Law Commons^™

The Role Of Ethical Principles In Ai Startups, James Bessen, Stephen Michael Impink, Robert Seamans

Faculty Scholarship

Do high-tech startups benefit from developing more ethical AI? AI startups implement policies and take actions to manage ethical issues associated with data collection, storage, and usage and adapt to the norms of their industry. This paper describes these startups' ethics-related actions, including ethical AI policy adoption, and examines how these actions relate to startup performance. We find that merely adopting an ethical AI policy (i.e., a less costly signal) does not relate to increased performance. However, there is evidence that investors reward startups that take more costly preventative pro-ethics actions, like seeking expert guidance, training employees about unconscious bias, …

Discredited Data, Ngozi Okidegbe

Faculty Scholarship

Jurisdictions are increasingly employing pretrial algorithms as a solution to the racial and socioeconomic inequities in the bail system. But in practice, pretrial algorithms have reproduced the very inequities they were intended to correct. Scholars have diagnosed this problem as the biased data problem: pretrial algorithms generate racially and socioeconomically biased predictions, because they are constructed and trained with biased data.

This Article contends that biased data is not the sole cause of algorithmic discrimination. Another reason pretrial algorithms produce biased results is that they are exclusively built and trained with data from carceral knowledge sources – the police, pretrial …

Using Artificial Intelligence In The Law Review Submissions Process, Brenda M. Simon

Faculty Scholarship

The use of artificial intelligence to help editors examine law review submissions may provide a way to improve an overburdened system. This Article is the first to explore the promise and pitfalls of using artificial intelligence in the law review submissions process. Technology-assisted review of submissions offers many possible benefits. It can simplify preemption checks, prevent plagiarism, detect failure to comply with formatting requirements, and identify missing citations. These efficiencies may allow editors to address serious flaws in the current selection process, including the use of heuristics that may result in discriminatory outcomes and dependence on lower-ranked journals to conduct …

The Role Of Data For Ai Startup Growth, James Bessen, Stephen Michael Impink, Lydia Reichensperger, Robert Seamans

Faculty Scholarship

Artificial intelligence (“AI”)-enabled products are expected to drive economic growth. Training data are important for firms developing AI-enabled products; without training data, firms cannot develop or refine their algorithms. This is particularly the case for AI startups developing new algorithms and products. However, there is no consensus in the literature on which aspects of training data are most important. Using unique survey data of AI startups, we find that startups with access to proprietary training data are more likely to acquire venture capital funding.

Toward Evidence-Based Antiracist Policymaking: Problems And Proposals For Better Racial Data Collection And Reporting, Neda Khoshkhoo, Aviva Geiger Schwarz, Luisa Godinez Puig, Caitlin Glass, Geoffrey S. Holtzman, Elaine O. Nsoesie, Jasmine Gonzales Rose

Faculty Scholarship

The study of data concerning racial and ethnic inequities and disparities allows us to better understand experiences of racism, and to see more clearly how and where racism manifests. Studying the effects of racism, in turn, allows us to more easily identify racist policies, so that we can craft antiracist interventions.

Existing race and ethnicity data collection efforts are riddled with gaps and errors, including missing and incomplete data, insufficiently disaggregated data, lack of meaningful longitudinal data, infrequently updated data, non-standardized methodologies, and other problems. These deficiencies significantly hinder evidence-based antiracist policymaking.

This policy report examines the state of racial …

Ethical Ai Development: Evidence From Ai Startups, James Bessen, Stephen Michael Impink, Lydia Reichensperger, Robert Seamans

Faculty Scholarship

Artificial Intelligence startups use training data as direct inputs in product development. These firms must balance numerous trade-offs between ethical issues and data access without substantive guidance from regulators or existing judicial precedence. We survey these startups to determine what actions they have taken to address these ethical issues and the consequences of those actions. We find that 58% of these startups have established a set of AI principles. Startups with data-sharing relationships with high-technology firms; that were impacted by privacy regulations; or with prior (non-seed) funding from institutional investors are more likely to establish ethical AI principles. Lastly, startups …

