The Use of AI in Legal Systems: Determining Independent Contractor vs. Employee Status

Cohen, Maxime C.; Dahan, Samuel; Khern-am-nuai, Warut; Shimao, Hajime; Touboul, Jonathan

doi:10.2139/ssrn.4013823

Cited by 3 publications

(4 citation statements)

References 9 publications

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“…Legal Artificial Intelligence (LegalAI) (Bui & Nguyen, 2023), (Završnik, 2020), (Zhong et al, 2020), (Wang & Tian, 2020) Big data analytics, machine learning, and AI in the criminal justice system (Bui & Nguyen, 2023), (Wang, 2020) AI in China's legal system (Wang, 2020), (Wang & Tian, 2020) AI for access to courts (Završnik, 2020) Advantages and difficulties of AI in the justice system AI in criminal justice (Cohen, 2023), (Rodrigues, 2020) AI in dispute resolution (Zeleznikow, 2016) AI for efficiency and democratization of access to justice (Norton, 2020), (Zeleznikow, 2016), (Poppe, 2019), (Hodson, 2019), (Alarie & Yoon, 2019) Limitations and challenges of AI in legal reasoning and decision-making (Cohen, 2023), (Rodrigues, 2020) Potential risks of AI applications in the legal system Discrimination and bias in AI algorithms and decision-making (Bui & Nguyen, 2023), (Rodrigues, 2020), (Kauffman & Soares, 2021) Lack of transparency and accountability in AI (Wang, 2020), (Wang & Tian, 2020), (Rodrigues, 2020) Exacerbation of existing biases in the justice system by AI (Rodrigues, 2020), (Kennedy, 2021), (Stahl, 2021) Implications for human rights and fairness (Bui & Nguyen, 2023), (Wang, 2020), (Schmitz, 2019), (Re & Solow-Niederman, 2019), (Floridi et al, 2021), (Stahl, 2021), (Barton, 2022) Ethical use of AI in legal systems…”

Section: Ai Applications In the Legal Systemmentioning

confidence: 99%

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Transforming Justice: Implications of Artificial Intelligence in Legal Systems

Vargas-Murillo,

Pari-Bedoya,

Turriate-Guzman

et al. 2024

Acad. J. Interdiscip. Stud.

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The present literature review explores the growing impact of artificial intelligence (AI) on the justice system. It sheds light on the prospects, obstacles, and probable consequences of its assimilation. Utilizing a broad array of scholarly resources, we examine the implementation of AI in various domains, including but not limited to predictive law enforcement, risk evaluation, evidentiary analysis, and judicial decision-making. The review recognizes the advantages of artificial intelligence, such as enhanced efficacy, precision, and impartiality in legal proceedings, while also expressing apprehensions regarding potential partialities, ethical predicaments, and risks to confidentiality and human liberties. Furthermore, it is crucial to underscore the significance of interdisciplinary cooperation and comprehensive regulatory frameworks in guaranteeing the judicious and impartial integration of AI technologies in the justice system. The present study endeavors to make a significant scholarly contribution to the ongoing discourse surrounding artificial intelligence and its intersection with the legal field. By examining the opportunities and challenges of integrating AI in legal systems, this review provides specific insights into formulating policies around algorithmic accountability, transparency, and ethical safeguards to ensure responsible AI adoption. Received: 27 October 2023 / Accepted: 29 February 2024 / Published: 5 March 2024

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Section: Ai Applications In the Legal Systemmentioning

confidence: 99%

“…Reflecting on the implications arising from deploying such advanced systems in jurisprudence is critically significant. Moreover, there's an immediate necessity for an allencompassing discourse on the consequences associated with these technologies within the judiciary (Cohen, 2023).…”

Section: Advantages and Difficulties Of Ai In The Justice Systemmentioning

confidence: 99%

Transforming Justice: Implications of Artificial Intelligence in Legal Systems

Vargas-Murillo,

Pari-Bedoya,

Turriate-Guzman

et al. 2024

Acad. J. Interdiscip. Stud.

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“…This has led to a heated debate on the legal status of gig workers. In fact, long before the rise of the gig economy, much was at stake in determining whether a worker should be classified as an employee or as an independent contractor (Barron 1999), as this question strikes at the core of the structure of the economy, and it has important implications for both workers' and employers' rights (Cohen et al 2022).…”

Section: Introductionmentioning

confidence: 99%

A Stressful Explanation: The Dual Effect of Explainable Artificial Intelligence in Personal Health Management

Grüning,

Wolf,

Trenz

2024

Proceedings of the Annual Hawaii International Conference on System Sciences

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There is a widespread debate over how gig workers should be classified. The passage of California Assembly Bill 5 (AB5) -a landmark legislation that aims to correct the misclassification of gig workers, has significant implications for workers, platforms, regulators, and the economy. In this research, leveraging the passage of AB5 as a shock for a natural experiment, we empirically investigate the impact of AB5 on gig workers in California to provide insights. With the data collected from a leading online labor market that connects clients and gig workers, we applied a Difference in Difference approach, and we found that the monthly earnings of gig workers in California, compared to those in other states, have a significantly higher increase after AB5 was signed into law. This effect stems from both increased daily earnings and increased working days. We discuss the implications for policymakers and platforms.

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“…In this study, we investigate how the use of artificial intelligence (AI) in the mortgage application process affects the issues surrounding bias and discrimination in the mortgage market. Our study is inspired by the increasing adoption of AI-based decision support systems among decision-makers in various contexts, including the justice system [5], credit card fraud detection [6], and job application screening [7]. As such, it is important to study the implications of the adoption of an AI-based decision support system in the mortgage application process, which historically suffers from racial discrimination, from the value/risk proposition perspective.…”

Section: Introductionmentioning

confidence: 99%

AI and housing discrimination: the case of mortgage applications

Zou

Khern-am-nuai

2022

AI Ethics

Self Cite

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Issues surrounding bias and discrimination in housing markets have been acknowledged and discussed both in the literature and in practice. In this study, we investigate this issue specifically in the context of mortgage applications through the lens of an AI-based decision support system. Using the data provided as a part of the Home Mortgage Disclosure Act (HMDA), we first show that ethnicity bias does indeed exist in historical mortgage application approvals, where black applicants are more likely to be declined a mortgage compared with white applicants whose circumstances are otherwise similar. More interestingly, this bias is amplified when an off-the-shelf machine-learning model is used to recommend an approval/denial decision. Finally, when fair machine-learning algorithms are adopted to alleviate such biases, we find that the "fairness" actually leaves all stakeholders-black applicants, white applicants, and mortgage lenders-worse off. Our findings caution against the use of machine-learning models without human involvement when the decision has significant implications for the prediction subjects.

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The Use of AI in Legal Systems: Determining Independent Contractor vs. Employee Status

Cited by 3 publications

References 9 publications

Transforming Justice: Implications of Artificial Intelligence in Legal Systems

Transforming Justice: Implications of Artificial Intelligence in Legal Systems

A Stressful Explanation: The Dual Effect of Explainable Artificial Intelligence in Personal Health Management

AI and housing discrimination: the case of mortgage applications

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