共 60 条
[1]
Ananny M., Crawford K., Seeing without knowing: limitations of the transparency ideal and its application to algorithmic accountability, New Media & Society, (2017)
[2]
Anderson C.W., Deliberative, agonistic, and algorithmic audiences: journalism’s vision of its public in an age of audience transparency, International Journal of Communication Systems, 5, (2011)
[3]
Barocas S., Selbst A.D., Big Data’s Disparate Impact, (2016)
[4]
Bostrom N., Ethical Issues in Advanced Artificial Intelligence, Science Fiction and Philosophy: From Time Travel To. Books.Google.Com, (2003)
[5]
Bovens M., Goodin R.E., Schillemans T., The Oxford Handbook of Public Accountability, (2014)
[6]
Box G.E.P., Draper N.R., Empirical model-building and response surfaces, 424, (1987)
[7]
Bozdag E., Bias in algorithmic filtering and personalization, Ethics and Information Technology, 15, 3, pp. 209-227, (2013)
[8]
Bratko I., Machine Learning: Between Accuracy and Interpretability, Learning, Networks and Statistics, pp. 163-177, (1997)
[9]
Burrell J., How the machine ‘thinks’: Understanding opacity in machine learning algorithms, Big Data & Society 3 (1): 2053951715622512 SAGE Publications Sage UK, (2016)
[10]
Danaher J., The threat of algocracy: reality, resistance and accommodation, Philosophy & Technology, 29, 3, pp. 245-268, (2016)