Algorithmic Unfairness through the Lens of EU Non-Discrimination Law
Concerns regarding unfairness and discrimination in the context of artificial intelligence (AI) systems have recently received increased attention from both legal and computer science scholars. Yet, the degree of overlap between notions of algorithmic bias and fairness on the one...
Algorithmic bias, data ethics, and governance: Ensuring fairness, transparency and compliance in AI-powered business analytics applications
The widespread adoption of AI-powered business analytics applications has revolutionized decision-making, yet it has also introduced significant challenges related to algorithmic bias, data ethics, and governance. As organizations increasingly rely on machine learning and big data analytics for customer profiling,...
Data augmentation for fairness-aware machine learning
Researchers and practitioners in the fairness community have highlighted the ethical and legal challenges of using biased datasets in data-driven systems, with algorithmic bias being a major concern. Despite the rapidly growing body of literature on fairness in algorithmic decision-making,...
Implementing User Rights for Research in the Field of Artificial Intelligence: A Call for International Action
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....
Artificial intelligence, the common good, and the democratic deficit in AI governance
Abstract There is a broad consensus that artificial intelligence should contribute to the common good, but it is not clear what is meant by that. This paper discusses this issue and uses it as a lens for analysing what it...
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...
Vision, status, and research topics of Natural Language Processing
Artificial intelligence, big data and intellectual property: protecting computer generated works in the United Kingdom
Big data and its use by artificial intelligence (AI) is changing the way intellectual property is developed and granted. For decades, machines have been autonomously generating works which have traditionally been eligible for copyright and patent protection. Now, the growing...
Standard Structure of Legal Provisions -For The Legal Knowledge Processing by Natural Language-
The Impact of Large Language Modeling on Natural Language Processing in Legal Texts: A Comprehensive Survey
Natural Language Processing (NLP) has witnessed significant advancements in recent years, particularly with the emergence of large language models. These models, such as GPT-3.5 and its variants, have revolutionized various domains, including legal text processing (LTP). This survey explores the...
The New Regulation of the European Union on Artificial Intelligence: Fuzzy Ethics Diffuse into Domestic Law and Sideline International Law
An Adaptive Conceptualisation of Artificial Intelligence and the Law, Regulation and Ethics
The description of a combination of technologies as ‘artificial intelligence’ (AI) is misleading. To ascribe intelligence to a statistical model without human attribution points towards an attempt at shifting legal, social, and ethical responsibilities to machines. This paper exposes the...
Data protection law and the regulation of artificial intelligence: a two-way discourse
The paper aims to analyse the relationship between the law on the protection of personal data and the regulation of artificial intelligence, in search of synergies and with a view to a complementary application to automated processing and decision-making. In...
A regulatory challenge for natural language processing (NLP)‐based tools such as ChatGPT to be legally used for healthcare decisions. Where are we now?
In the global debate about the use of Natural Language Processing (NLP)-based tools such as ChatGPT in healthcare decisions, the question of their use as regulatory-approved Software as Medical Device (SaMD) has not yet been sufficiently clarified. Currently, this discussion...
High-reward, high-risk technologies? An ethical and legal account of AI development in healthcare
Abstract Background Considering the disruptive potential of AI technology, its current and future impact in healthcare, as well as healthcare professionals’ lack of training in how to use it, the paper summarizes how to approach the challenges of AI from...
AI Legal Insight Analyser (ALIA)
The AI Legal Insight Analyzer (ALIA) is a smart web application designed to make legal document analysis faster, easier, and more accurate. By combining artificial intelligence (AI) with natural language processing (NLP), ALIA helps legal professionals, researchers, and students efficiently...
Predicting Outcomes of Legal Cases based on Legal Factors using Classifiers
Predicting outcomes of legal cases may aid in the understanding of the judicial decision-making process. Outcomes can be predicted based on i) case-specific legal factors such as type of evidence ii) extra-legal factors such as the ideological direction of the...
GPT-3: Its Nature, Scope, Limits, and Consequences
Abstract In this commentary, we discuss the nature of reversible and irreversible questions, that is, questions that may enable one to identify the nature of the source of their answers. We then introduce GPT-3, a third-generation, autoregressive language model that...
Human-AI collaboration in legal services: empirical insights on task-technology fit and generative AI adoption by legal professionals
Purpose This study aims to investigate the use of generative artificial intelligence (GenAI) in the legal profession, focusing on its fit with tasks performed by legal practitioners and its impact on performance and adoption. Design/methodology/approach This study uses a mixed...
Finance, Financial Crime and Regulation: Can Generative AI (Artificial Intelligence) Help Face the Challenges?
Generative artificial intelligence (Gen AI) has helped change the trajectory of Banking (FinTech) and Law (Reg Tech/Law Tech). Technology innovates at an astounding rate. AI and Gen AI can not only simulate human intelligence (human thinking) but also perform tasks...
Computational Law, Symbolic Discourse, and the AI Constitution
Gottfried Leibniz—who died just more than 300 years ago in November 1716—worked on many things, but a theme that recurred throughout his life was the goal of turning human law into an exercise in computation. One gets a reasonable idea...
Computation of minimum-time feedback control laws for discrete-time systems with state-control constraints
The problem of finding a feedback law that drives the state of a linear discrete-time system to the origin in minimum-time subject to state-control constraints is considered. Algorithms are given to obtain facial descriptions of the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</tex> -step...
Critical perspectives on AI in education: political economy, discrimination, commercialization, governance and ethics
AI in education is not only a challenging area of technical development and educational innovation, but increasingly the focus of critical analysis informed by the social sciences, philosophy and theory. This chapter provides an overview of critical perspectives on AI...
Operationalising AI governance through ethics-based auditing: an industry case study
AbstractEthics-based auditing (EBA) is a structured process whereby an entity’s past or present behaviour is assessed for consistency with moral principles or norms. Recently, EBA has attracted much attention as a governance mechanism that may help to bridge the gap...
AI Training and Copyright: Should Intellectual Property Law Allow Machines to Learn?
This article examines the intricate legal landscape surrounding the use of copyrighted materials in the development of artificial intelligence (AI). It explores the rise of AI and its reliance on data, emphasizing the importance of data availability for machine learning...
Demystifying the Draft EU Artificial Intelligence Act — Analysing the good, the bad, and the unclear elements of the proposed approach
AI standardization promises to support the implementation of EU legislation and promote the rapid transfer,transparency, and interoperability of this massively disruptive technology. However, apart from well-known practical difficulties stemming from the unique probabilistic nature and the rapid development of AI...
A Computational Evaluation of Two Laws of Semantic Change
For more than a century scholars have proposed laws of se-\nmantic change that characterize how words change in meaning\nover time. Two such laws are the law of differentiation, which\nproposes that near-synonyms tend to differentiate in meaning\nover time, and the law...
Natural language processing and query expansion in legal information retrieval: Challenges and a response
As methods in legal information retrieval (IR) evolve to meet the demands of rapidly increasing stores of electronic information, there is the intuitive appeal of capturing detail in legal queries with natural language processing (NLP). One difficulty with this approach...
Protecting Intellectual Property With Reliable Availability of Learning Models in AI-Based Cybersecurity Services
Artificial intelligence (AI)-based cybersecurity services offer significant promise in many scenarios, including malware detection, content supervision, and so on. Meanwhile, many commercial and government applications have raised the need for intellectual property protection of using deep neural network (DNN). Existing...