The Second Wave of Algorithmic Accountability

Frank Pasquale –

Over the past decade, algorithmic accountability has become an important concern for social scientists, computer scientists, journalists, and lawyers. Exposés have sparked vibrant debates about algorithmic sentencing. Researchers have exposed tech giants showing women ads for lower-paying jobs, discriminating against the aged, deploying deceptive dark patterns to trick consumers into buying things, and manipulating users toward rabbit holes of extremist content. Public-spirited regulators have begun to address algorithmic transparency and online fairness, building on the work of legal scholars who have called for technological due process, platform neutrality, and nondiscrimination principles.

This policy work is just beginning, as experts translate academic research and activist demands into statutes and regulations. Lawmakers are proposing bills requiring basic standards of algorithmic transparency and auditing. We are starting down on a long road toward ensuring that AI-based hiring practices and financial underwriting are not used if they have a disparate impact on historically marginalized communities. And just as this “first wave” of algorithmic accountability research and activism has targeted existing systems, an emerging “second wave” of algorithmic accountability has begun to address more structural concerns. Both waves will be essential to ensure a fairer, and more genuinely emancipatory, political economy of technology.

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The Uneasy Case Against Occupational Licensing (Part 2)

Frank Pasquale and Sandeep Vaheesan–

Successful ideological entrepreneurs change policy-makers’ focus and their presumptions. Those on the right, in particular, have been very effective at shifting attention from core confrontations of capital and labor to peripheral conflicts among laborers. We see this repeatedly in inequality policy, where fundamental tensions between capital and labor are ignored, obfuscated, or trivialized by a tidal wave of technocratic reframing. Continue reading

The Uneasy Case Against Occupational Licensing (Part 1)

Frank Pasquale & Sandeep Vaheesan–

Obama-era technocrats and Trump cronies may not agree on much, but they have made common cause against occupational licensing. That focus undermines important social objectives while obscuring far more important problems in the labor market. In this post, we cover the basics of licensing, and then reframe current attacks on it. In our next post, we will explain why licensing’s mix of consumer protection and labor market stabilization is a legitimate policy option for a wide range of occupations.

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The dark side of the ‘data-driven’

Frank Pasquale –

In her fascinating new book Automating Inequality, Virginia Eubanks recounts that the first “big data” set in the United States “was the Eugenics Records Office in Cold Spring Harbor. It was the public arm of the eugenics movement.” While the systematic collection of data has underpinned many important initiatives, it also has a dark side. Expect to see that dark side re-emerge with a vengeance in the next few years, as many American states intensify their surveillance of already disadvantaged groups.

Are there forms of knowledge that the state—or even university researchers—should not aspire to attain? Privacy law is meant to empower us with zones of thought and experience that no one can access without permission. Another branch of law, governing human subjects research, ensures that experimenters obtain consent before gathering data about individuals. As a member of the Council on Big Data, Ethics, and Society, I have thought and written about the types of data corporations and states should be able to gather about individuals, and the power relationships that data gathering entailed.benthams-panopticon-copy.jpg

Like disputes over free expression, the politics of data gathering for social science research is becoming a fraught area for progressives. For some, knowledge is an intrinsic good. Research of all stripes is a way of better understanding ourselves and our world. But there is another, more Foucauldian perspective: Where does the burden of scrutiny fall? What complicity does a social scientist have with the regime that provides data? The construction of what counts as “success” or “failure” in a given study is a highly political decision. A particular focus on some data or metrics comes at the cost of an exclusion or devaluation of others (akin to the “jurispathic” judgments Robert Cover recognized). All these questions will be critical as America’s laboratories (or meth labs) of democracy concoct innovative ways of denying health care to the poor, and ask social scientists to study “what works” in health policy.

Evaluating the Costs of Program Evaluation

The Trump Administration recently announced an intent to grant states permission to condition Medicaid benefits on work requirements (via Section 1115 of the Social Security Act). Former CMS Administrator Andy Slavitt immediately condemned the move. Activists were even more outraged. Journalists chronicled the many ways the work requirements were likely to worsen health outcomes, while burdening the vulnerable with paperwork and bureaucratic hurdles. New state “flexibility” will translate into cruel cutbacks for the disabled (who now may be denied transportation benefits).   Continue reading