[
Angwin J., Larson J., Mattu S. and Kirchner L., Machine Bias, ProPublica 2016, https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing.
]Search in Google Scholar
[
Barfield W. and Pagallo U., Advanced Introduction to Law and Artificial Intelligence, Cheltenham/Northampton 2020.10.4337/9781789905137
]Search in Google Scholar
[
Barocas S. and Selbst A.D., Big Data’s disparate impact, “California Law Review” 2016, vol. 104, no. 2.10.2139/ssrn.2477899
]Search in Google Scholar
[
Berendt B., Preibusch S., Toward accountable discrimination-aware data mining: The importance of keeping human in the loop – and under the looking-glass, “Big Data” 2017, vol. 5, no. 2.10.1089/big.2016.0055
]Search in Google Scholar
[
Boden M.A., Sztuczna inteligencja. Jej natura i przyszłość, trans. T. Sieczkowski, Łódź 2020.
]Search in Google Scholar
[
Borysiak W. and Bosek L., Komentarz do art. 32, (in:) M. Safjan and L. Bosek (eds.), Konstytucja RP. Tom I. Komentarz do art. 1–86, Warsaw 2016.
]Search in Google Scholar
[
Brennan T., Dieterich W. and Ehret B., Evaluating the predictive validity of the COMPAS risk and needs assessment system, “Criminal Justice and Behavior” 2009, vol. 36, no. 1.10.1177/0093854808326545
]Search in Google Scholar
[
Cataleta M.S. and Cataleta A., Artificial Intelligence and Human Rights, an Unequal Struggle, “CIFILE Journal of International Law” 2020, vol. 1, no. 2.
]Search in Google Scholar
[
Coeckelbergh M., AI Ethics, Cambridge/London 2020.10.7551/mitpress/12549.001.0001
]Search in Google Scholar
[
Cummings M.L., Automation and Accountability in Decision Support System Interface Design, “The Journal of Technology Studies” 2006, vol. 32, no. 1.10.21061/jots.v32i1.a.4
]Search in Google Scholar
[
Danks D. and London A.J., Algorithmic Bias in Autonomous Systems, ‘Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017)’, https://www.cmu.edu/dietrich/philosophy/docs/london/IJCAI17-AlgorithmicBias-Distrib.pdf.10.24963/ijcai.2017/654
]Search in Google Scholar
[
Davenport T. and Kalakota R., The potential for artificial intelligence in healthcare, “Future Healthcare Journal” 2019, vol. 6, no. 2.10.7861/futurehosp.6-2-94
]Search in Google Scholar
[
Dymitruk M., Sztuczna inteligencja w wymiarze sprawiedliwości? (in:) L. Lai and M. Świerczyński (eds.), Prawo sztucznej inteligencji, Warsaw 2020.
]Search in Google Scholar
[
European Parliament resolution of 20 October 2020 with recommendations to the Commission on a framework of ethical aspects of artificial intelligence, robotics and related technologies (2020/2012(INL)).
]Search in Google Scholar
[
Fjeld J., Achten N., Hilligoss H., Nagy A. and Srikumar M., Principled Artificial Intelligence. Mapping Consensus in Ethical and Rights-Based Approaches to Principles for AI, Cambridge 2020.10.2139/ssrn.3518482
]Search in Google Scholar
[
Flasiński M., Wstęp do sztucznej inteligencji, Warsaw 2020.
]Search in Google Scholar
[
Fry H., Hello world. Jak być człowiekiem w epoce maszyn, trans. S. Musielak, Krakow 2019.
]Search in Google Scholar
[
German S., Bienstock E. and Doursat R., Neural networks and bias/variance dilemma, “Neural Computation” 1992, vol. 4, no. 1.10.1162/neco.1992.4.1.1
]Search in Google Scholar
[
Hacker P., Teaching Fairness to Artificial Intelligence: Existing and Novel Strategies against Algorithmic Discrimination under EU Law, “Common Market Law Review” 2018, vol. 55.10.54648/COLA2018095
]Search in Google Scholar
[
High-Level Expert Group on Artificial Intelligence (appointed by the European Commission in June 2018), A Definition of Artificial Intelligence: Main Capabilities and Scientific Disciplines, Brussels 2019.
