Labor & Employment

Racial equality is an important theme of international human rights law, but it has been largely obscured when the overall face recognition accuracy is pursued blindly. More facts indicate racial bias indeed degrades the fairness of recognition system and the...

Predictive analytics and artificial intelligence are applied widely across law enforcement agencies and the criminal justice system. Despite criticism that such tools reinforce inequality and structural discrimination, proponents insist that they will nonetheless improve the equality and fairness of outcomes...

By: Alyssa Shaw, Volume 109 Staff Member If the progress towards closing the gender wage gap continues on the trends of the last few years, women will not be compensated equally to men until at least 2067—over a century after...

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,...

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Holistically minded, the Office provides services and resources that reflect the diversity of needs and issues that law students encounter during their education. Its vision is to send the happiest, healthiest, and most professional law students out into the world...

Pre-training large transformer models with in-domain data improves domain adaptation and helps gain performance on the domain-specific downstream tasks. However, sharing models pre-trained on potentially sensitive data is prone to adversarial privacy attacks. In this paper, we asked to which...

Information theory provides a constructive criterion for setting up probability distributions on the basis of partial knowledge, and leads to a type of statistical inference which is called the maximum-entropy estimate. It is the least biased estimate possible on the...

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This research paper deals with the general understanding of AI technology and its laws and regulations in India and China. It examines this issue from developing countries perspective and focusing on India and China, as they represent around 40 %...

[Context] Semantic legal metadata provides information that helps with understanding and interpreting the meaning of legal provisions. Such metadata is important for the systematic analysis of legal requirements. [Objectives] Our work is motivated by two observations: (1) The existing requirements...

Law, interpretations of law, legal arguments, agreements, etc. are typically expressed in writing, leading to the production of vast corpora of legal text.Their analysis, which is at the center of legal practice, becomes increasingly elaborate as these collections grow in...

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The use of machine learning algorithms has permeated into nearly all aspects of life. With this steady integration, tasks previously handled by humans are increasingly falling into the ‘hands’ of machines. Ideally this would be celebrated as a great improvement...

In the era of big data, the application of AI technology has become a core driver of social development, widely affecting a wide range of fields and impacting on the development models of various industries. With changing business models and...

Natural language processing (NLP) technology is an important constituent of artificial intelligence, focusing on the interaction between computers and human natural language, with the aim of enabling computers to understand, analyze, generate and process human languages. The fields of legal...

Machine learning fairness enhancement methods based on data bias correction are usually divided into two processes: The determination of sensitive attributes (such as race and gender) and the correction of data bias. In terms of determining sensitive attributes, existing studies...

The rapid integration of artificial intelligence (AI) into critical decision-making domains—such as healthcare, finance, law enforcement, and hiring—has raised significant ethical concerns regarding bias and fairness. Algorithmic decision-making systems, if not carefully designed and monitored, risk perpetuating and amplifying societal...

PurposeThis study examines the impact of data bias and algorithmic discrimination on individual credit accessibility in China’s financial system. It aims to align financial inclusion and equity goals with statistical fairness conditions by constructing fairness metrics from multiple dimensions. The...

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The AAAI Conference on Artificial Intelligence promotes theoretical and applied AI research as well as intellectual interchange among researchers and practitioners.