Author: Frank Pasquale

University of Utah Conference on Precision Medicine

Via Leslie Francis, news of a great conference at the University of Utah on precision medicine on Dec. 1 and 2. It will be livestreamed:

The federal Precision Medicine Initiative (PMI) announced in 2015 will be the largest study of human genetics and health in history. With a planned cohort of one million Americans, the PMI promises to increase our understanding of the genetic basis of disease and forge the way for new diagnostic and therapeutic innovations. The PMI is linked to another ambitious national initiative, Vice President Joe Biden’s “Cancer Moonshot,” which hopes to accelerate the cure for cancer using big data and precision oncology techniques. Though the technology to undertake these monumental projects exists today, many scientific, legal, economic, and ethical questions remain. This one and a half day symposium at the University of Utah will host leading national experts in medicine, bioinformatics, law, policy and ethics who are tackling the major questions raised by precision medicine, the PMI, and the Cancer Moonshot.

I wish I could watch, but I will be speaking at another conference. Best wishes to the Utah group!

Post-Neoliberal Higher Education Policy

The Obama Administration made at least two major contributions to higher education policy. It cracked down on some for-profit colleges, taking on a consumer protection role largely missing from the Bush years. Donald Trump is unlikely to continue that initiative, and may roll it back.

Obama also encouraged income-based repayment (IBR) of student loans. It appears that “the repayment plan proposed by candidate Trump is not too far from the current repayment plans already in existence”–but few know exactly how the policy will play out once a new set of think tankers and lobbyists take over the Department of Education (DOE).

I surveyed higher education finance policy in 2015, in a piece for the Atlantic. I felt at the time that the Sanders plan was by far the best, and that Clinton’s plan could lead incrementally to a better higher ed landscape. However, over the summer I co-authored a longer article on the foundations of higher ed policy with Luke Herrine, Legal Coordinator of the Debt Collective. Herrine does both scholarly and advocacy work. In a project organizing for-profit college students to obtain debt discharges, he saw some of the worst bureaucratic failures of the current DOE.

The same concerns I’ve expressed about health policy also dog education policy. Extreme complexity and baroque targeting of aid make it hard to sustain political support. Just as private insurers have done as much to undermine as to implement the ACA, the servicers at the core of DOE’s student loan management have serially failed the students they are supposed to help.
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Rebuilding Health Care Policy from the Ground Up


Campaign Flier from the Wright Patman Archives (via Matthew Stoller)

The signature progressive initiative of early 21st century America–the Affordable Care Act–is about to be gutted.  In 2009, I agonized about whether to support it. In the last paragraph of a bloated blog post, I concluded:

By passing this reform bill, Democrats will jettison whatever “populist” credentials they once had, opting instead for an early-twentieth-century “progressive” vision of technocratic alliance between corporate and government experts. . . . We’ll commence an endless argument (read: notice and comment rulemaking and subsequent administrative adjudications) over what constitutes an adequate baseline of coverage. . . . But the fundamental victory of reform–the national commitment that no one should have to choose between death or bankruptcy when confronted with a serious illness–will also endure. The tragic paradox is that the Democrats can only achieve this great cultural and ideological victory by becoming identified with the very interests that only they are willing to confront.

I was right about a few things: it was a Pyrrhic victory, the backlash was brutal, and virtually every indignity or imposition concocted by private insurers in the past seven years has been blamed on “Obamacare.” But I was wrong about the most important points. The rulemaking and adjudications will end. The Trump/Ryan/McConnell approach to health care will leave Obamacare in the dustbin of history. And when it does, it will impose on millions of Americans exactly the situation they faced pre-ACA: choose between death or bankruptcy when confronted with a serious illness.


In October, Larissa MacFarquhar published a thoughtful essay on “The Heart of Trump Country.” One supporter of the President-elect said:  “When you hear about illegal aliens getting benefits and you have people here starving to death and can’t get nothing, it’s just a slap in the face. When you start talking about bringing in refugees and when they get here they get medical and dental and they get set up with some funds—what do we get?” Here’s Obamacare’s answer:

Under the terms of the ACA, if you are unemployed, or if your employer’s insurance is unaffordable (defined as an individual plan (not a family plan) costing you over 9.5% of income), you can buy insurance on the exchange. You can choose plans from one of four precious metal tiers (bronze, silver, gold, and platinum), with varying actuarial values (60 to 90%). You’ll pay premiums, but you’ll also get sliding scale subsidies based on how high your income is above the poverty level. You will probably also need to pay co-pays, coinsurance (a percentage of each bill), and deductibles, up to some percentage of your income specified by statutory out-of-pocket maximums. (Just be sure not to incur out-out-network costs that don’t count toward out-of-pocket maximums.)