]Search in Google Scholar
[
High-Level Expert Group on Artificial Intelligence, Ethics Guidelines for Trustworthy AI, Brussels 2019.
]Search in Google Scholar
[
Jernigan C. and Mistree B.F., Gaydar: Facebook friendships expose sexual orientation, “First Monday” 2009, vol. 14, no. 10.10.5210/fm.v14i10.2611
]Search in Google Scholar
[
Kasperska A., Problemy zastosowania sztucznych sieci neuronalnych w praktyce prawniczej, „Przegląd Prawa Publicznego” 2017, no. 11.
]Search in Google Scholar
[
Lattimore F., O’Callaghan S., Paleologos Z., Reid A., Santow E., Sargeant H. and Thomsen A., Using artificial intelligence to make decisions: Addressing the problem of algorithmic bias. Technical Paper, Australian Human Rights Commission, Sydney 2020.
]Search in Google Scholar
[
Massey G. and Ehrensberger-Dow M., Machine learning: Implications for translator education, “Lebende Sprachen” 2017, vol. 62, no. 2.10.1515/les-2017-0021
]Search in Google Scholar
[
Michie D., Methodologies from Machine Learning in Data Analysis and Software, “The Computer Journal” 1991, vol. 34, no. 6.10.1093/comjnl/34.6.559
]Search in Google Scholar
[
Neff G. and Nagy P., Talking to Bots: Symbiotic Agency and the Case of Tay, “International Journal of Communication” 2016, no. 10.
]Search in Google Scholar
[
Ntoutsi E., Fafalios P., Gadiraju U., Iosifidis V., Nejdl W., Vidal M.-E., Ruggieri S., Turini F., Papadopoulos S., Krasanakis E., Kompatsiaris I., Kinder-Kurlanda K., Wagner C., Karimi F., Fernandez M., Alani H., Berendt B., Kruegel T., Heinze Ch., Broelemann K., Kasneci G., Tiropanis T. and Staab S., Bias in data-driven artificial intelligence systems – An introductory survey, “WIREs Data Mining Knowledge Discovery” 2020, vol. 10, no. 3.10.1002/widm.1356
]Search in Google Scholar
[
O’Neil C., Broń matematycznej zagłady. Jak algorytmy zwiększają nierówności i zagrażają demokracji, trans. M. Z. Zieliński, Warsaw 2017.
]Search in Google Scholar
[
Raji I.D., Buolamwini J., Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products, ‘Conference on Artificial Intelligence, Ethics, and Society’ 2019, https://www.media.mit.edu/publications/actionable-auditing-investigating-the-impact-of-publicly-naming-biased-performance-results-of-commercial-ai-products/.10.1145/3306618.3314244
]Search in Google Scholar
[
Ribeiro M.T., Singh S. and Guestrin C., „Why Should I Trust You?” Explaining the Predictions of Any Classifier, “22nd ACM SIGKDD International Conference 2016, San Francisco”, https://www.kdd.org/kdd2016/papers/files/rfp0573-ribeiroA.pdf.10.1145/2939672.2939778
]Search in Google Scholar
[
Rodrigues R., Legal and human rights issues of AI: Gaps, challenges and vulnerabilities, “Journal of Responsible Technology” 2020, vol. 4.10.1016/j.jrt.2020.100005
]Search in Google Scholar
[
Roselli D., Matthews J., Talagala N., Managing Bias in AI, “Companion Proceedings of the 2019 World Wide Web Conference, San Francisco, CA, USA”, May 2019.10.1145/3308560.3317590
]Search in Google Scholar
[
Rutkowski L., Metody i techniki sztucznej inteligencji, Warsaw 2012.
]Search in Google Scholar
[
White Paper On Artificial Intelligence. A European approach to excellence and trust, COM(2020) 65 final, European Commission, Brussels 2020.
]Search in Google Scholar
[
Yapo A. and Weiss J., Ethical Implications of Bias In Machine Learning, “Proceedings of the Annual Hawaii International Conference on System Sciences” 2018.10.24251/HICSS.2018.668
]Search in Google Scholar
[
Zuiderveen Borgesius F., Discrimination, artificial intelligence and algorithmic decision-making, Council of Europe, Strasbourg 2018.
]Search in Google Scholar
