Intellectual Property

By REBEKAH NINAN. Full Text. lawreview - Minnesota Law Review

Evaluating whether machines improve on human performance is one of the central questions of machine learning. However, there are many domains where the data is <i>selectively labeled</i> in the sense that the observed outcomes are themselves a consequence of the...

Program Overview Each summer, Vanderbilt in Venice allows American and European law students an opportunity to gain an invaluable international perspective. Directed by Professor Michael Newton, Vanderbilt in Venice brings together a maximum of 45 students with 3 professors to...

The legal profession is facing an era of change driven by technological advancements, environmental crises, shifting client expectations, and evolving societal norms. This article argues that flexibility and resilience are not just positive personality traits but essential legal skills that...

Abstract In the debate on copyright exceptions permitting text and data mining (“TDM”) for the development of generative AI systems, the so-called “three-step test” has become a centre of gravity. The test serves as a universal yardstick for assessing the...

Algorithmic decision-making systems have become pervasive across critical domains including employment, housing, healthcare, and criminal justice. While these systems promise enhanced efficiency and objectivity, they increasingly demonstrate patterns of discrimination that perpetuate and amplify existing societal biases. This paper examines...

The integration of Artificial Intelligence (AI) in recruitment processes has revolutionized hiring by increasing efficiency, reducing time-to-hire, and enabling data-driven decision-making. However, despite these advancements, concerns about algorithmic bias and fairness remain central to ethical AI deployment. This paper explores...

Artificial intelligence systems deployed through cloud infrastructure have transformed numerous sectors while simultaneously raising critical ethical concerns regarding bias and fairness. This article examines the multifaceted nature of algorithmic bias in cloud AI systems, presenting quantitative evidence of disparities across...

This paper examines how UK ‘hard laws’ can adapt to regulate algorithmic bias in the healthcare context. I explore the causes of algorithmic bias which sets the foundation for how the law will address this issue. I critically analyse elements...

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...