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Full-Text Articles in Law
A Public Technology Option, Hannah Bloch-Wehba
A Public Technology Option, Hannah Bloch-Wehba
Faculty Scholarship
Private technology increasingly underpins public governance. But the state’s growing reliance on private firms to provide a variety of complex technological products and services for public purposes brings significant costs for transparency: new forms of governance are becoming less visible and less amenable to democratic control. Transparency obligations initially designed for public agencies are a poor fit for private vendors that adhere to a very different set of expectations.
Aligning the use of technology in public governance with democratic values calls for rethinking, and in some cases abandoning, the legal structures and doctrinal commitments that insulate private vendors from meaningful …
Artificial Intelligence And Contract Formation: Back To Contract As Bargain?, John Linarelli
Artificial Intelligence And Contract Formation: Back To Contract As Bargain?, John Linarelli
Book Chapters
Some say AI is advancing quickly. ChatGPT, Bard, Bing’s AI, LaMDA, and other recent advances are remarkable, but they are talkers not doers. Advances toward some kind of robust agency for AI is, however, coming. Humans and their law must prepare for it. This chapter addresses this preparation from the standpoint of contract law and contract practices. An AI agent that can participate as a contracting agent, in a philosophical or psychological sense, with humans in the formation of a con-tract will have to have the following properties: (1) AI will need the cognitive functions to act with intention and …
Algorithmic Governance From The Bottom Up, Hannah Bloch-Wehba
Algorithmic Governance From The Bottom Up, Hannah Bloch-Wehba
Faculty Scholarship
Artificial intelligence and machine learning are both a blessing and a curse for governance. In theory, algorithmic governance makes government more efficient, more accurate, and more fair. But the emergence of automation in governance also rests on public-private collaborations that expand both public and private power, aggravate transparency and accountability gaps, and create significant obstacles for those seeking algorithmic justice. In response, a nascent body of law proposes technocratic policy changes to foster algorithmic accountability, ethics, and transparency.
This Article examines an alternative vision of algorithmic governance, one advanced primarily by social and labor movements instead of technocrats and firms. …
Algorithm Vs. Algorithm, Cary Coglianese, Alicia Lai
Algorithm Vs. Algorithm, Cary Coglianese, Alicia Lai
All Faculty Scholarship
Critics raise alarm bells about governmental use of digital algorithms, charging that they are too complex, inscrutable, and prone to bias. A realistic assessment of digital algorithms, though, must acknowledge that government is already driven by algorithms of arguably greater complexity and potential for abuse: the algorithms implicit in human decision-making. The human brain operates algorithmically through complex neural networks. And when humans make collective decisions, they operate via algorithms too—those reflected in legislative, judicial, and administrative processes. Yet these human algorithms undeniably fail and are far from transparent. On an individual level, human decision-making suffers from memory limitations, fatigue, …
Submission To The Toronto Police Services Board’S Use Of New Artificial Intelligence Technologies Policy- Leaf And The Citizen Lab, Suzie Dunn, Kristen Mj Thomasen, Kate Robertson, Pam Hrick, Cynthia Khoo, Rosel Kim, Ngozi Okidegbe, Christopher Parsons
Submission To The Toronto Police Services Board’S Use Of New Artificial Intelligence Technologies Policy- Leaf And The Citizen Lab, Suzie Dunn, Kristen Mj Thomasen, Kate Robertson, Pam Hrick, Cynthia Khoo, Rosel Kim, Ngozi Okidegbe, Christopher Parsons
Reports & Public Policy Documents
We write as a group of experts in the legal regulation of artificial intelligence (AI), technology-facilitated violence, equality, and the use of AI systems by law enforcement in Canada. We have experience working within academia and legal practice, and are affiliated with LEAF and the Citizen Lab who support this letter.
