or later will live over 30 years longer than people born in 1900.
Inspired by the success of public health, leaders in technology and policy have suggested a public health model of digital governance in which technology policy not only detects and remediates past harms of technology on society, but also supports societal well-being and prevents future crises. Public health also offers a roadmap—professions, academic disciplines, public institutions, and networks of engaged community leaders—for building the systems needed for a healthy digital environment.
Yet public health, like the technology industry, has systematically failed marginalized communities in ways that are not accidents. Consider the public health response to Covid-19. Despite decades of scientific research on health equity, Covid-19 policies weren’t designed for communities of color, medical devices weren’t designed for our bodies, and health programs were no match for inequalities that exposed us to greater risk. As the US reached a million recorded deaths, Black and Brown communities shouldered a disproportionate share of the country’s labor and burden of loss.
The tech industry, like public health, has encoded inequality into its systems and institutions. In the past decade, pathbreaking investigations and advocacy in technology policy led by women and people of color have made the world aware of these failures, resulting in a growing movement for technology governance. Industry has responded to the possibility of regulation by putting billions of dollars into tech ethics, hiring vocal critics, and underwriting new fields of study. Scientific funders and private philanthropy have also responded, investing hundreds of millions to support new industry-independent innovators and watchdogs. As a cofounder of the Coalition for Independent Tech Research, I am excited about the growth in these public-interest institutions.
But we could easily repeat the failures of public health if we reproduce the same inequality within the field of technology governance. Commentators often criticize the tech industry’s lack of diversity, but let’s be honest—America’s would-be institutions of accountability have our own histories of exclusion. Nonprofits, for example, often say they seek to serve marginalized communities. Yet despite being 42 percent of the US population, just 13 percent of nonprofit leaders are Black, Latino, Asian, or Indigenous. Universities publicly celebrate faculty of color but are failing to make progress on faculty diversity. The year I completed my PhD, I was just one of 24 Latino/a computer science doctorates in the US and Canada, just 1.5 percent of the 1,592 PhDs granted that year. Journalism also lags behind other sectors on diversity. Rather than face these facts, many US newsrooms have chosen to block a 50-year program to track and improve newsroom diversity. That’s a precarious standpoint from which to demand transparency from Big Tech.
How Institutions Fall Short of Our Aspirations on Diversity
In the 2010s, when Safiya Noble began investigating racism in search engine results, computer scientists had already been studying search engine algorithms for decades. It took another decade for Noble’s work to reach the mainstream through her book Algorithms of Oppression.
Why did it take so long for the field to notice a problem affecting so many Americans? As one of only seven Black scholars to receive Information Science PhDs in her year, Noble was able to ask important questions that predominantly-white computing fields were unable to imagine.
Stories like Noble’s are too rare in civil society, journalism, and academia, despite the public stories our institutions tell about progress on diversity. For example, universities with lower student diversity are more likely to put students of color on their websites and brochures. But you can’t fake it till you make it; cosmetic diversity turns out to influence white college hopefuls but not Black applicants. (Note, for instance, that in the decade since Noble completed her degree, the percentage of PhDs awarded to Black candidates by Information Science programs has not changed.) Even worse, the illusion of inclusivity can increase discrimination for people of color. To spot cosmetic diversity, ask whether institutions are choosing the same handful of people to be speakers, award-winners, and board members. Is the institution elevating a few stars rather than investing in deeper change?