The Surprising Virtues Of Data Loyalty, Woodrow Hartzog, Neil M. Richards

Faculty Scholarship

Lawmakers in the United States and Europe are seriously considering imposing duties of data loyalty that implement ideas from privacy law scholarship, but critics claim such duties are unnecessary, unworkable, overly individualistic, and indeterminately vague. This paper takes those criticisms seriously, and its analysis of them reveals that duties of data loyalty have surprising virtues. Loyalty, it turns out, can support collective well-being by embracing privacy’s relational turn; it can be a powerful state of mind for reenergizing privacy reform; it prioritizes human values rather than potentially empty formalism; and it offers solutions that are flexible and clear rather than …

Legislating Data Loyalty, Woodrow Hartzog, Neil Richards

Faculty Scholarship

Lawmakers looking to embolden privacy law have begun to consider imposing duties of loyalty on organizations trusted with people’s data and online experiences. The idea behind loyalty is simple: organizations should not process data or design technologies that conflict with the best interests of trusting parties. But the logistics and implementation of data loyalty need to be developed if the concept is going to be capable of moving privacy law beyond its “notice and consent” roots to confront people’s vulnerabilities in their relationship with powerful data collectors.

In this short Essay, we propose a model for legislating data loyalty. Our …

Algorithms In Business, Merchant-Consumer Interactions, & Regulation, Tabrez Y. Ebrahim

Faculty Scholarship

The shift towards the use of algorithms in business has transformed merchant–consumer interactions. Products and services are increasingly tailored for consumers through algorithms that collect and analyze vast amounts of data from interconnected devices, digital platforms, and social networks. While traditionally merchants and marketeers have utilized market segmentation, customer demographic profiles, and statistical approaches, the exponential increase in consumer data and computing power enables them to develop and implement algorithmic techniques that change consumer markets and society as a whole. Algorithms enable targeting of consumers more effectively, in real-time, and with high predictive accuracy in pricing and profiling strategies. In …

The Covid-19 Pandemic And The Technology Trust Gap, Johanna Gunawan, David Choffnes, Woodrow Hartzog, Christo Wilson

Faculty Scholarship

Industry and government tried to use information technologies to respond to the COVID-19 pandemic, but using the internet as a tool for disease surveillance, public health messaging, and testing logistics turned out to be a disappointment. Why weren’t these efforts more effective? This Essay argues that industry and government efforts to leverage technology were doomed to fail because tech platforms have failed over the past few decades to make their tools trustworthy, and lawmakers have done little to hold these companies accountable. People cannot trust the interfaces they interact with, the devices they use, and the systems that power tech …

A Duty Of Loyalty For Privacy Law, Neil M. Richards, Woodrow Hartzog

Faculty Scholarship

Data privacy law fails to stop companies from engaging in self-serving, opportunistic behavior at the expense of those who trust them with their data. This is a problem. Modern tech companies are so entrenched in our lives and have so much control over what we see and click that the self-dealing exploitation of people has become a major element of the internet’s business model.

Academics and policymakers have recently proposed a possible solution: require those entrusted with people’s data and online experiences to be loyal to those who trust them. But many have concerns about a duty of loyalty. What, …

What Is Privacy? That’S The Wrong Question, Woodrow Hartzog

Faculty Scholarship

Privacy has never had a precise meaning. But in the early 1900s, the concept took on new life as a term of art in legal frameworks. The result has been a bit of a mess, as no singular definition has been adequate for all purposes. Daniel Solove, perhaps the most influential privacy scholar of our day, wrote at the turn of the millennium that privacy was “a concept in disarray.”

In this short essay reflecting upon Solove’s impact on the modern study of information privacy, I argue that the chaos and futility of competing conceptualizations of privacy is why Solove’s …

Gdpr And The Importance Of Data To Ai Startups, James Bessen, Stephen Michael Impink, Lydia Reichensperger, Robert Seamans

Faculty Scholarship

What is the impact of the European Union’s General Data Protection Regime (“GDPR”) and data regulation on AI startups? How important is data to AI product development? We study these questions using unique survey data of commercial AI startups. AI startups rely on data for their product development. Given the scale and scope of their business models, these startups are particularly susceptible to policy changes impacting data collection, storage and use. We find that training data and frequent model refreshes are particularly important for AI startups that rely on neural nets and ensemble learning algorithms. We also find that firms …

The Mixed Case For A Ptab Off-Ramp, Saurabh Vishnubhakat

Faculty Scholarship

This Essay begins from the emerging agenda in the political branches for reforming various aspects of the USPTO Patent Trial and Appeal Board, and focuses on a particular reform: the creation of a PTAB off-ramp whereby a patent being challenged in an administrative revocation proceeding could be removed into a system primarily aimed at amending its claims and preserving its validity. To put the proposal into perspective, the Essay presents specific empirical trends, largely unexplored until now, that implicate patent reliance interests to which the PTAB has done injury. Ultimately, because the benefits and costs from a PTAB off-ramp are …

