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In section II, this paper will begin with an analysis of the development of AI, noting famous examples and establishing a baseline definition as a lens for the rest of this discussion. This paper will assess aspects of AI and machine learning to the extent it furthers our understanding of AI’s ability to collect data and make decisions. Some popular culture references will be brought into focus here to recognize storytelling’s ability to inspire and influence real-world scientific pursuits. Of preliminary importance, the AI we have both dreamed of and feared are certainly kept in mind as technology advances through sentience milestones.

Section III will discuss emerging technologies in the correctional space, including automated inmate communications monitoring services and related privacy and safety implications. Such technologies are designed to be objective and non-biased, though human involvement will necessarily entail subjectivity at each stage of development and implementation. The problem of encroaching AI is thus balanced between its own sophistication and that of its human collaborators.

In section IV, this paper will discuss the now-widescale adoption of correctional tablets in jails and prisons across the country. Persons experiencing incarceration have expectations about traditional monitoring areas, such as phone calls, mail, and video surveillance. However, allocating so many correctional services to a single device necessitates a new analysis of how governments, and the private contractors providing and maintaining their tablets, impact data collection and algorithm development practices.

Finally, in section V, the pieces come together as this paper argues for responsible data analysis and algorithm development. The drumbeat march of AI into detention spaces shows no sign of halting but there is time yet to steer its development to productive and humane purpose. In the end, this paper aims to increase awareness of the potential benefits and pitfalls of AI integration in the correctional space and provide a framework to understand tradeoffs in this sector.

Publication Citation

9 Lincoln Mem'l Univ. L. Rev., no. 3, 2022 at 1.