Re-conceptualising Scientific Expertise in International Criminal Investigations: An STS Perspective

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  • Karen McGregor Richmond
Contemporary societies have become reliant upon the guidance of scientific, and technological, experts whose inputs are utilized - to a hitherto unparalleled degree - by a proliferating array of complex and specialised systems,. Paradoxically, the contemporary reliance upon expert knowledge has given rise to a countervailing popular skepticism, which threatens to erode the very foundations of rational discourse, generating developmental obstacles across the panoply of natural, and social scientific domains, and creating tensions within discrete sites of technological application and epistemological uncertainty.

The field of international criminal justice has come to be regarded as a particular site of contestation, the investigation and prosecution of criminal acts - at the international level - being dependent upon the collection, processing, and categorisation of a diverse body of objective evidence, drawn from multiple sources: forensic samples, documentary material, ‘open source’ data and witness statements, inter alia, are recovered, and evaluated, by a heterogeneous body of institutional actors, drawn from diverse fields and backgrounds, possessed of varying levels of expertise, and increasingly founding upon disruptive new technologies, which themselves emerge across multiple disciplinary boundaries, confounding pre-existing institutional norms and expectations.

Clearly, the articulation of a coherent theoretical foundation for interdisciplinary expertise would serve all disciplines. However, that need is particularly acute within a criminal justice sector facing ethical and epistemological challenges generated by the emergence and confluence of machine learning technologies, biomedical research and the proliferating use of telecommunications data. Meanwhile, citizen participation in open source investigations has grown steadily (at least insofar as public involvement facilitates distributed data collection), offering a direct challenge to scientific and technological experts, trust in whose practices has been further eroded by the politicization of knowledge production and dissemination.

If the international legal system is to maintain a robust and rational approach to the ethical, legal and social challenges engendered by machine learning, bio-medical research, and sundry emergent technologies, then its responses must be founded upon a coherent theoretical account of trans-disciplinary scientific and technological expertise: an understanding whose broader application will enable citizens and policy makers alike to answer questions related to the proper function of expertise, its efficient mobilisation, and its limits. This necessary foundational research may thereby serve as a theoretical base which subsequent elaboration may aid institutional agents in negotiating disagreements between experts, serving not merely to justify the decision-making process to the public, but to facilitate their involvement in a dialectic process of policy development. The primary objective of this paper is therefore to develop, articulate, and disseminate, a normatively coherent theoretical account of transdisciplinary expertise, as practiced in the international criminal justice sector. An account which may demonstrate the potential for STS scholarship to address this area of collective concern, resolving the ontological and epistemological tensions which have been generated by the mobilization of trans-disciplinary scientific and technological innovations, deployed across disciplinary boundaries.
Original languageEnglish
Title of host publicationScience, technology and society for a post-truth age : Comparative dialogues on reflexivity
EditorsMelike Sahinol, Emine Onculer Yayalar
Number of pages26
Place of PublicationWilmington, Delaware
PublisherVernon Press
Publication date2023
Edition1
Pages117-143
Chapter6
ISBN (Print)9781648897887
Publication statusPublished - 2023
SeriesSeries in Philosophy of Science

ID: 375878835