Exploring the Ethical Implications of AI in Legal Decision-Making

Authors

  • Avinash Gaur Assistant professor of law at Gurugram University Avinashllm2015@hpnlu.ac.in

Keywords:

Artificial Intelligence (AI), Legal Decision-Making, Ethical Implications

Abstract

One of the many domains in which artificial intelligence (AI) is becoming increasingly present in today's modern society is the process of decision-making within the legal system. the ethical problems that arise when artificial intelligence is used in judicial decision-making. There is a possibility that artificial intelligence will have positive effects, such as increased productivity and reduced human bias; however, there are also potential negative effects associated with it. These include concerns regarding transparency and accountability, as well as the potential for a reduction in human judgement and empathy. When investigating potential ethical implications, we adopt a comprehensive approach, taking into account the perspectives of AI researchers, attorneys, lawmakers, and the general public. the ethical responsibilities of artificial intelligence programmers to produce reliable and accountable software. In addition to this, it explores how legal practitioners might learn to maximise the use of AI tools while maintaining their authoritative decision-making positions without having to give up their positions.

References

 Alexander, L., & Versteeg, M. (2012). Constitutional retrogression. In California Law Review, 100(6), 1259-1313.

 Barocas, S., Hardt, M., & Narayanan, A. (2019). Fairness and machine learning. In Big Data, 5(3), 159-163.

 Caliskan, A., Bryson, J. J., & Narayanan, A. (2017). Semantics derived automatically from language corpora contain human-like biases. In Science, 356(6334), 183-186.

 Diakopoulos, N. (2016). Accountability in algorithmic decision-making. In Digital Journalism, 4(6), 700-708.

 Gillespie, T. (2014). The relevance of algorithms. In Media Technologies, 30(2), 67-88.

 Green, B., & Selfridge, R. (2015). This time it's personal: The public and private sides of predictive analytics. In Duke Law Journal, 65(5), 897-950.

 Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. In Nature Machine Intelligence, 1(9), 389-399.

 Kroll, J. A., Huey, J., Barocas, S., Felten, E. W., Reidenberg, J., Robinson, D. G., & Yu, H. (2017). Accountable algorithms. In University of Pennsylvania Law Review, 165(3), 633-705.

 Pasquale, F. (2015). The black box society: The secret algorithms that control money and information. Harvard University Press.

 Selbst, A. D., & Barocas, S. (2018). The intuitive appeal of explainable machines. In Fordham Law Review, 87(3), 1085-1130.

 Wachter, S., Mittelstadt, B., & Floridi, L. (2017). Why a right to explanation of automated decision-making does not exist in the General Data Protection Regulation. In International Data Privacy Law, 7(2), 76-99.

Downloads

Published

31-12-2022

How to Cite

Avinash Gaur. (2022). Exploring the Ethical Implications of AI in Legal Decision-Making. International Journal for Research Publication and Seminar, 13(5), 257–264. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/273

Issue

Section

Original Research Article