THE IMPACT OF ARTIFICIAL INTELLIGENCE IN THE CONCLUSION OF THE PLEA AGREEMENT
DOI:
https://doi.org/10.55516/ijlso.v6i1.309Rezumat
The digital transformation of the judicial system has made artificial intelligence (AI) an increasingly important vector in the analysis of evidence, in the formulation of plea agreements, and in the anticipation of judicial outcomes (Susskind, 2019; Surden, 2020). The article investigates the impact of these technologies in the context of plea bargaining, highlighting the tension between procedural efficiency and fundamental guarantees of a fair trial (Angwin et al., 2016; Katz, 2020). AI can reduce the length of cases and standardize practice, but it brings risks related to voluntarism, transparency, equality of arms, and accountability (Goodman & Flaxman, 2017; Floridi, 2021). Predictive models that estimate the probability of conviction or suggest sentences can influence the decision-making autonomy of the defendant (Wachter & Mittelstadt, 2019). The main proposal is to establish a regulatory framework focused on meaningful human control, algorithmic audit and data protection (CEPEJ, 2021), so that the final decision remains a responsible and fair human act. Conclusion: AI can support criminal justice only if it is used transparently, ethically and under constant legal supervision (Dignum, 2022).
Referințe
Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016). Machine bias: There’s software used across the country to predict future criminals. And it’s biased against Blacks. ProPublica;
CEPEJ – European Commission for the Efficiency of Justice. (2021). European Ethical Charter on the Use of Artificial Intelligence in Judicial Systems and Their Environment. Council of Europe;
Damaschin, M. (2020). Procedura penală. Partea generală. Editura Universul Juridic;
Dignum, V. (2022). Responsible Artificial Intelligence: Developing and Using AI in a Responsible Way. Springer;
European Commission. (2021). Ethics Guidelines for Trustworthy AI. Publications Office of the European Union;
Floridi, L. (2021). The Ethics of Artificial Intelligence. Oxford University Press;
Goodman, B., & Flaxman, S. (2017). European Union regulations on algorithmic decision-making and a right to explanation. AI Magazine, 38(3) 50–57;
Katz, D. M. (2020). Quantitative legal prediction. Emory Law Journal, 62(4), 909–966;
Kelleher, J. D. (2019). Deep Learning. MIT Press;
Lagioia, F., & Sartor, G. (2020). The Impact of Artificial Intelligence on the Judiciary. Springer
Mittelstadt, B. (2022). Principles for transparency and accountability in algorithmic decision-making. AI & Society, 37(2), 1–15;
Neagu, I. (2018). Tratat de procedură penală. Partea generală. Editura Universul Juridic;
Susskind, R. (2019). Tomorrow’s Lawyers: An Introduction to Your Future (2nd ed.). Oxford University Press;
Surden, H. (2020). Artificial Intelligence and Law: An overview. Georgia State University Law Review, 35(4), 1305–1340;
Udroiu, M. (2022). Procedură penală. Partea generală. Sinteze și grile. Editura C.H. Beck;
Volonciu, N. (2017). Tratat de procedură penală. Partea generală. Editura Paideia;
Wachter, S., & Mittelstadt, B. (2019). A right to reasonable inferences: Rethinking data protection law in the age of Big Data and AI. Columbia Business Law Review, 2019(2), 494–620.
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