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Full-Text Articles in Law
Voices In, Voices Out: Impacted Stakeholders And The Governance Of Ai, Margot Kaminski
Voices In, Voices Out: Impacted Stakeholders And The Governance Of Ai, Margot Kaminski
Publications
This Essay addresses reasons for impacted stakeholder involvement in AI governance, ranging from democratic accountability norms to principles of regulatory design. It evaluates several recent examples of both soft and hard law, noting a range of examples of impacted stakeholder participation. It closes with a critique: none of these laws adequately contemplates how to craft transparency and provide expertise so as to meaningfully empower impacted stakeholders.
Risky Speech Systems: Tort Liability For Ai-Generated Illegal Speech, Margot E. Kaminski
Risky Speech Systems: Tort Liability For Ai-Generated Illegal Speech, Margot E. Kaminski
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No abstract provided.
Chatgpt, Ai Large Language Models, And Law, Harry Surden
Chatgpt, Ai Large Language Models, And Law, Harry Surden
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This Essay explores Artificial Intelligence (AI) Large Language Models (LLMs) like ChatGPT/GPT-4, detailing the advances and challenges in applying AI to law. It first explains how these AI technologies work at an understandable level. It then examines the significant evolution of LLMs since 2022 and their improved capabilities in understanding and generating complex documents, such as legal texts. Finally, this Essay discusses the limitations of these technologies, offering a balanced view of their potential role in legal work.
Constructing Ai Speech, Margot E. Kaminski, Meg Leta Jones
Constructing Ai Speech, Margot E. Kaminski, Meg Leta Jones
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Artificial Intelligence (AI) systems such as ChatGPT can now produce convincingly human speech, at scale. It is tempting to ask whether such AI-generated content “disrupts” the law. That, we claim, is the wrong question. It characterizes the law as inherently reactive, rather than proactive, and fails to reveal how what may look like “disruption” in one area of the law is business as usual in another. We challenge the prevailing notion that technology inherently disrupts law, proposing instead that law and technology co-construct each other in a dynamic interplay reflective of societal priorities and political power. This Essay instead deploys …
Regulating The Risks Of Ai, Margot E. Kaminski
Regulating The Risks Of Ai, Margot E. Kaminski
Publications
Companies and governments now use Artificial Intelligence (“AI”) in a wide range of settings. But using AI leads to well-known risks that arguably present challenges for a traditional liability model. It is thus unsurprising that lawmakers in both the United States and the European Union (“EU”) have turned to the tools of risk regulation in governing AI systems.
This Article describes the growing convergence around risk regulation in AI governance. It then addresses the question: what does it mean to use risk regulation to govern AI systems? The primary contribution of this Article is to offer an analytic framework for …
Naïve Realism, Cognitive Bias, And The Benefits And Risks Of Ai, Harry Surden
Naïve Realism, Cognitive Bias, And The Benefits And Risks Of Ai, Harry Surden
Publications
In this short piece I comment on Orly Lobel's book on artificial intelligence (AI) and society "The Equality Machine." Here, I reflect on the complex topic of aI and its impact on society, and the importance of acknowledging both its positive and negative aspects. More broadly, I discuss the various cognitive biases, such as naïve realism, epistemic bubbles, negativity bias, extremity bias, and the availability heuristic, that influence individuals' perceptions of AI, often leading to polarized viewpoints. Technology can both exacerbate and ameliorate these biases, and I commend Lobel's balanced approach to AI analysis as an example to emulate.
Although …
Humans In The Loop, Rebecca Crootof, Margot E. Kaminski, W. Nicholson Price Ii
Humans In The Loop, Rebecca Crootof, Margot E. Kaminski, W. Nicholson Price Ii
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From lethal drones to cancer diagnostics, humans are increasingly working with complex and artificially intelligent algorithms to make decisions which affect human lives, raising questions about how best to regulate these "human-in-the-loop" systems. We make four contributions to the discourse.
First, contrary to the popular narrative, law is already profoundly and often problematically involved in governing human-in-the-loop systems: it regularly affects whether humans are retained in or removed from the loop. Second, we identify "the MABA-MABA trap," which occurs when policymakers attempt to address concerns about algorithmic incapacities by inserting a human into a decision-making process. Regardless of whether the …
The Law Of Ai, Margot Kaminski
The Right To Contest Ai, Margot E. Kaminski, Jennifer M. Urban
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 …
Book Review, Aamir S. Abdullah
The Right To Explanation, Explained, Margot E. Kaminski
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 …
Artificial Intelligence And Law: An Overview, Harry Surden
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
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
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 …
Authorship, Disrupted: Ai Authors In Copyright And First Amendment Law, Margot E. Kaminski
Authorship, Disrupted: Ai Authors In Copyright And First Amendment Law, Margot E. Kaminski
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Technology is often characterized as an outside force, with essential qualities, acting on the law. But the law, through both doctrine and theory, constructs the meaning of the technology it encounters. A particular feature of a particular technology disrupts the law only because the law has been structured in a way that makes that feature relevant. The law, in other words, plays a significant role in shaping its own disruption. This Essay is a study of how a particular technology, artificial intelligence, is framed by both copyright law and the First Amendment. How the algorithmic author is framed by these …
From Google To Tolstoy Bot: Should The First Amendment Protect Speech Generated By Algorithms?, Margot Kaminski
From Google To Tolstoy Bot: Should The First Amendment Protect Speech Generated By Algorithms?, Margot Kaminski
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No abstract provided.
Machine Learning And Law, Harry Surden
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 …