But you can get cost-sharing subsidies to cover some of that expense, based on a sliding scale slightly different than the premium assistance tax credit scale. Just be sure to shop carefully on the exchange, because some plans have narrow networks–that is, they may not cover the physicians or hospitals you normally use. In fact, you may have to drive 20 or 50 miles to find a physician in the network–the rules on network adequacy can be hazy. Note also that, in a narrow network, if you have a surgery, it’s possible out-of-network physicians or other personnel may attend, and you could be on the hook for the whole amount they charge–unless your state has a “no surprise billing” law.

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Rethinking the Political Economy of Automation

The White House recently released two important reports on the future of artificial intelligence. The “robot question” is as urgent today as it was in the 1960s. Back then, worry focused on the automation of manufacturing jobs. Now, the computerization of services is top of mind.

At present, economists and engineers dominate public debate on the “rise of the robots.” The question of whether any given job should be done by a robot is modeled as a relatively simple cost-benefit analysis. If the robot can perform a task more cheaply than a worker, substitute it in. This microeconomic approach to filling jobs dovetails with a technocratic, macroeconomic goal of maximizing some blend of GDP and productivity.

In the short run, these goals appear almost indisputable–the dictates of market reason. In the long run, they presage a jobs crisis. As Michael Dorf recently observed, even though “[i]t is possible that new technologies will create all sorts of new jobs that we have not imagined yet,” it is hard to imagine new mass opportunities for employment. So long as a job can be sufficiently decomposed, any task within it seems (to the ambitious engineer) automatable, and (to the efficiency-maximizing economist) ripe for transferring to software and machines. The professions may require a holistic perspective, but other work seems doomed to fragmentation and mechanization.

Dorf is, nevertheless, relatively confident about future economic prospects:

Standard analyses…assume that in the absence of either socialism or massive philanthropy from future tech multi-billionaires, our existing capitalist system will lead to a society in which the benefits of automation are distributed very unevenly. . . . That’s unlikely. Think about Henry Ford’s insight that if he paid his workers a decent wage, he would have not only satisfied workers but customers to buy his cars. If the benefits of technology are beyond the means of the vast majority of ordinary people, that severely limits the ability of capitalists and super-skilled knowledge workers to profit from the mass manufacture of the robotic gizmos. . . . Enlightened capitalists would understand that they need customers and that, with automation severely limiting the number of jobs available, customers can only be ensured through generous government-provided payments to individuals and families.

I hope he is right. But I want to explore some countervailing trends that militate against wider distribution of the gains from automation:
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The Phantom Industrial Policy of the Beltway’s Favorite Health Cost Cutters

A few weeks ago, I spoke on artificial intelligence in health care at the AI Now Conference. I focused on the distinction between substitutive automation (which replaces human labor with software or robots) and complementary automation (which deploys technology to assist, accelerate, or improve humans’ work). I developed three cases where complementary automation ought to be preferred: where it produces better outcomes; in sensitive areas like targeting persons for mental health interventions; and to improve data gathering. Law and policy (ranging from licensure rules to reimbursement regs) could help assure that the health care sector pursued complementary automation where appropriate, rather than chasing the well-hyped narrative of robot doctors and nurses.

The pushback was predictable. Even if complementary automation is better now, shouldn’t our policy reward firms that try to eliminate ever more labor costs? Doesn’t *everyone* agree that the US spends too much on health care–and isn’t technology the best way of reducing that spending? Let me try to address each of these views, boiling down some perspectives from a longer, academic article.

A Policy at War with Itself

There is a troubling tension at the heart of US labor policy on health care and automation. Numerous high-level officials express grave concerns about the “rise of the robots,” since software is taking over more jobs once done by humans. They also tend to lament growth in health care jobs as a problem. In an economy where automation is pervasive, one would think they would be thankful for new positions at hospitals, nursing homes, and EHR vendors. But they remain conflicted, anxious about maintaining some arbitrary cap on health spending.

Politico reporter Dan Diamond encapsulated this conflict in his recent article, “Obamacare: The Secret Jobs Program”–and he leaves no uncertainty about which side he thinks is right:
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Social Media for Scholars

For about a year now, Nic Terry and I have been hosting “The Week in Health Law” podcast. (We did miss a few weeks–so we’re actually more like “This 8.3 Days in Health Law”–but we’re pretty reliable!) We interview law professors, social scientists, and other experts, mainly from the US, though with some international presence. We recently convened a “meta-podcast” with 3 past show guests (and the editor of Pharmalot, an influential pharma industry blog) on the importance of social media presence for engaged academics. Our show notes also link to some good guides from other scholars. Like the “No Jargon” podcast of the Scholars Strategy Network, we try to bring informed commentary on complex ideas (like agency guidance on wellness programs) to a broad audience. We’ve received positive feedback from around the world, and I’m often surprised by the range of people who are tuning in (from hospital administrators to bar leaders to general counsel).

