Law Commons^™

Risky Speech Systems: Tort Liability For Ai-Generated Illegal Speech, Margot E. Kaminski

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No abstract provided.

Hunting And Gathering On The Legal Information Savannah, Susan Nevelow Mart, Adam Litzler, David Gunderman

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This article asks, what is it like for novice researchers to research real-world legal problems using four platforms: Bloomberg Law, Fastcase, Lexis Advance, and Westlaw? The study findings produced some surprises, as well as some clear implications for teaching legal research.

Algorithmic Impact Assessments Under The Gdpr: Producing Multi-Layered Explanations, Margot E. Kaminski, Gianclaudio Malgieri

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Policy-makers, scholars, and commentators are increasingly concerned with the risks of using profiling algorithms and automated decision-making. The EU’s General Data Protection Regulation (GDPR) has tried to address these concerns through an array of regulatory tools. As one of us has argued, the GDPR combines individual rights with systemic governance, towards algorithmic accountability. The individual tools are largely geared towards individual “legibility”: making the decision-making system understandable to an individual invoking her rights. The systemic governance tools, instead, focus on bringing expertise and oversight into the system as a whole, and rely on the tactics of “collaborative governance,” that is, …

The Law Of Ai, Margot Kaminski

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No abstract provided.

Book Review, Aamir S. Abdullah

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No abstract provided.

Models, Race, And The Law, Moon Duchin, Douglas M. Spencer

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Capitalizing on recent advances in algorithmic sampling, The Race-Blind Future of Voting Rights explores the implications of the long-standing conservative dream of certified race neutrality in redistricting. Computers seem promising because they are excellent at not taking race into account—but computers only do what you tell them to do, and the rest of the authors’ apparatus for measuring minority electoral opportunity failed every check of robustness and numerical stability that we applied. How many opportunity districts are there in the current Texas state House plan? Their methods can give any answer from thirty-four to fifty-one, depending on invisible settings. But …

The Right To Contest Ai, Margot E. Kaminski, Jennifer M. Urban

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Artificial intelligence (AI) is increasingly used to make important decisions, from university admissions selections to loan determinations to the distribution of COVID-19 vaccines. These uses of AI raise a host of concerns about discrimination, accuracy, fairness, and accountability.

In the United States, recent proposals for regulating AI focus largely on ex ante and systemic governance. This Article argues instead—or really, in addition—for an individual right to contest AI decisions, modeled on due process but adapted for the digital age. The European Union, in fact, recognizes such a right, and a growing number of institutions around the world now call for …

The Influencers: Facebook’S Libra, Public Blockchains, And The Ethical Considerations Of Centralization, Michele Benedetto Neitz

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The theoretical promise of blockchain technology is truly extraordinary: a peer-to-peer distributed immutable ledger that could revolutionize economies, societies, and even our daily lives. But what if blockchain technology is not as decentralized as people think? What are the ramifications if, in reality, a blockchain’s core decisions are actually influenced by small groups of people or corporations?

This short article seeks to answer that question, by demonstrating that decentralized public blockchains are only as immutable as the decentralization of their governance. Moreover, the announcement of Libra, Facebook’s new permissioned blockchain, shows a growing trend of centralized control around decentralized technologies. …

Artificial Intelligence And Law: An Overview, Harry Surden

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Much has been written recently about artificial intelligence (AI) and law. But what is AI, and what is its relation to the practice and administration of law? This article addresses those questions by providing a high-level overview of AI and its use within law. The discussion aims to be nuanced but also understandable to those without a technical background. To that end, I first discuss AI generally. I then turn to AI and how it is being used by lawyers in the practice of law, people and companies who are governed by the law, and government officials who administer the …

Lessons From Literal Crashes For Code, Margot Kaminski

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No abstract provided.

Binary Governance: Lessons From The Gdpr’S Approach To Algorithmic Accountability, Margot E. Kaminski

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Algorithms are now used to make significant decisions about individuals, from credit determinations to hiring and firing. But they are largely unregulated under U.S. law. A quickly growing literature has split on how to address algorithmic decision-making, with individual rights and accountability to nonexpert stakeholders and to the public at the crux of the debate. In this Article, I make the case for why both individual rights and public- and stakeholder-facing accountability are not just goods in and of themselves but crucial components of effective governance. Only individual rights can fully address dignitary and justificatory concerns behind calls for regulating …

Inside The Black Box Of Search Algorithms, Susan Nevelow Mart, Joe Breda, Ed Walters, Tito Sierra, Khalid Al-Kofahi

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A behind-the-scenes look at the algorithms that rank results in Bloomberg Law, Fastcase, Lexis Advance, and Westlaw.

