Subject: A | Algorithmic accountability, algorithms, discrimination, machine learning, personal data, privacy | General Works
Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used to train them. While computational techniques are emerging to address aspects of these concerns through communities such as discrimination-aware data mining... View more
Agrawal R and Srikant R (2000) Privacy-preserving data mining. In: SIGMOD '00: Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data, New York, NY, 16-18 May, pp. 439-450. Available at: http://dx.doi.org/10.1145/335191.335438.
Andrews R, Diederich J and Tickle AB (1995) Survey and critique of techniques for extracting rules from trained artificial neural networks. Knowledge-Based Systems 8(6): 373-389.
Angwin J, Larson J, Mattu S, et al. (2016) Machine bias: There's software used across the country to predict future criminals, and it's biased against blacks. ProPublica 23 May.
Azavea (2015) HunchLab: Under the Hood. Philadelphia, PA: Author. Available at: http://cdn.azavea.com/pdfs/hunchlab/ HunchLab-Under-the-Hood.pdf.
Barocas S and Selbst AD (2016) Big Data's disparate impact. California Law Review 104: 671-732.
Behrens JT (1997) Principles and procedures of exploratory data analysis. Psychological Methods 2(2): 131-160.
Berendt B and Preibusch S (2014) Better decision support through exploratory discrimination-aware data mining: Foundations and empirical evidence. Artificial Intelligence and Law 22(2): 175-209.
Berk R, Heidari H, Jabbari S, et al. (2017) Fairness in criminal justice risk assessments: The state of the art. arXiv [stat.ML]. Available at: http://arxiv.org/abs/ 1703.09207 (accessed 20 April 2017).
Binns R (2017) Data protection impact assessments: A metaregulatory approach. International Data Privacy Law 7(1): 22-35.
Binns R, Veale M, Van Kleek M, et al. (2017) Like trainer, like bot? Inheritance of bias in algorithmic content moderation. In: Ciampaglia G, et al. (eds) Social informatics: 9th international conference, SocInfo 2017, Oxford, UK, 13-15 September, Proceedings, Part II. Cham: Springer, pp. 405-415. Available at: https://doi.org/10.1007/978-3- 319-67256-4_32.