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Table 3 Discriminatory outcomes of Big Data

From: Big Data and discrimination: perils, promises and solutions. A systematic review

Discriminatory outcomes Paper references
1. Forms of discrimination
 1.1. Accidental/involuntary discrimination Calders and Verwer 2010 [17], Schermer 2011 [73], Citron and Pasquale 2014 [21], Zarsky 2014 [93], Barocas and Selbst 2016 [8], Holtzhausen 2016 [39], Mantelero 2016 [54], Brayne 2017 [14], Chouldechova 2017 [20], d'Alessandro et al. 2017 [25], Kroll et al. 2017 [45]
 1.2. Direct voluntary discrimination Ajana 2015 [1], Holtzhausen 2016 [39], Kuempel 2016 [46]
2. Victims/targets of discrimination
 2.1. Vulnerable groups/populations Leese 2014 [48], Newell and Marabelli 2015 [58], Kuempel 2016 [46]
 2.2. Larger groups de Vries 2010 [27], Kennedy and Moss 2015 [44], Mantelero 2016 [54], Francis and Francis 2017 [30]
3. Discriminatory consequences
 3.1. Social marginalization and stigma Lerman 2013 [49], Casanas i Comabella and Wanat 2015 [18], Kennedy and Moss 2015 [44], Lupton 2015 [51], Susewind 2015 [76], Barocas and Selbst 2016 [8], Sharon 2016 [73], Francis and Francis 2017 [30], Pak et al. 2017 [60], Ploug and Holm 2017 [64], Taylor 2017 [79]
 3.2. Exacerbation of existing inequalities Timmis et al. 2016 [80], Brannon 2017 [13], Brayne 2017 [14], Pak et al. 2017 [60], Taylor 2017 [79], Voigt 2017 [85]
 3.3. New forms of discrimination
  3.3.1. Economic discrimination Hildebrandt and Koops 2010 [35], Peppet 2014 [62], Turow et al. 2015 [81]
  3.3.2. Health prediction discrimination Hoffman 2010 [37], Cohen et al. 2014 [22], Ajunwa et al. 2016 [2], Hoffman 2017 [38]