Reputation laundering and museum collections

Patterns, Priorities, Provenance, and Hidden Crime

Datos Bibliográficos

ID5700531
AutoresDonna Yates (0000-0002-9936-6461, Maastricht University, autor de correspondencia), Shawn Graham (0000-0002-2887-3554, Carleton University)
Año2024
Volumen30
Número2
Páginas145-164
Fecha de publicación2024-02-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaInternational Journal of Heritage Studies (JOURNAL)
Identificadores de la revistaISSN: 1352-7258 • E-ISSN: 1470-3610
EditorialInforma UK Limited (PUBLISHER • GB)
DOI10.1080/13527258.2023.2284740
OpenAlexW4388849500
IdiomaEN
Citas recibidas3
Referencias citadas28

Provenance research in museums has traditionally been reactive and focused on singular objects with dubious histories, such as colonial-era acquisitions, Nazi-looted art, and objects with active ownership claims; the ‘crimes’ we expect to see. But what if what we think we know prevents us from seeing the bigger picture within and across museum collections? We argue that a machine-learning approach to provenance could allow the detection of broader patterns of unethical or even criminal behaviour that are embedded in the relationships underpinning museum collections. To demonstrate the potential of a machine-learning approach, we present a computer-assisted model that predicts plausible patterns and connections, ‘leads’ or ‘hot tips’, derived from a dataset of unstructured texts concerning the antiquities trade. Preliminary results have revealed what may have been a multi-decade scheme involving the donation of low-value Latin American antiquities to museums as a form of ‘reputation laundering’ potentially in advance of criminal fraud. We believe that such patterns could not be identified by an approach to museum provenance that is restricted to known problems within individual institution, demonstrating the need for innovative provenance tools and approaches that consider the complex networks within which museum objects exist

Institution · Money Laundering · Political science · Provenance · Reputation · Archaeological Research and Protection · Art History and Market Analysis · Computer Science · History · Law · Artificial Intelligence