Law Commons^™

Governing Smart Cities As Knowledge Commons - Introduction, Chapter 1 & Conclusion, Brett M. Frischmann, Michael J. Madison, Madelyn Sanfilippo

Book Chapters

Smart city technology has its value and its place; it isn’t automatically or universally harmful. Urban challenges and opportunities addressed via smart technology demand systematic study, examining general patterns and local variations as smart city practices unfold around the world. Smart cities are complex blends of community governance institutions, social dilemmas that cities face, and dynamic relationships among information and data, technology, and human lives. Some of those blends are more typical and common. Some are more nuanced in specific contexts. This volume uses the Governing Knowledge Commons (GKC) framework to sort out relevant and important distinctions. The framework grounds …

Big Data & Litigation: Analyzing The Expectation Of Lawyers To Provide Big Data Predictions When Advising Clients, Siegfried Fina, Irene Ng (Huang Ying)

Indian Journal of Law and Technology

This article intends to provide a background of big data and law, and to provide insights on the interaction between professional legal ethics and big data analytics, i.e. whether a lawyer can be disciplined for failing to use big data analytics in litigation cases. While most references in this article will be made to developments in the US legal technology/legal industry scene, this article will also provide a short segment on general developments of big data and law in the developing world. Ultimately, this article hopes to shed light on what litigators may expect from the use of this technology …

Prospects For Legal Analytics: Some Approaches To Extracting More Meaning From Legal Texts, Kevin D. Ashley

University of Cincinnati Law Review

No abstract provided.

Using Ai To Reduce Performance Risk In U.S. Procurement, Jessica Tillipman

GW Law Faculty Publications & Other Works

In recent years, several U.S. government agencies have pioneered the use of artificial intelligence (AI) and other emerging technologies to improve the efficiency and accuracy of their "responsibility determinations" (reviews of, among other things, contractor representations and certifications, past performance history, civil and criminal settlements, exclusions (such as suspensions or debarments), and contract terminations). As federal agencies continue to think strategically about how to improve processes and reduce risk in their procurements, technology-driven solutions will play a critical role in this undertaking.

Antitrust By Algorithm, Cary Coglianese, Alicia Lai

All Faculty Scholarship

Technological innovation is changing private markets around the world. New advances in digital technology have created new opportunities for subtle and evasive forms of anticompetitive behavior by private firms. But some of these same technological advances could also help antitrust regulators improve their performance in detecting and responding to unlawful private conduct. We foresee that the growing digital complexity of the marketplace will necessitate that antitrust authorities increasingly rely on machine-learning algorithms to oversee market behavior. In making this transition, authorities will need to meet several key institutional challenges—building organizational capacity, avoiding legal pitfalls, and establishing public trust—to ensure successful …

The Kind Of Solution A Smart City Is: Knowledge Commons And Postindustrial Pittsburgh, Michael J. Madison

Book Chapters

This case study brings new attention to a critical but under-appreciated dimension of so-called “smart” cities: how smart city governance builds and relies on institutionalized sharing of data, information, and other forms of knowledge across all sectors of public administration. Those smart city practices are referred to here as knowledge commons and systematized using the Governing Knowledge Commons (GKC) research framework. That framework extends and modifies Ostrom’s research tradition as to community-based resource governance. As with other GKC-focused research, this work relies on a qualitative case study. It draws a detailed, context-specific portrait of a smart city as knowledge commons …

Litigation Analytics: A Framework For Understanding, Using & Teaching, Peter A. Hook

Journal Articles

This article, appearing in the American Association of Law Libraries bimonthly member magazine, provides a brief introduction (under 2000 words) to litigation analytics. It contains a definition, common uses of litigation analytics, a brief history, as well as why litigation analytics should be taught in law school. The author provides his framework for teaching and understanding litigation analytics which includes types of analytics, pivot points (perspectives from which the analytics may be understood), and contextualizes the various analytics offerings by insight-needs categories: (1) categorizing and clustering; (2) ordering, ranking, and sorting; (3) distribution; (4) comparison; (5) trends; (6) geospatial location; …

Automating Fairness? Artificial Intelligence In The Chinese Court, Rachel E. Stern, Benjamin L. Liebman, Margaret Roberts, Alice Z. Wang

Faculty Scholarship

How will surging global interest in data analytics and artificial intelligence transform the day-to-day operations of courts, and what are the implications for judicial power? In the last five years, Chinese courts have come to lead the world in their efforts to deploy automated pattern analysis to monitor judges, standardize decision-making, and observe trends in society. This Article chronicles how and why Chinese courts came to embrace artificial intelligence, making public tens of millions of court judgments in the process. Although technology is certainly being used to strengthen social control and boost the legitimacy of the Chinese Communist Party, examining …

Leveraging Legal Analytics And Spend Data As A Law Firm Self-Governance Tool, Nancy B. Rapoport, Joseph R. Tiano Jr.