The Right To Explanation, Explained, Margot E. Kaminski

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Many have called for algorithmic accountability: laws governing decision-making by complex algorithms, or AI. The EU’s General Data Protection Regulation (GDPR) now establishes exactly this. The recent debate over the right to explanation (a right to information about individual decisions made by algorithms) has obscured the significant algorithmic accountability regime established by the GDPR. The GDPR’s provisions on algorithmic accountability, which include a right to explanation, have the potential to be broader, stronger, and deeper than the preceding requirements of the Data Protection Directive. This Essay clarifies, largely for a U.S. audience, what the GDPR actually requires, incorporating recently released …

Understanding The Human Element In Search Algorithms And Discovering How It Affects Search Results, Susan Nevelow Mart

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When legal researchers search in online databases for the information they need to solve a legal problem, they need to remember that the algorithms that are returning results to them were designed by humans. The world of legal research is a human-constructed world, and the biases and assumptions the teams of humans that construct the online world bring to the task are imported into the systems we use for research. This article takes a look at what happens when six different teams of humans set out to solve the same problem: how to return results relevant to a searcher’s query …

The Gdpr’S Version Of Algorithmic Accountability, Margot Kaminski

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No abstract provided.

That Was Close! Reward Reporting Of Cybersecurity “Near Misses”, Jonathan Bair, Steven M. Bellovin, Andrew Manley, Blake Reid, Adam Shostak

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Building, deploying, and maintaining systems with sufficient cybersecurity is challenging. Faster improvement would be valuable to society as a whole. Are we doing as much as we can to improve? We examine robust and long-standing systems for learning from near misses in aviation, and propose the creation of a Cyber Safety Reporting System (CSRS).

To support this argument, we examine the liability concerns which inhibit learning, including both civil and regulatory liability. We look to the way in which cybersecurity engineering and science is done today, and propose that a small amount of ‘policy entrepreneurship’ could have substantial positive impact. …

Bridges Ii: The Law--Stem Alliance & Next Generation Innovation, Harry Surden

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Technological change recently has altered business models in the legal field, and these changes will continue to affect the practice of law itself. How can we, as educators, prepare law students to meet the challenges of new technology throughout their careers?

Results May Vary, Susan Nevelow Mart

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No abstract provided.

Panel 1: Robotic Speech And The First Amendment, Bruce E. H. Johnson, Helen Norton, David Skover

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Moderator: Professor Gregory Silverman.

Book discussed: Ronald L. Collins & David M. Skover, Robotica: Speech Rights and Artificial Intelligence (Cambridge Univ. Press 2018).

Siri-Ously 2.0: What Artificial Intelligence Reveals About The First Amendment, Toni M. Massaro, Helen Norton, Margot E. Kaminski

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The First Amendment may protect speech by strong Artificial Intelligence (AI). In this Article, we support this provocative claim by expanding on earlier work, addressing significant concerns and challenges, and suggesting potential paths forward.

This is not a claim about the state of technology. Whether strong AI — as-yet-hypothetical machines that can actually think — will ever come to exist remains far from clear. It is instead a claim that discussing AI speech sheds light on key features of prevailing First Amendment doctrine and theory, including the surprising lack of humanness at its core.

Courts and commentators wrestling with free …

Every Algorithm Has A Pov, Susan Nevelow Mart

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When legal researchers search in online databases for the information they need to solve a legal problem, they need to remember that the algorithms that are returning results to them were designed by humans. The world of legal research is a human-constructed world, and the biases and assumptions the teams of humans that construct the online world bring to the task are imported into the systems we use for research. This article takes a look at what happens when six different teams of humans set out to solve the same problem: how to return results relevant to a searcher’s query …

Research Algorithms Have A Point Of View: The Effect Of Human Decision Making On Your Search Results, Susan Nevelow Mart

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No abstract provided.

