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These aspirations are often coupled with a focus on responsibility, ethics and transparency, as well as emergent forms of regulation that seek to set demands for corporate conduct and the protection of civic rights. And the Protective measures include methods of traceability and assessments of \u2018good\u2019 and \u2018bad\u2019 datasets and algorithms that are considered to be traceable, stable and contained. However, these ways of thinking about both technology and ethics obscure a fundamental issue, namely that machine learning systems entangle data, algorithms and more-than-human environments in ways that challenge a well-defined separation. This article investigates the fundamental fallacy of most data reuse strategies as well as their regulation and mitigation strategies that data can somehow be followed, contained and controlled in machine learning processes. Instead, the article argues that we need to understand the reuse of data as an inherently entangled phenomenon. To examine this tension between the discursive regimes and the realities of data reuse, we advance the notion of reuse entanglements as an analytical lens. The main contribution of the article is the conceptualization of reuse that places entanglements at its core and the articulation of its relevance using empirical illustrations. This is important, we argue, for our understanding of the nature of data and algorithms, for the practical uses of data and algorithms and our attitudes regarding ethics, responsibility and regulation. <\/jats:p>","DOI":"10.1177\/20539517221139785","type":"journal-article","created":{"date-parts":[[2022,12,14]],"date-time":"2022-12-14T05:59:39Z","timestamp":1670997579000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":26,"title":["Politics of data reuse in machine learning systems: Theorizing reuse entanglements"],"prefix":"10.1177","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6094-2970","authenticated-orcid":false,"given":"Nanna Bonde","family":"Thylstrup","sequence":"first","affiliation":[{"name":"Department of Management, Society and Communication, Copenhagen Business School, Frederiksberg, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9536-6050","authenticated-orcid":false,"given":"Kristian Bondo","family":"Hansen","sequence":"additional","affiliation":[{"name":"Department of Management, Society and Communication, Copenhagen Business School, Frederiksberg, Denmark"}]},{"given":"Mikkel","family":"Flyverbom","sequence":"additional","affiliation":[{"name":"Department of Management, Society and Communication, Copenhagen Business School, Frederiksberg, Denmark"}]},{"given":"Louise","family":"Amoore","sequence":"additional","affiliation":[{"name":"Department of Geography, Durham University, Durham, UK"}]}],"member":"179","published-online":{"date-parts":[[2022,12,13]]},"reference":[{"key":"bibr111-20539517221139785","author":"Aaen J","year":"2021","journal-title":"European Journal of Information Systems"},{"key":"bibr1-20539517221139785","doi-asserted-by":"publisher","DOI":"10.1386\/pop.9.2.131_1"},{"key":"bibr2-20539517221139785","volume-title":"What\u2019s the Use?","author":"Ahmed S","year":"2019"},{"key":"bibr112-20539517221139785","doi-asserted-by":"publisher","DOI":"10.1177\/1024529417712830"},{"key":"bibr3-20539517221139785","volume-title":"Managing by Data: Algorithmic Categories and Organizing","author":"Alaimo C","year":"2020"},{"key":"bibr4-20539517221139785","doi-asserted-by":"publisher","DOI":"10.4337\/9781788119986.00022"},{"key":"bibr5-20539517221139785","unstructured":"Alden W (2018) Palantir had no policy on social media data collection prior to 2015. 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