The Journal of Business, Entrepreneurship & the Law

Our essay has five parts: (i) a discussion of how external forces are reshaping the economics of today’s legal industry; (ii) examples of the types of decisions that tend to drive up the cost of bills in contravention of ethical duties; (iii) a discussion of possible reasons for those decisions (including a short discussion of social science explanations); (iv) a description of how attorneys can use data analytics tools to self-govern how they staff, deliver and bill for their legal services; and (v) recommendations for how both clients and law firms can benefit from proactively managing, on the front end, …

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 …

Big Data Analytics: What Can Go Wrong, Sharona Hoffman

Faculty Publications

It is not uncommon to read that long-held beliefs about medical treatments have been dislodged by new studies. For example, there is now doubt as to whether women should undergo annual mammograms, previously a cornerstone of cancer screening. Hormone replacement therapy for menopausal women, once considered highly suspect in light of worrisome research findings, is now being reconsidered as a beneficial therapy. These reversals trouble and confuse many Americans.

This Article explores why medical research findings can be erroneous and what can go wrong in the process of designing and conducting research studies. It provides readers with essential analytical tools …

The New Settlement Tools, Bernard Chao, Christopher Robertson, David Yokum

Sturm College of Law: Faculty Scholarship

By protecting the right to a jury, the state and federal constitutions recognize the fundamental value of having civil and criminal disputes resolved by laypersons. Actual trials, however, are relatively rare, in part because parties seek to avoid the risks and cost of trials and courts seek to clear dockets efficiently. But as desirable as settlement may be, it can be a difficult way to resolve a dispute. Parties view their cases from different perspectives, and these perspectives often cause both sides to be overly optimistic and to expect unreasonably large or unreasonably small resolutions.

This article describes a novel …

Data-Driven Discrimination At Work, Pauline T. Kim

AI-DR Collection

A data revolution is transforming the workplace. Employers are increasingly relying on algorithms to decide who gets interviewed, hired, or promoted. Although data algorithms can help to avoid biased human decision-making, they also risk introducing new sources of bias. Algorithms built on inaccurate, biased, or unrepresentative data can produce outcomes biased along lines of race, sex, or other protected characteristics. Data mining techniques may cause employment decisions to be based on correlations rather than causal relationships; they may obscure the basis on which employment decisions are made; and they may further exacerbate inequality because error detection is limited and feedback …

Standing After Snowden: Lessons On Privacy Harm From National Security Surveillance Litigation, Margot E. Kaminski

Publications

Article III standing is difficult to achieve in the context of data security and data privacy claims. Injury in fact must be "concrete," "particularized," and "actual or imminent"--all characteristics that are challenging to meet with information harms. This Article suggests looking to an unusual source for clarification on privacy and standing: recent national security surveillance litigation. There we can find significant discussions of what rises to the level of Article III injury in fact. The answers may be surprising: the interception of sensitive information; the seizure of less sensitive information and housing of it in a database for analysis; and …

The Fourth Amendment In A Digital World, Laura K. Donohue

Georgetown Law Faculty Publications and Other Works

Fourth Amendment doctrines created in the 1970s and 1980s no longer reflect how the world works. The formal legal distinctions on which they rely—(a) private versus public space, (b) personal information versus third party data, (c) content versus non-content, and (d) domestic versus international—are failing to protect the privacy interests at stake. Simultaneously, reduced resource constraints are accelerating the loss of rights. The doctrine has yet to catch up with the world in which we live. A necessary first step for the Court is to reconsider the theoretical underpinning of the Fourth Amendment, to allow for the evolution of a …

Using Data Analytics Tools To Supplement Traditional Research And Analysis In Forecasting Case Outcomes, Mark K. Osbeck

Articles

Companies are now developing legal research tools that employ the power of data analytics to aid case forecasting. These tools hold significant promise as a supplement to the traditional element-focused predictive analysis. Instead of having to rely solely on their own experience to balance the results of the traditional element-focused analysis, lawyers may soon be able to rely on software products that mine data about past cases, and then run the data through algorithms to detect patterns. Those patterns can then inform predictions about likely case outcomes, based upon similarities between the facts, the courts, the individual judges, etc.

Automating Vendor Fraud Detection In Enterprise Systems, Kishore Singh, Peter Best, Joseph Mula

Journal of Digital Forensics, Security and Law

Fraud is a multi-billion dollar industry that continues to grow annually. Many organizations are poorly prepared to prevent and detect fraud. Fraud detection strategies are intended to quickly and efficiently identify fraudulent activities that circumvent preventative measures. In this paper, we adopt a DesignScience methodological framework to develop a model for detection of vendor fraud based on analysis of patterns or signatures identified in enterprise system audit trails. The concept is demonstrated by developing prototype software. Verification of the prototype is achieved by performing a series of experiments. Validation is achieved by independent reviews from auditing practitioners. Key findings of …