The Algorithm As A Human Artifact: Implications For Legal [Re]Search, Susan Nevelow Mart

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The results of using the search algorithms in Westlaw, Lexis Advance, Fastcase, Google Scholar, Ravel, and Casetext are compared. Six groups of humans created six different algorithms, and the results are a testament to the variability of human problem solving. That variability has implications both for researching and teaching research.

Siri-Ously? Free Speech Rights And Artificial Intelligence, Toni M. Massaro, Helen Norton

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Computers with communicative artificial intelligence (AI) are pushing First Amendment theory and doctrine in profound and novel ways. They are becoming increasingly self-directed and corporal in ways that may one day make it difficult to call the communication ours versus theirs. This, in turn, invites questions about whether the First Amendment ever will (or ever should) cover AI speech or speakers even absent a locatable and accountable human creator. In this Article, we explain why current free speech theory and doctrine pose surprisingly few barriers to this counterintuitive result; their elasticity suggests that speaker humanness no longer may be …

Regulating Software When Everything Has Software, Paul Ohm, Blake Reid

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This Article identifies a profound, ongoing shift in the modern administrative state: from the regulation of things to the regulation of code. This shift has and will continue to place previously isolated agencies in an increasing state of overlap, raising the likelihood of inconsistent regulations and putting seemingly disparate policy goals, like privacy, safety, environmental protection, and copyright enforcement, in tension. This Article explores this problem through a series of case studies and articulates a taxonomy of code regulations to help place hardware-turned-code rules in context. The Article considers the likely turf wars, regulatory thickets, and related dynamics that are …

Are Mobile Device Examinations Practiced Like 'Forensics'?, Gary Kessler

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"Mobile device forensics is sometimes disparaged as not really being ‘forensics.’ This paper discusses the relationship between digital forensics and other forensic sciences, and the relationship of mobile device forensics to the broader field of digital forensics. It specifically addresses the question of whether mobile device forensics processes – and practices – rise to the level of suitable forensics quality."

Machine Learning And Law, Harry Surden

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This Article explores the application of machine learning techniques within the practice of law. Broadly speaking “machine learning” refers to computer algorithms that have the ability to “learn” or improve in performance over time on some task. In general, machine learning algorithms are designed to detect patterns in data and then apply these patterns going forward to new data in order to automate particular tasks. Outside of law, machine learning techniques have been successfully applied to automate tasks that were once thought to necessitate human intelligence — for example language translation, fraud-detection, driving automobiles, facial recognition, and data-mining. If performing …

Computable Contracts, Harry Surden

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This Article explains how and why firms are representing certain contractual obligations as computer data. The reason is so that computers can read and process the substantive aspects of contractual obligations. The representation of contractual obligations in data instead of (or in addition to) the traditional written language form - what this Article calls "data-oriented contracting" - allows for the application of advanced computer processing abilities to substantive contractual obligations. Certain financial contracts exemplify this model. Equity option contracts are routinely represented not as contract documents written in ordinary language - but as data records intended to be processed by …

The Variable Determinacy Thesis, Harry Surden

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This Article proposes a novel technique for characterizing the relative determinacy of legal decision-making. I begin with the observation that the determinacy of legal outcomes varies from context to context within the law. To augment this intuition, I develop a theoretical model of determinate legal decision-making. This model aims to capture the essential features that are typically associated with the concept of legal determinacy. I then argue that we can use such an idealized model as a standard for expressing the relative determinacy or indeterminacy of decision-making in actual, observed legal contexts. From a legal theory standpoint, this approach - …

Code, Crash, And Open Source: The Outsourcing Of Financial Regulation To Risk Models And The Global Financial Crisis, Erik F. Gerding

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The widespread use of computer-based risk models in the financial industry during the last two decades enabled the marketing of more complex financial products to consumers, the growth of securitization and derivatives, and the development of sophisticated risk-management strategies by financial institutions. Over this same period, regulators increasingly delegated or outsourced vast responsibility for regulating risk in both consumer finance and financial markets to these privately owned industry models. Proprietary risk models of financial institutions thus came to serve as a "new financial code" that regulated transfers of risk among consumers, financial institutions, and investors.

The spectacular failure of financial-industry …