We reviewed the Toronto Police Services Board Use of New Artificial Intelligence Technologies Policy and provide comments and recommendations focused on the following key observations:
1. Police use of AI technologies must not be seen as inevitable
2. A commitment to protecting equality and human rights must be integrated …
Beyond Algorithms: Toward A Normative Theory Of Automated Regulation, Felix Mormann
Beyond Algorithms: Toward A Normative Theory Of Automated Regulation, Felix Mormann
Faculty Scholarship
The proliferation of artificial intelligence in our daily lives has spawned a burgeoning literature on the dawn of dehumanized, algorithmic governance. Remarkably, the scholarly discourse overwhelmingly fails to acknowledge that automated, non-human governance has long been a reality. For more than a century, policymakers have relied on regulations that automatically adjust to changing circumstances, without the need for human intervention. This article surveys the track record of self-adjusting governance mechanisms to propose a normative theory of automated regulation.
Effective policymaking frequently requires anticipation of future developments, from technology innovation to geopolitical change. Self-adjusting regulation offers an insurance policy against the …
Administrative Law In The Automated State, Cary Coglianese
Administrative Law In The Automated State, Cary Coglianese
All Faculty Scholarship
In the future, administrative agencies will rely increasingly on digital automation powered by machine learning algorithms. Can U.S. administrative law accommodate such a future? Not only might a highly automated state readily meet longstanding administrative law principles, but the responsible use of machine learning algorithms might perform even better than the status quo in terms of fulfilling administrative law’s core values of expert decision-making and democratic accountability. Algorithmic governance clearly promises more accurate, data-driven decisions. Moreover, due to their mathematical properties, algorithms might well prove to be more faithful agents of democratic institutions. Yet even if an automated state were …
The Law Of Black Mirror - Syllabus, Yafit Lev-Aretz, Nizan Packin
The Law Of Black Mirror - Syllabus, Yafit Lev-Aretz, Nizan Packin
Open Educational Resources
Using episodes from the show Black Mirror as a study tool - a show that features tales that explore techno-paranoia - the course analyzes legal and policy considerations of futuristic or hypothetical case studies. The case studies tap into the collective unease about the modern world and bring up a variety of fascinating key philosophical, legal, and economic-based questions.
Artificial Financial Intelligence, William Magnuson
Artificial Financial Intelligence, William Magnuson
Faculty Scholarship
Recent advances in the field of artificial intelligence have revived long-standing debates about what happens when robots become smarter than humans. Will they destroy us? Will they put us all out of work? Will they lead to a world of techno-savvy haves and techno-ignorant have-nots? These debates have found particular resonance in finance, where computers already play a dominant role. High-frequency traders, quant hedge funds, and robo-advisors all represent, to a greater or lesser degree, real-world instantiations of the impact that artificial intelligence is having on the field. This Article will argue that the primary danger of artificial intelligence in …
Ok, Google, Will Artificial Intelligence Replace Human Lawyering?, Amy Vorenberg, Julie A. Oseid, Melissa Love Koenig
Ok, Google, Will Artificial Intelligence Replace Human Lawyering?, Amy Vorenberg, Julie A. Oseid, Melissa Love Koenig
Law Faculty Scholarship
Will Artificial Intelligence (AI) replace human lawyering? The answer is no. Despite worries that AI is getting so sophisticated that it could take over the profession, there is little cause for concern. Indeed, the surge of AI in the legal field has crystalized the real essence of effective lawyering. The lawyer’s craft goes beyond what AI can do because we listen with empathy to clients’ stories, strategize to find that story that might not be obvious, thoughtfully use our imagination and judgment to decide which story will appeal to an audience, and creatively tell those winning stories.
