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This paper adopts a conventionalist approach to shed light on the measurement and reification problems that underlie the quantification of desistance from crime in the scientific literature. Analysis of 100 papers spanning three decades indicates that approaches based on theoretical classification have recently lost ground in favor of more sophisticated techniques aimed at empirically identifying subgroups. These techniques convey the impression of objectiveness among statistics users and consumers and, as a result, the classification “desisters” and “persisters” are increasingly reified. Findings suggest that the quantification of desistance is intimately linked to the maintenance of a classification system that constitutes delinquency as a stable category and contributes to “making” up new kinds of people over which institutions can legitimately intervene.

With technologies like machine learning and data analytics being deployed as privileged means to improve how contemporary bureaucracies work, many governments around the world have turned to artificial intelligence as a tool of statecraft. In that context, our paper uses Canada as a critical case to investigate the relationship between ideals of good government and good technology. We do so through not one, but two Trudeaus—celebrity Prime Minister Justin Trudeau (2015—…) and his equally famous father, former Prime Minister Pierre Elliott Trudeau (1968–1979, 1980–1984). Both shared a similar interest in new ideas and practices of both intelligent government and artificial intelligence. Influenced by Marshall McLuhan and his media theory, Pierre Elliott Trudeau deployed new communication technologies to restore centralized control in an otherwise decentralized state. Partly successful, he left his son with an informationally inclined political legacy, which decades later animated Justin Trudeau's own turn toward Big Data and artificial intelligence. Compared with one another, these two visions for both government and artificial intelligence illustrate the broader tensions between cybernetic and neoliberal approaches to government, which inform how new technologies are conceived of, and adopted, as political ones. As this article argues, Canada offers a paradigmatic case for how artificial intelligence is as much shaped by theories of government as by investments and innovations in computing research, which together delimit the contours of intelligence by defining which technical systems, people, and organizations come to be recognized as its privileged bearers.