Data-Informed Duties In Ai Development, Frank A. Pasquale

Faculty Scholarship

Law should help direct—and not merely constrain—the development of artificial intelligence (AI). One path to influence is the development of standards of care both supplemented and informed by rigorous regulatory guidance. Such standards are particularly important given the potential for inaccurate and inappropriate data to contaminate machine learning. Firms relying on faulty data can be required to compensate those harmed by that data use—and should be subject to punitive damages when such use is repeated or willful. Regulatory standards for data collection, analysis, use, and stewardship can inform and complement generalist judges. Such regulation will not only provide guidance to …

Data-Centric Technologies: Patent And Copyright Doctrinal Disruptions, Tabrez Y. Ebrahim

Faculty Scholarship

Data-centric technologies create information content that directly controls, modifies, or responds to the physical world. This information content resides in the digital world yet has profound economic and societal impact in the physical world. 3D printing and artificial intelligence are examples of data-centric technologies. 3D printing utilizes digital data for eventual printing of physical goods. Artificial intelligence learns from data sets to make predictions or automated decisions for use in physical applications and systems. 3D printing and artificial intelligence technologies are based on digital foundations, blur the digital and physical divide, and dramatically improve physical goods, objects, products, or systems. …

Body Cameras And The Path To Redeem Privacy Law, Woodrow Hartzog

Faculty Scholarship

From a privacy perspective, the movement towards police body cameras seems ominous. The prospect of a surveillance device capturing massive amounts of data concerning people’s most vulnerable moments is daunting. These concerns are compounded by the fact that there is little consensus and few hard rules on how and for whom these systems should be built and used. But in many ways, this blank slate is a gift. Law and policy makers are not burdened by the weight of rules and technologies created in a different time for a different purpose. These surveillance and data technologies will be modern. Many …

Rise Of The Digital Regulator, Rory Van Loo

Faculty Scholarship

The administrative state is leveraging algorithms to influence individuals’ private decisions. Agencies have begun to write rules to shape for-profit websites such as Expedia and have launched their own online tools such as the Consumer Financial Protection Bureau’s mortgage calculator. These digital intermediaries aim to guide people toward better schools, healthier food, and more savings. But enthusiasm for this regulatory paradigm rests on two questionable assumptions. First, digital intermediaries effectively police consumer markets. Second, they require minimal government involvement. Instead, some for-profit online advisers such as travel websites have become what many mortgage brokers were before the 2008 financial crisis. …

On Questioning Automation, Woodrow Hartzog

Faculty Scholarship

Given the rapid pace of innovation and adoption, it can be hard to make sense of automated technologies. New products that leverage algorithms and artificial intelligence seem to be both promising and frightening. Law and policymakers, as well as the general public, are grappling with when to be excited and when to be concerned. If you're confused, you're not alone

The Inadequate, Invaluable Fair Information Practices, Woodrow Hartzog

Faculty Scholarship

For the past thirty years, the general advice for those seeking to collect, use, and share people’s personal data in a responsible way was relatively straightforward: follow the fair information practices, often called the “FIPs.” These general guidelines were designed to ensure that data processors are accountable for their actions and that data subjects are safe, secure, and endowed with control over their personal information. The FIPs have proven remarkably sturdy against the backdrop of near-constant technological change. Yet in the age of social media, big data, and artificial intelligence, the FIPs have been pushed to their breaking point. We …

The Internet Of Heirlooms And Disposable Things, Woodrow Hartzog, Evan Selinger

Faculty Scholarship

The Internet of Things (“IoT”) is here, and we seem to be going all in. We are trying to put a microchip in nearly every object that is not nailed down and even a few that are. Soon, your cars, toasters, toys, and even your underwear will be wired up to make your lives better. The general thought seems to be that “Internet connectivity makes good objects great.” While the IoT might be incredibly useful, we should proceed carefully. Objects are not necessarily better simply because they are connected to the Internet. Often, the Internet can make objects worse and …

Law And Politics, An Emerging Epidemic: A Call For Evidence-Based Public Health Law, Michael Ulrich

