Later this year, we’ll be hosting a symposium to investigate what our changing capacities to capture, analyze, and manipulate data mean for self-government, and ask how the law must adapt to ensure the conditions for a robust democracy in this age of big data. The symposium, to be called “Data and Democracy,” is being organized by the Institute’s Senior Visiting Research Scholar Amy Kapczynski and will take place on October 15-16 at Columbia University—remotely, if necessary. It will be co-sponsored by the Law and Political Economy Project at Yale Law School.  

The symposium will focus on three areas that are both central to democratic governance and directly affected by advancing technologies and ever-increasing data collection: 1) public opinion formation and access to information; 2) the formation and exercise of public power; and 3) the political economy of data. Today, we are excited to announce that the symposium will feature 11 papers from the following scholars and technologists: 

Hannah Bloch-Wehba (Texas A&M University School of Law) will argue that the use of algorithmic decision making in governance is reflecting and amplifying previously documented weaknesses in the government transparency legal regime, and requires a shift in transparency law towards meaningful public engagement in ongoing oversight.

John Bowers (Harvard Berkman Klein Center), Elaine Sedenberg* (Harvard Berkman Klein Center), and Jonathan Zittrain (Harvard Law School) will argue that digital platforms should create archives of their past efforts to moderate content. These archives, made accessible to researchers after a waiting period, would stand to bolster work in two key research areas: efforts to understand the trajectory of platform policymaking around content moderation, and models for how harmful content appears and circulates across platforms.

danah boyd (Data & Society) and Dan Bouk (Colgate University) will focus on a series of events over the last century that have called the Census Bureau’s data practices into question. They will argue that the legitimacy of data infrastructure depends as much on social, political, and historical factors, as on the quality and accuracy of the data.

Kiel Brennan-Marquez (University of Connecticut Law) and Daniel Susser (Pennsylvania State University) will explore the rise of individual digital platforms that can obtain and process amounts of information that exceed the capacity, historically speaking, of entire markets. They will argue that governance discourse must quickly catch up to shifts in the way market structures will begin to function as a result. 

Julie Cohen (Georgetown Law) will look at the ways in which the emergence of digital platforms has reshaped the informational economy, and how preexisting methods for governing private firms that presume the market as the underlying organizational logic—including antitrust law, consumer protection law, and elements from the corporate governance toolkit—may need to be reconsidered.

Aziz Huq (University of Chicago Law) will investigate a potential paradox in proposals to regulate new technologies of analysis and prediction: These proposals presuppose a state capable of reliably and responsibly exercising new regulatory authorities, an assumption that may not be borne out in an era of weakened institutions and democratic backsliding. Huq will identify possible strategies for mitigating the harms of concentrated digital power without precipitating new forms of domination and entrenched power.

Frank Pasquale (University of Maryland Carey School of Law) will write about efforts to restrict the use of artificial intelligence technology through licensing regimes, including the broad concerns motivating calls for licensing and what kinds of uses should be allowed or banned.

Bertrall Ross (University of California, Berkeley, School of Law) and Douglas Spencer (University of Connecticut Law) will show that political campaigns’ use of increasing amounts of data about potential voters to microtarget their online messages is potentially increasing voter apathy and ignorance and exploiting voters’ lack of resources, to the detriment of legitimate elections and representative government.

Mathias Vermeulen (Mozilla Foundation) will examine tech companies’ frequent claims that privacy concerns prevent them from including certain data sets in materials that they release to the public and to researchers, such as political ad archives and initiatives like Social Science One. Looking at the European Union’s General Data Protection Regulation (GDPR) and Code of Practice on Disinformation, he will identify three new measures that legislators could implement to facilitate data sharing while safeguarding privacy.

Wendy Wagner (University of Texas School of Law) and Martin Murillo (Institute of Electrical and Electronics Engineers) will focus on the challenges to accountable administrative governance posed by the increasing use of large datasets and algorithmic models by agencies. They will discuss the ways administrative processes currently reward agencies for using models that are inaccessible to the people affected by them, and identify ways to counteract this by requiring agencies to produce comprehensible explanations of their use of algorithms.

Rebecca Wexler (University of California, Berkeley, School of Law) will look at the recent expansion of law enforcement powers to obtain data for use in prosecutions through new cross-border agreements and whether this has created asymmetry between law enforcement’s access to inculpatory data and defendants’ access to exculpatory data. She will argue that exceptions to privacy protections that enable law enforcement to access data across borders should also apply to defense investigators.

 

*Sedenberg is also a Privacy & Data Policy Manager at Facebook but is writing solely in her personal capacity.