Artificial Intelligence (AI) And The Criminal Justice System: Examining The Ethical And Social Implications Of AI In Policing.
Volume 7 - Issue 4, April 2024 Edition
[Download Full Paper]
Author(s)
Ifeoluwa S. Elegbe, Oreoluwa Ladoja
Keywords
Criminal Justice System, Ethical Implications, Cybercrime, Social Implications, Policing, Crime Prediction, Predictive Policing Algorithms, Effectiveness.
Abstract
The integration of artificial intelligence (AI) in the criminal justice system has raised significant ethical and social implications. As AI technology continues to advance it has been increasingly utilized in various aspects of policing including crime prediction facial recognition and predictive policing algorithms. While these advancements hold the potential to enhance law enforcement efficiency and effectiveness, they also pose challenges related to privacy bias accountability and transparency. This paper aims to explore and analyze the ethical and social implications of AI in policing highlighting its potential benefits and drawbacks. This paper also examines AI development and implementation to ensure the fair and equitable treatment of all individuals within the criminal justice system.
References
[1]. Babuta, A., Oswald, M., & Rinik, C. (2020). Machine learning algorithms and police decision-making: Legal, ethical, and regulatory challenges. Royal United Services Institute for Defence and Security Studies.
[2]. Brayne, S. (2017). Big data surveillance: The case of policing. American Sociological Review, 82(5), 977-1008.
[3]. Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. Proceedings of the 1st Conference on Fairness, Accountability and Transparency, 77-91.
[4]. Christin, A. (2017). Algorithms in practice: Comparing web journalism and criminal justice. Big Data & Society, 4(2), 1-14.
[5]. Garvie, C., Bedoya, A. M., & Frankle, J. (2016). The perpetual lineup: Unregulated police face recognition in America. Georgetown Law, Center on Privacy & Technology.
[6]. Kim, M. (2019). Who should be afraid of AI? Examining the ethics of AI in criminal justice. AI & Society, 34(4), 899-910.
[7]. Lum, K., & Isaac, W. (2016). To predict and serve? Significance, 13(5), 14-19.
[8]. Oswald, M., Grace, J., Urwin, S., & Barnes, G. C. (2018). Algorithmic risk assessment policing models: Lessons from the Durham HART model and 'Experimental' proportionality. Information & Communications Technology Law, 27(2), 223-250.