Open Access. Powered by Scholars. Published by Universities.®

Law Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 13 of 13

Full-Text Articles in Law

Resisting Face Surveillance With Copyright Law, Amanda Levendowski May 2022

Resisting Face Surveillance With Copyright Law, Amanda Levendowski

Georgetown Law Faculty Publications and Other Works

Face surveillance is animated by deep-rooted demographic and deployment biases that endanger marginalized communities and threaten the privacy of all. But current approaches have not prevented its adoption by law enforcement. Some companies have offered voluntary moratoria on selling the technology, leaving many others to fill in the gaps. Legislators have enacted regulatory oversight at the state and city levels, but a federal ban remains elusive. Both approaches require vast shifts in practical and political will, each with drawbacks. While we wait, face surveillance persists. This Article suggests a new possibility: face surveillance is fueled by unauthorized copies and reproductions …


Contracting For Algorithmic Accountability, Cary Coglianese, Erik Lampmann Jan 2021

Contracting For Algorithmic Accountability, Cary Coglianese, Erik Lampmann

All Faculty Scholarship

As local, state, and federal governments increase their reliance on artificial intelligence (AI) decision-making tools designed and operated by private contractors, so too do public concerns increase over the accountability and transparency of such AI tools. But current calls to respond to these concerns by banning governments from using AI will only deny society the benefits that prudent use of such technology can provide. In this Article, we argue that government agencies should pursue a more nuanced and effective approach to governing the governmental use of AI by structuring their procurement contracts for AI tools and services in ways that …


Clearing Opacity Through Machine Learning, W. Nicholson Price Ii, Arti K. Rai Jan 2021

Clearing Opacity Through Machine Learning, W. Nicholson Price Ii, Arti K. Rai

Articles

Artificial intelligence and machine learning represent powerful tools in many fields, ranging from criminal justice to human biology to climate change. Part of the power of these tools arises from their ability to make predictions and glean useful information about complex real-world systems without the need to understand the workings of those systems.


Implementing User Rights For Research In The Field Of Artificial Intelligence: A Call For International Action, Sean Flynn, Michael W. Carroll Jan 2020

Implementing User Rights For Research In The Field Of Artificial Intelligence: A Call For International Action, Sean Flynn, Michael W. Carroll

Articles in Law Reviews & Other Academic Journals

Last year, before the onset of a global pandemic highlighted the critical and urgent need for technology-enabled scientific research, the World Intellectual Property Organization (WIPO) launched an inquiry into issues at the intersection of intellectual property (IP) and artificial intelligence (AI). We contributed comments to that inquiry, with a focus on the application of copyright to the use of text and data mining (TDM) technology. This article describes some of the most salient points of our submission and concludes by stressing the need for international leadership on this important topic. WIPO could help fill the current gap on international leadership, …


Artificial Intelligence Inventions & Patent Disclosure, Tabrez Y. Ebrahim Jan 2020

Artificial Intelligence Inventions & Patent Disclosure, Tabrez Y. Ebrahim

Faculty Scholarship

Artificial intelligence (“AI”) has attracted significant attention and has imposed challenges for society. Yet surprisingly, scholars have paid little attention to the impediments AI imposes on patent law’s disclosure function from the lenses of theory and policy. Patents are conditioned on inventors describing their inventions, but the inner workings and the use of AI in the inventive process are not properly understood or are largely unknown. The lack of transparency of the parameters of the AI inventive process or the use of AI makes it difficult to enable a future use of AI to achieve the same end state. While …


Algorithms And Human Freedom, Richard Warner, Robert Sloan Apr 2019

Algorithms And Human Freedom, Richard Warner, Robert Sloan

All Faculty Scholarship

Predictive analytics such as data mining, machine learning, and artificial intelligence drive algorithmic decision making. Its "all-encompassing scope already reaches the very heart of a functioning society". Unfortunately, the legal system and its various tools developed around human decisionmakers cannot adequately administer accountability mechanisms for computer decision making. Antiquated approaches require modernization to bridge the gap between governing human decision making and new technologies. We divide the bridge-building task into three questions. First, what features of the use of predictive analytics significantly contribute to incorrect, unjustified, or unfair outcomes? Second, how should one regulate those features to make outcomes more …


The New Legal Landscape For Text Mining And Machine Learning, Matthew Sag Jan 2019

The New Legal Landscape For Text Mining And Machine Learning, Matthew Sag

Faculty Articles

Now that the dust has settled on the Authors Guild cases, this Article takes stock of the legal context for TDM research in the United States. This reappraisal begins in Part I with an assessment of exactly what the Authors Guild cases did and did not establish with respect to the fair use status of text mining. Those cases held unambiguously that reproducing copyrighted works as one step in the process of knowledge discovery through text data mining was transformative, and thus ultimately a fair use of those works. Part I explains why those rulings followed inexorably from copyright's most …


Automation And Predictive Analytics In Patent Prosecution: Uspto Implications And Policy, Tabrez Y. Ebrahim Jan 2019

Automation And Predictive Analytics In Patent Prosecution: Uspto Implications And Policy, Tabrez Y. Ebrahim

Faculty Scholarship

Artificial-intelligence technological advancements bring automation and predictive analytics into patent prosecution. The information asymmetry between inventors and patent examiners is expanded by artificial intelligence, which transforms the inventor-examiner interaction to machine-human interactions. In response to automated patent drafting, automated office-action responses, "cloems" (computer-generated word permutations) for defensive patenting, and machine-learning guidance (based on constantly updated patent-prosecution big data), the United States Patent and Trademark Office (USPTO) should reevaluate patent-examination policy from economic, fairness, time, and transparency perspectives. By conceptualizing the inventor-examiner relationship as a "patenting market," economic principles suggest stronger efficiencies if both inventors and the USPTO have better information …


Using Ai To Analyze Patent Claim Indefiniteness, Dean Alderucci, Kevin D. Ashley Jan 2019

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 …


Computational Experimentation, Tabrez Y. Ebrahim Jan 2019

Computational Experimentation, Tabrez Y. Ebrahim

Faculty Scholarship

Experimentation conjures images of laboratories and equipment in biotechnology, chemistry, materials science, and pharmaceuticals. Yet modern day experimentation is not limited to only chemical synthesis, but is increasingly computational. Researchers in the unpredictable arts can experiment upon the functions, properties, reactions, and structures of chemical compounds with highly accurate computational techniques. These computational capabilities challenge the enablement and utility patentability requirements. The patent statute requires that the inventor explain how to make and use the invention without undue experimentation and that the invention have at least substantial and specific utility. These patentability requirements do not align with computational research capabilities, …


Data-Centric Technologies: Patent And Copyright Doctrinal Disruptions, Tabrez Y. Ebrahim Jan 2019

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. …


How Copyright Law Can Fix Artificial Intelligence's Implicit Bias Problem, Amanda Levendowski Jun 2018

How Copyright Law Can Fix Artificial Intelligence's Implicit Bias Problem, Amanda Levendowski

Georgetown Law Faculty Publications and Other Works

As the use of artificial intelligence (AI) continues to spread, we have seen an increase in examples of AI systems reflecting or exacerbating societal bias, from racist facial recognition to sexist natural language processing. These biases threaten to overshadow AI’s technological gains and potential benefits. While legal and computer science scholars have analyzed many sources of bias, including the unexamined assumptions of its often homogenous creators, flawed algorithms, and incomplete datasets, the role of the law itself has been largely ignored. Yet just as code and culture play significant roles in how AI agents learn about and act in the …


Machine Learning And Law, Harry Surden Jan 2014

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 …