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Articles 1 - 16 of 16
Full-Text Articles in Law
Machine Manipulation: Why An Ai Editor Does Not Serve First Amendment Values, Alec Peters
Machine Manipulation: Why An Ai Editor Does Not Serve First Amendment Values, Alec Peters
University of Colorado Law Review
The past few years have seen increasing calls for regulation of large social media platforms, and several states have recently enacted laws regulating their content moderation, promotion, and recommendation practices. But if those platforms are exercising editorial discretion when carrying out these tasks, many of the regulations will run into constitutional concerns: the First Amendment protects the “exercise of editorial control and judgment” by publishers over their choice of content and how it is presented. However, the editorial operation of social media platforms differs significantly from traditional media, most importantly in the use of artificial intelligence (AI) for editorial decision-making. …
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
Publications
No abstract provided.
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
Publications
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 …
Algorithmic Impact Assessments Under The Gdpr: Producing Multi-Layered Explanations, Margot E. Kaminski, Gianclaudio Malgieri
Algorithmic Impact Assessments Under The Gdpr: Producing Multi-Layered Explanations, Margot E. Kaminski, Gianclaudio Malgieri
Publications
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, …
Book Review, Aamir S. Abdullah
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
Publications
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 …
Artificial Intelligence And Law: An Overview, Harry Surden
Artificial Intelligence And Law: An Overview, Harry Surden
Publications
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
Publications
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
Publications
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 …
The Right To Explanation, Explained, Margot E. Kaminski
The Right To Explanation, Explained, Margot E. Kaminski
Publications
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 …
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
Publications
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
Publications
No abstract provided.
Machine Learning And Law, Harry Surden
Machine Learning And Law, Harry Surden
Publications
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 …