I just wanted to add one cautionary note to the emerging commentary on engaged scholarship and social media. I often see participation in blogs, podcasts, or Twitter framed in corporate or neoliberal discourse–the need to “build a brand,” “increase citations,” “leverage a network,” and so on. Even I engage in that in the podcast when I discuss altmetrics. But at its core, the scholarly identity is a very different one than the metricized self of performance optimization. Our best conversations feature a critical distance from the topics at hand and even from the ever more voluminous research apparatus around them. They highlight, rather than gloss over, inevitable conflicts of values that emerge once once tries to apply banalities like the “triple aim” in specific settings. There is a deep interest in an empirical research, and a sober awareness of its limits. (Our discussion with Scott Burris on policies like bike helmet laws is one very good example of this.)

The best moments of the podcast (contrasted with the impoverished neoliberal discourse often used to justify participation in engaged scholarship) highlight two very different meanings of “professionalism” now at work in our culture. The professionalized scholar is often a cite-generator and grant-grubber, more concerned with the external indicia of achievement than the intrinsic value of research they are meant to merely validate or support. But if we consider the academy as a profession, we realize the extraordinary importance of its partial autonomy from both market and state. It exists to create a space for research and conversations that are impossible to monetize immediately (or maybe ever), and which have not been specifically approved by political institutions.

As the state increasingly becomes a cat’s paw of market forces, and market forces themselves are engineered by a shrinking and short-sighted financial elite, preserving the residual autonomy of professions is more important than ever. I hope that future discussions of engaged scholarship focus more on its potential to advance solidarity among those committed to an independent academy–not one keen on ever-preciser rankings of its members, or defensive about proving its value in economic terms that are themselves of questionable utility.

Scholarship and Mid-Career Self-Assessments: A Brief Reflection on Simkovic’s What Can We Learn from Credit Markets?

Chris J. Walker has written a very helpful series of posts for young professors on “how to become a voice in one’s field.” The last addressed one of the hardest issues: “Am I Asking the Right Questions?” Academic freedom at a professional school comes with serious responsibilities: to choose field(s), to apply methodology well, and to try to establish the importance of one’s findings among one’s peers and (increasingly) among educated publics, as an engaged academic. Both Walker and Michael Rich offer wise perspectives on the dilemmas that inevitably come up during thoughtful reflection on these responsibilities, focusing on a process of discernment.

I also think that we can learn a great deal from the content of successful scholars’ inquiry. Usually, researchers only undertake this type of self-reflection when applying for jobs and preparing research agendas (a mostly private process), or at the end of a career (when a long list of accomplishments may seem too daunting to be relatable to younger peers). But winners of the ALI Young Scholars Medal appear to get invited to give a public talk on their work at an earlier stage of inquiry. Mike Simkovic (whose work I’ve previously praised here) gave such an address in May.

The talk is focused on the questions that led Simkovic to research credit markets. His work helped explain some puzzling aspects of personal finance–for example, why harsh restrictions on bankruptcy imposed in the mid-2000s did not lead to a cheapening of credit. His findings are revealing: consolidation in the credit card industry, as well as confusing contractual terms, helped dominant firms keep the resulting profits, rather than compete them away. As of 2016, even The Economist has caught up to this challenge to laissez-faire orthodoxy–but at the time it was made, complacent assumptions about market efficiency were dominant.

From that inquiry, Simkovic describes a chain of puzzles that led him to challenge widely held preconceptions in corporate, education finance, and tax law. It’s an engaging documentation of a particularly fruitful and insightful trajectory in inquiry.

I recently proposed a paper to the MLA’s annual conference entitled “Beyond the False Certainties of Impact Factors, Altmetrics, and Download Counts: Qualitative & Narrative Accounts of Scholarship.” It arose out of my dissatisfaction with the metricization of accomplishment. As citation counts proliferate, accumulating the ersatz currency of reputational quantifications threatens to overwhelm the real purpose of research–just as financialization has all too often undermined the productive functions of the economy.

Traditional modes of assessment (including tenure letters and festschrift tributes) are an alternative form of evaluation. And an essay like Simkovic’s is an example of a type of self-evaluation that should become more popular among scholars at certain career milestones (like tenure, appointment to full professor or senior lecturer, and, say, every 5 or 10 years thenceforward.) We need better, more narrative, mid-career assessments of the depth and breadth of scholarly contributions. Such qualitative modes of evaluation can complement the quantification-driven metrics now ascendant in the academy.

