1. bookVolume 26 (2021): Issue 3 (September 2021)
Journal Details
License
Format
Journal
eISSN
2719-9452
First Published
01 Jan 2006
Publication timeframe
4 times per year
Languages
English, Polish
Open Access

Bias in Artificial Intelligence Systems

Published Online: 22 Oct 2021
Volume & Issue: Volume 26 (2021) - Issue 3 (September 2021)
Page range: 25 - 42
Received: 19 Dec 2020
Accepted: 25 Mar 2021
Journal Details
License
Format
Journal
eISSN
2719-9452
First Published
01 Jan 2006
Publication timeframe
4 times per year
Languages
English, Polish
Abstract

Artificial intelligence systems are currently deployed in many areas of human activity. Such systems are increasingly assigned tasks that involve taking decisions about people or predicting future behaviours. These decisions are commonly regarded as fairer and more objective than those taken by humans, as AI systems are thought to be resistant to such influences as emotions or subjective beliefs. In reality, using such a system does not guarantee either objectivity or fairness. This article describes the phenomenon of bias in AI systems and the role of humans in creating it. The analysis shows that AI systems, even if operating correctly from a technical standpoint, are not guaranteed to take decisions that are more objective than those of a human, but those systems can still be used to reduce social inequalities.

Keywords

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

Recommended articles from Trend MD

Plan your remote conference with Sciendo