Danielle Keats Citron and Mary Anne Franks, Criminalizing Revenge Porn, U of Maryland Legal Studies Research Paper No. 2014-1.
The non-consensual publication of non-newsworthy sexually graphic images deserves criminal punishment. It produces grave emotional and dignitary harms, exacts steep financial costs, and increases the risks of physical assault. A narrowly and carefully crafted criminal statute can comport with the First Amendment. Criminalization of revenge porn is necessary to protect against devastating privacy invasions that chill self-expression and ruin lives.
Renee M. Hutchins, Stop Terry: Reasonable Suspicion, Race, and a Proposal to Limit Terry Stops, U of Maryland Legal Studies Research Paper No. 2014-2
The Terry doctrine, which grants a police officer the authority to stop and frisk based on his or her reasonable suspicion rather than probable cause, was created by the Supreme Court at a time when the nation confronted a particular moment of violent racial strife. Since Terry was decided, the Supreme Court has continued to expand the reach of the doctrine — which opened the door for potential abuse. Existing data is increasingly proving that the loosening of constitutional standards is causing substantial harms to people of color nationwide. This article joins the existing scholarly discussion surrounding this decision to suggest one additional tool that might be used to address the racial impact of the Terry doctrine. In particular, this Article proposes that police authority to stop suspects on nothing more than reasonable suspicion be limited to cases in which an officer reasonably believes the suspect is engaged in something more than a mere possessory offense.
David C. Gray and Chelsea M. Jones, In Defense of Specialized Theft Statutes, U of Maryland Legal Studies Research Paper No. 2014-3
This essay is an invited contribution to a symposium hosted by the New England Law Review in celebration of Stuart Green’s important book 13 Ways to Steal a Bicycle. As we note, Professor Green’s argument is so reasonable and executed in such elegant prose, there is little call for anything other than praise. Nevertheless, in the spirit of academic exchange, we challenge Professor Green’s skepticism of specialized theft statutes. Relying on retributivist theories of criminal punishment, we argue that specialized theft statutes have an important role to play in contemporary criminal law by educating the public about the necessary commitments that must be maintained in order to facilitate emerging fields of art, technology, and commerce and by guarding the boundaries of those enterprises. In the process, we propose an “enterprise theory” of theft that justifies criminal prohibition as a tool to defend vulnerable social enterprises ranging from retail sales to copyright.
James Grimmelmann, Anarchy, Status Updates, and Utopia, U of Maryland Legal Studies Research Paper No. 2014-4
Is it possible to create online spaces without technical power? This paper argues that it is not, because of social software’s power problem. Unlike the rule of law, the rule of software is simple and brutal: whoever controls the software makes the rules. And if power corrupts, then automatic power corrupts automatically. Facebook can drop you down the memory hole; Paypal can garnish your pay. These sovereigns of software have absolute and dictatorial control over their domains.
James Grimmelmann, Indistinguishable from Magic: A Wizard's Guide to Copyright and 3D Printing,
U of Maryland Legal Studies Research Paper No. 2014-5
3D printing is a technology of such surprise and wonder that it verges on the magical. But what if 3D printers actually were magic? How would copyright law treat the wizards who used them? This Comment uses the magical analogy to make familiar doctrines strange, and a strange technology familiar. This Comment was prepared as an invited comment on Kyle Dolinsky's "CAD’s Cradle: Untangling Copyrightability, Derivative Works, and Fair Use in 3D Printing" for the 2013 Washington and Lee Student Notes Colloquium.
James Grimmelmann, The Merchants of MOOCs, U of Maryland Legal Studies Research Paper No. 2014-6
This essay examines some common arguments about what gives MOOCs their value, and finds them wanting. There is a sharp division between the features that make MOOCs exciting for education and the features that make them financially appealing to the Merchants of MOOCs.
James Grimmelmann, Big Data's Other Privacy Problem, U of Maryland Legal Studies Research Paper No. 2014-7
Big Data has not one privacy problem, but two. We are accustomed to talking about surveillance of data subjects. But Big Data also enables disconcertingly close surveillance of its users. The questions we ask of Big Data can be intensely revealing, but, paradoxically, protecting subjects' privacy can require spying on users. Big Data is an ideology of technology, used to justify the centralization of information and power in data barons, pushing both subjects and users into a kind of feudal subordination. This short and polemical essay uses the Bloomberg Terminal scandal as a window to illuminate Big Data's other privacy problem
Danielle Keats Citron and Frank A. Pasquale, The Scored Society: Due Process for Automated Predictions, U of Maryland Legal Studies Research Paper No. 2014-8
Big Data is increasingly mined to rank and rate individuals. Predictive algorithms assess whether we are good credit risks, desirable employees, reliable tenants, valuable customers — or deadbeats, shirkers, menaces, and “wastes of time.” Crucial opportunities are on the line, including the ability to obtain loans, work, housing, and insurance. Though automated scoring is pervasive and consequential, it is also opaque and lacking oversight. In one area where regulation does prevail — credit — the law focuses on credit history, not the derivation of scores from data.
Procedural regularity is essential for those stigmatized by “artificially intelligent” scoring systems. The American due process tradition should inform basic safeguards. Regulators should be able to test scoring systems to ensure their fairness and accuracy. Individuals should be granted meaningful opportunities to challenge adverse decisions based on scores miscategorizing them. Without such protections in place, systems could launder biased and arbitrary data into powerfully stigmatizing scores.