Facebook is More Like a Cable Network than a Newspaper

As I worried yesterday, Facebook’s defenders are already trying to end the conversation about platform bias before it can begin. “It’s like complaining that the New York Times doesn’t publish everything that’s fit to print or that Fox News is conservative,” Eugene Volokh states.

Eight years ago, I argued that platforms like Google are much more like cable networks than newspapers–and should, in turn, be eligible for more governmental regulation. (The government can’t force Fox News to promote Bernie Sanders–but it can require Comcast to carry local news.) The argument can be extended to dominant social networks, or even apps like WeChat.

As I note here, to the extent megaplatforms are classifiable under traditional First Amendment doctrine, they are often closer to utilities or cable networks than newspapers or TV channels. Their reach is far larger than that of newspapers or channels. Their selection and arrangement of links comes far closer to the cable network’s decision about what channels to program (where such entities, by and large, do not create the content they choose to air), than it does to a newspaper which mostly runs its own content and has cultivated an editorial voice. Finally, and most importantly, massive internet platforms must take the bitter with the sweet: if they want to continue avoiding liability for intellectual property infringement and defamation, they should welcome categorization as a conduit for speech, rather than speaker status itself.

Admittedly, if there is any aspect of Facebook where it might be said to be cultivating some kind of editorial voice, it is the Trend Box. It is ironic that they’ve gotten in the most trouble for this service, rather than the much more problematic newsfeed. But they invited this trouble with their bland and uninformative description of what the Trend Box is. Moreover, if the Trend Box is indeed treated as “media” (rather than a conduit for media), it could betoken a much deeper challenge to foundational media regulation like sponsorship disclosures–a topic I’ll tackle next week.

Platform Responsibility

Internet platforms are starting to recognize the moral duties they owe their users. Consider, for example, this story about Baidu, China’s leading search engine:

Wei Zexi’s parents borrowed money and sought an experimental treatment at a military hospital in Beijing they found using Baidu search. The treatment failed, and Wei died less than two months later. As the story spread, scathing attacks on the company multiplied, first across Chinese social networks and then in traditional media.

After an investigation, Chinese officials told Baidu to change the way it displays search results, saying they are not clearly labeled, lack objectivity and heavily favor advertisers. Baidu said it would implement the changes recommended by regulators, and change its algorithm to rank results based on credibility. In addition, the company has set aside 1 billion yuan ($153 million) to compensate victims of fraudulent marketing information.

I wish I could include this story in the Chinese translation of The Black Box Society. On a similar note, Google this week announced it would no longer run ads from payday lenders. Now it’s time for Facebook to step up to the plate, and institute new procedures to ensure more transparency and accountability.

A Social Theory of Surveillance

LocksBernard Harcourt’s Exposed is a deeply insightful analysis of data collection, analysis, and use by powerful commercial and governmental actors.  It offers a social theory of both surveillance and self-exposure. Harcourt transcends methodological individualism by explaining how troubling social outcomes can be generated by personal choices that each seem rational at the time they are made. He also helps us understand why ever more of daily life is organized around the demands of what Shoshanna Zuboff calls “surveillance capitalism:” intimate monitoring of our daily lives to maximize our productivity as consumers and workers.

The Chief Data Scientist of a Silicon Valley firm told Zuboff, “The goal of everything we do is to change people’s actual behavior at scale. When people use our app, we can capture their behaviors, identify good and bad behaviors, and develop ways to reward the good and punish the bad. We can test how actionable our cues are for them and how profitable for us.” Harcourt reflects deeply on what it means for firms and governments to “change behavior at scale,” identifying “the phenomenological steps of the structuration of the self in the age of Google and NSA data-mining.”

Harcourt also draws a striking, convincing analogy between Erving Goffman’s concept of the “total institution,” and the ever-denser networks of sensors and training (both in the form of punishments and lures) that powerful institutions use to assure behavior occurs within ranges of normality. He observes that some groups are far more likely to be exposed to pain or inconvenience from the surveillance apparatus, while others enjoy its blandishments in relative peace. But almost no one can escape its effects altogether.

In the space of a post here, I cannot explicate Harcourt’s approach in detail. But I hope to give our readers a sense of its power to illuminate our predicament by focusing on one recent, concrete dispute: Apple’s refusal to develop a tool to assist the FBI’s effort to reveal the data in an encrypted iPhone. The history Harcourt’s book recounts helps us understand why the case has attracted so much attention—and how it may be raising false hopes.

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