2016

ANANNY, M. (2016). Toward an Ethics of Algorithms: Convening, Observation, Probability, and Timeliness. Science Technology and Human Values, 41(1), 93–117

ARNOLDI, Jakob. Computer algorithms, market manipulation and the institutionalization of high frequency trading. Theory, Culture & Society, v. 33, n. 1, p. 29-52, 2016.

BAROCAS, Solon; SELBST, Andrew D. Big data's disparate impact. Cal. L. Rev., v. 104, p. 671, 2016.

BELLANOVA, Rocco (2016) Digital, politics, and algorithms: Governing digital data through the lens of data protection, European Journal of Social Theory. DOI: 10.1177/1368431016679167: 1–19.

BILIC, Paško, Search algorithms, hidden labour and information control. Big Data & Society, 2016. DOI: https://doi.org/10.1177/2053951716652159.

BURRELL, Jenna. How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big Data & Society, v. 3, n. 1, p. 2053951715622512, 2016.

CRAWFORD, Kate. Can an algorithm be agonistic? Ten scenes from life in calculated publics. Science, Technology, & Human Values, v. 41, n. 1, p. 77-92, 2016.

DANAHER, John. The threat of algocracy: Reality, resistance and accommodation. Philosophy & Technology, v. 29, n. 3, p. 245-268, 2016. https://link.springer.com/content/pdf/10.1007%2Fs13347-015-0211-1.pdf

DONEDA, D.; ALMEIDA, V. A. F. What Is Algorithm Governance? IEEE Internet Computing, v. 20, n. 4, p. 60-63, jul.-ago. 2016.

GOODMAN, Bryce; FLAXMAN, Seth. European Union regulations on algorithmic decision-making and a" right to explanation". arXiv preprint arXiv:1606.08813, 2016.

INTRONA, Lucas D. Algorithms, governance, and governmentality: On governing academic writing. Science, Technology, & Human Values, v. 41, n. 1, p. 17-49, 2016.

INTRONA, Lucas D. (2016), The algorithmic choreography of the impressionable subject. in Seyfert, R.; Roberge j. (eds), Algorithmic Cultures: essays on meaning, performance and new technologies. Oxford: Routledge, pp. 26-51. (Routledge Advances in Sociology)

JANSSEN, Marijn; KUK, George. The challenges and limits of big data algorithms in technocratic governance. 2016.

KITCHIN, R.; McARDLE G. What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets. Big Data and Society. Epub ahead of print 2016. DOI: 10.1177/2053951716631130.

LI, Shaoyong ; XIAO, Xingda; CAI, Ying; MA, Bingshan; HOU, Caiqin; HAN, Xilian. (2016). An algorithm to evaluate implementation cost for liveness-enforcing supervisors designed by deadlock prevention policy. Advances in Mechanical Engineering. 8. 10.1177/1687814016658388.

MITTELSTADT, B.; FLORIDI, L. The ethics of Big Data: Current and foreseeable issues in biomedical contexts. Science and Engineering Ethics 22(2): 303–341, 2016.

O'NEIL, Cathy. Weapons of math destruction: How big data increases inequality and threatens democracy. Broadway Books, 2016.

REED, Laura; BOYD, Danah. Who Controls the Public Sphere in an Era of Algorithms?. 2016. New York: Data & Society, 2016.

REZAEI, Zadeh M., Hogan M., O’Reilly J., MURPHY, E. (2016). Core entrepreneurial competencies and their interdependencies: Insights from a study of Irish and Iranian entrepreneurs, university students and academics. International Entrepreneurship and Management Journal 13(1): 1–39.

ROUVROY, Antoinette; STIEGLER, Bernard. The digital regime of truth: From the algorithmic governmentality to a new rule of law. La Deleuziana: Online Journal of Philosophy, v. 3, p. 6-29, 2016. http://www.ladeleuziana.org/wp-content/uploads/2016/12/Rouvroy-Stiegler_eng.pdf

WAGNER, Ben. Algorithmic regulation and the global default: Shifting norms in Internet technology. Etikk i praksis-Nordic Journal of Applied Ethics, v. 10, n. 1, p. 5-13, 2016.

ZARSKY, T. The trouble with algorithmic decisions: An analytic road map to examine efficiency and fairness in automated and opaque decision making. Science, Technology, & Human Values, v. 41, n. 1, p. 118–132, 2016.

ZIEWITZ, Malte. Governing algorithms: Myth, mess, and methods. Science, Technology, & Human Values, v. 41, n. 1, p. 3-16, 2016.