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- W2904112238 abstract "Technological advances enable big data and its use in creating ‘predictive algorithms’, used to socially engineer and further political agendas. Welfare ideology in the UK operates in a climate of considerable political chaos and uncertainty, economic downturn and a rise in extremist views since the EU Referendum in 2016. In this context, there are considerable dangers in singling out vulnerable groups for State interference into private family life via algorithmic predictions. This paper identifies and explores a dual danger in the current climate: Inaccuracy and victimisation. Predictive analytic systems used in social work to predict and prevent child abuse unconsciously draw on germ theory to justify their approach. This ideological basis presents a theoretically elegant but flawed theory of child abuse eradication. In addition to the flawed science assuming child abuse is analogous to germs, the unstable political and confused ideological climate in the UK presents dangers to minority and disadvantaged groups targeted by predictive analytics. Identification via big data, ‘othering’, and consequential social engineering via forced separation of families is unregulated by ethical or legal charter. Reflection on the fate of the vulnerable in chaotic political regimes offers a glimpse of a dystopian future and a compelling argument for regulation." @default.
- W2904112238 created "2018-12-22" @default.
- W2904112238 creator A5079419267 @default.
- W2904112238 date "2018-12-06" @default.
- W2904112238 modified "2023-09-25" @default.
- W2904112238 title "'Dirty science': Big data, algorithms social work prediction systems" @default.
- W2904112238 hasPublicationYear "2018" @default.
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