A hybrid CNN + BILSTM deep learning-based DSS for efficient prediction of judicial case decisions
GeM software package for computation of symmetries and conservation laws of differential equations
Algorithmic Government: Automating Public Services and Supporting Civil Servants in using Data Science Technologies
The data science technologies of artificial intelligence (AI), Internet of Things (IoT), big data and behavioral/predictive analytics, and blockchain are poised to revolutionize government and create a new generation of GovTech start-ups. The impact from the ‘smartification’ of public services...
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Ganesh Sitaraman Testifies Before U.S. Senate Judiciary Subcommittee The airline industry is not resilient, competitive, or serving the public, and Congress must fix the miserable flying experience, Vanderbilt Law Professor Ganesh Sitaraman testified before the U.S. Senate Judiciary Subcommittee on...
Putting AI Ethics into Practice: The Hourglass Model of Organizational AI Governance
The organizational use of artificial intelligence (AI) has rapidly spread across various sectors. Alongside the awareness of the benefits brought by AI, there is a growing consensus on the necessity of tackling the risks and potential harms, such as bias...
Artificial Intelligence in Business Law: Navigating Regulation, Ethics, and Governance
Abstract: This chapter examines the transformative role of artificial intelligence (AI) in business law, focusing on the regulatory, ethical, and governance challenges it presents. As AI applications in legal processes grow—ranging from compliance automation and contract management to risk assessment...
Predicting the Behavior of the Supreme Court of the United States: A General Approach
The Scored Society: Due Process for Automated Predictions
Big Data is increasingly mined to rank and rate individuals. Predictive algorithms assess whether we are good credit risks, desirable employees, reliable tenants, valuable customers—or deadbeats, shirkers, menaces, and “wastes of time.” Crucial opportunities are on the line, including the...
The Judicial Demand for Explainable Artificial Intelligence
A recurrent concern about machine learning algorithms is that they operate as “black boxes,” making it difficult to identify how and why the algorithms reach particular decisions, recommendations, or predictions. Yet judges will confront machine learning algorithms with increasing frequency,...
Russian Court Decisions Data Analysis Using Distributed Computing and Machine Learning to Improve Lawmaking and Law Enforcement
This article describes the study results of semi-structured data processing and analysis of the Russian court decisions (almost 30 million) using distributed cluster-computing framework and machine learning. Spark was used for data processing and decisions trees were used for analysis....
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1 Collectively striving to succeed Immersive Learning Benefit from close-knit residential education and experiential learning in the classroom and beyond. Integrated Research Working across institutions, Vanderbilt bridges disciplines to solve the great challenges of our time. Collaborative Discovery Collaborative culture...
Regulatory Settlement, Stare Decisis, and Loper Bright
In Loper Bright v. Raimondo, the Supreme Court adopted and deployed a particular narrative about agency action in support of overruling Chevron: Agencies reverse their own statutory interpretations “as much as [they] like[],” creating pervasive instability in the law, thereby...
A systematic literature review of machine learning methods in predicting court decisions
<span>Envisaging legal cases’ outcomes can assist the judicial decision-making process. Prediction is possible in various cases, such as predicting the outcome of construction litigation, crime-related cases, parental rights, worker types, divorces, and tax law. The machine learning methods can function...
Mapping global AI governance: a nascent regime in a fragmented landscape
AbstractThe rapid advances in the development and rollout of artificial intelligence (AI) technologies over the past years have triggered a frenzy of regulatory initiatives at various levels of government and the private sector. This article describes and evaluates the emerging...
The Dilemma and Countermeasures of AI in Educational Application
This paper divides the application of AI in education into three categories, namely, students-oriented AI, teachers-oriented AI and school mangers -oriented AI, which focuses on the individualized self-adaptive learning of students, the assisted teaching of teachers and the service management...
Artificial Intelligence and Copyright: Issues and Challenges
The increasing role of Artificial Intelligence in the area of medical science, transportation, aviation, space, education, entertainment (music, art, games, and films), industry, and many other sectors has transformed our day to day lives. The area of Intellectual Property Rights...
AI Governance by Human Rights-Centred Design, Deliberation and Oversight: An End to Ethics Washing
A predictive performance comparison of machine learning models for judicial cases
Artificial intelligence is currently in the center of attention of legal professionals. In recent years, a variety of efforts have been made to predict judicial decisions using different machine learning models, but no realistic performance comparison between them is available....
Geometric conservation laws for flow problems with moving boundaries and deformable meshes, and their impact on aeroelastic computations
The keys to sustainable competitive advantage
Legal Barriers in Developing Educational Technology
The integration of technology in education has transformed teaching and learning, making digital tools essential in the context of Industry 4.0. However, the rapid evolution of educational technology poses significant legal challenges that must be addressed for effective implementation. This...
Aether, Radiation, Mass-Energy Law, Gravity and Inertia
The universal space, crisscrossed by electric fields from electric charges in bodies, is proposed to be the aether as a physical medium conceived by Maxwell, Einstein and others. The fields, in accordance with Coulomb’s law, balance out everywhere. Permittivity and...
Copyright and AI training data—transparency to the rescue?
Abstract Generative Artificial Intelligence (AI) models must be trained on vast quantities of data, much of which is composed of copyrighted material. However, AI developers frequently use such content without seeking permission from rightsholders, leading to calls for requirements to...
Direito e inteligência artificial: desafios da regulação da IA no Sistema Judiciário Brasileiro
This article analyzes the challenges of regulating Artificial Intelligence (AI) in the Brazilian judicial system, considering the constitutional, ethical, and normative principles that guide the use of technologies within the Judiciary. The research examines the normative evolution promoted by the...
Patents’ “Self-Consistency” Question: Diversion and Blocking Under a Patent-Racing Model
Introduction The United States patent system is commonly justified by its provision of economic incentives for innovation.[1] But this justification comes with constant concern that the social benefits of innovation that the patent system stimulates might not outweigh the sum...
Legal Exploration of AI Face-Changing Technology
The present society is in a period of rapid development of artificial intelligence, and the process of its swift advancement is filled with both opportunities and challenges. As a branch of artificial intelligence, deep synthesis technology gradually enters people's vision....
Curbing Private Enforcement of the Voting Rights Act: Thoughts on Recent Developments
For decades, private plaintiffs have brought claims to enforce key provisions of the Voting Rights Act (VRA). Recent decisions have tossed out these claims on the ground that enforcement authority lies solely with the Attorney…The postCurbing Private Enforcement of the...
Auditing Algorithms for Discrimination
This Essay responds to the argument by Joshua Kroll, et al., in Accountable Algorithms, 165 U.PA.L.REV. 633 (2017), that technical tools can be more effective in ensuring the fairness of algorithms than insisting on transparency. When it comes to combating...