This article reviews …
Automatically Extracting Meaning From Legal Texts: Opportunities And Challenges, Kevin D. Ashley
Automatically Extracting Meaning From Legal Texts: Opportunities And Challenges, Kevin D. Ashley
Articles
This paper examines impressive new applications of legal text analytics in automated contract review, litigation support, conceptual legal information retrieval, and legal question answering against the backdrop of some pressing technological constraints. First, artificial intelligence (Al) programs cannot read legal texts like lawyers can. Using statistical methods, Al can only extract some semantic information from legal texts. For example, it can use the extracted meanings to improve retrieval and ranking, but it cannot yet extract legal rules in logical form from statutory texts. Second, machine learning (ML) may yield answers, but it cannot explain its answers to legal questions or …
Using Ai To Analyze Patent Claim Indefiniteness, Dean Alderucci, Kevin D. Ashley
Using Ai To Analyze Patent Claim Indefiniteness, Dean Alderucci, Kevin D. Ashley
Articles
In this Article, we describe how to use artificial intelligence (AI) techniques to partially automate a type of legal analysis, determining whether a patent claim satisfies the definiteness requirement. Although fully automating such a high-level cognitive task is well beyond state-of-the-art AI, we show that AI can nevertheless assist the decision maker in making this determination. Specifically, the use of custom AI technology can aid the decision maker by (1) mining patent text to rapidly bring relevant information to the decision maker attention, and (2) suggesting simple inferences that can be drawn from that information.
We begin by summarizing the …
Law's Halo And The Moral Machine, Bert I. Huang
Law's Halo And The Moral Machine, Bert I. Huang
Faculty Scholarship
How will we assess the morality of decisions made by artificial intelligence – and will our judgments be swayed by what the law says? Focusing on a moral dilemma in which a driverless car chooses to sacrifice its passenger to save more people, this study offers evidence that our moral intuitions can be influenced by the presence of the law.
Outcome Prediction In The Practice Of Law, Mark K. Osbeck, Michael Gilliland
Outcome Prediction In The Practice Of Law, Mark K. Osbeck, Michael Gilliland
Articles
Business forecasters typically use time-series models to predict future demands, the forecasts informing management decision making and guiding organizational planning. But this type of forecasting is merely a subset of the broader field of predictive analytics, models used by data scientists in all manner of applications, including credit approvals, fraud detection, product-purchase and music-listening recommendations, and even the real-time decisions made by self-driving vehicles. The practice of law requires decisions that must be based on predictions of future legal outcomes, and data scientists are now developing forecasting methods to support the process. In this article, Mark Osbeck and Mike Gilliland …
A Rule Of Persons, Not Machines: The Limits Of Legal Automation, Frank A. Pasquale
A Rule Of Persons, Not Machines: The Limits Of Legal Automation, Frank A. Pasquale
Faculty Scholarship
No abstract provided.
Regulating By Robot: Administrative Decision Making In The Machine-Learning Era, Cary Coglianese, David Lehr
Regulating By Robot: Administrative Decision Making In The Machine-Learning Era, Cary Coglianese, David Lehr
All Faculty Scholarship
Machine-learning algorithms are transforming large segments of the economy, underlying everything from product marketing by online retailers to personalized search engines, and from advanced medical imaging to the software in self-driving cars. As machine learning’s use has expanded across all facets of society, anxiety has emerged about the intrusion of algorithmic machines into facets of life previously dependent on human judgment. Alarm bells sounding over the diffusion of artificial intelligence throughout the private sector only portend greater anxiety about digital robots replacing humans in the governmental sphere. A few administrative agencies have already begun to adopt this technology, while others …
Computer Models For Legal Prediction, Kevin D. Ashley, Stephanie Bruninghaus
Computer Models For Legal Prediction, Kevin D. Ashley, Stephanie Bruninghaus
Articles
Computerized algorithms for predicting the outcomes of legal problems can extract and present information from particular databases of cases to guide the legal analysis of new problems. They can have practical value despite the limitations that make reliance on predictions risky for other real-world purposes such as estimating settlement values. An algorithm's ability to generate reasonable legal arguments also is important. In this article, computerized prediction algorithms are compared not only in terms of accuracy, but also in terms of their ability to explain predictions and to integrate predictions and arguments. Our approach, the Issue-Based Prediction algorithm, is a program …