Faculty Scholarship

As Jacobson v. Massachusetts recognized in 1905, the basis of public health law, and its ability to limit constitutional rights, is the use of scientific data and empirical evidence. Far too often, this important fact is lost. Fear, misinformation, and politics frequently take center stage and drive the implementation of public health law. In the recent Ebola scare, political leaders passed unnecessary and unconstitutional quarantine measures that defied scientific understanding of the disease and caused many to have their rights needlessly constrained. Looking at HIV criminalization and exemptions to childhood vaccine requirements, it becomes clear that the blame cannot be …

Addressing The Harm Of Total Surveillance: A Reply To Professor Neil Richards, Danielle Keats Citron, David C. Gray

Faculty Scholarship

In his insightful article The Dangers of Surveillance, 126 HARV. L. REV. 1934 (2013), Neil Richards offers a framework for evaluating the implications of government surveillance programs that is centered on protecting "intellectual privacy." Although we share his interest in recognizing and protecting privacy as a condition of personal and intellectual development, we worry in this essay that, as an organizing principle for policy, "intellectual privacy" is too narrow and politically fraught. Drawing on other work, we therefore recommend that judges, legislators, and executives focus instead on limiting the potential of surveillance technologies to effect programs of broad and indiscriminate …

Social Data, Woodrow Hartzog

Faculty Scholarship

As online social media grow, it is increasingly important to distinguish between the different threats to privacy that arise from the conversion of our social interactions into data. One well-recognized threat is from the robust concentrations of electronic information aggregated into colossal databases. Yet much of this same information is also consumed socially and dispersed through a user interface to hundreds, if not thousands, of peer users.

In order to distinguish relationally shared information from the threat of the electronic database, this essay identifies the massive amounts of personal information shared via the user interface of social technologies as “social …

System Adjustments, Brendan S. Maher

Faculty Scholarship

This invited Essay considers the future of law data and system reform.

Chain-Link Confidentiality, Woodrow Hartzog

Faculty Scholarship

Disclosing personal information online often feels like losing control over one’s data forever; but this loss is not inevitable. This essay proposes a “chain-link confidentiality” approach to protecting online privacy. One of the most difficult challenges to guarding privacy in the digital age is the protection of information once it is exposed to other people. A chain-link confidentiality regime would contractually link the disclosure of personal information to obligations to protect that information as the information moves downstream. The system would focus on the relationships not only between the discloser of information and the initial recipient, but also between the …

Higher First Amendment Hurdles For Public Health Regulation, Kevin Outterson

Faculty Scholarship

In 2007, Vermont enacted the Prescription Confidentiality Law, prohibiting pharmacies from selling “prescriber-identifiable” prescription information to data-mining companies such as IMS Health and Verispan. These companies aggregate such data and sell them to many groups, including drug companies, so when drug sales representatives visit a physician, they can know exactly what prescriptions the physician has written.

States And Internet Enforcement, Joel R. Reidenberg

Faculty Scholarship

This essay addresses the enforcement of decisions through internet instruments. The starting point is a brief justification of internet enforcement as the obligation of democratic states. Next, the essay argues that the movement to re-engineer the internet infrastructure by public and private actions also facilitates state enforcement of legal and policy decisions. The essay maintains that states will increasingly try to use network intermediaries such as payment systems and Internet Service Providers as enforcement instruments. Finally, and most importantly, the essay focuses on ways that states may harness the power of technological instruments such as worms, filters and packet interceptors …

Privacy Wrongs In Search Of Remedies, Joel R. Reidenberg

Faculty Scholarship

The American legal system has generally rejected legal rights for data privacy and relies instead on market self-regulation and the litigation process to establish norms of appropriate behavior in society. Information privacy is protected only through an amalgam of narrowly targeted rules. The aggregation of these specific rights leaves many significant gaps and fewer clear remedies for violations of fair information practices. With an absence of well-established legal rights, privacy wrongs are currently in search of remedies. This Article first describes privacy rights and wrongs that frame the search for remedies in the United States. It explores public enforcement of, …

Commentary On Economic And Ethical Reasons For Protecting Data, Wendy J. Gordon

Faculty Scholarship

Like Jane Ginsburg, I would like to drop back a bit, to talk about more general principles. Essentially, both of our primary speakers focused on a distinction between property and non-property modes of protecting data. I would like to highlight the economic and ethical reasons for maintaining that distinction.