Unfairness in Machine Learning for Web Systems Applications
Resumo
Machine learning models are increasingly present in our society; many of these models integrate Web Systems and are directly related to the content we consume daily. Nonetheless, on several occasions, these models have been responsible for decisions that spread prejudices or even decisions, if committed by humans, that would be punishable. After several cases of this nature came to light, research and discussion topics such as Fairness in Machine Learning and Artificial Intelligence Ethics gained a boost of importance and urgency in our society. Thus, one way to make Web Systems fairer in the future is to show how they can currently be unfair. In order to support discussions and be a reference for unfairness cases in machine learning decisions, this work aims to organize in a single document known decision-making that was wholly or partially supported by machine learning models that propagated prejudices, stereotypes, and inequalities in Web Systems. We conceptualize relevant categories of unfairness (such as Web Search and Deep Fake), and when possible, we present the solution adopted by those involved. Furthermore, we discuss approaches to mitigate or prevent discriminatory effects in Web Systems decision-making based on machine learning.
Palavras-chave:
Data Bias, Machine Learning, Unfairness Examples, Web Systems
Referências
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Joy Buolamwini and Timnit Gebru. 2018. Gender shades: Intersectional accuracy disparities in commercial gender classification. In Conference on fairness, accountability and transparency. 77–91
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Amelia Butterly. 2015. Google Image search for CEO has Barbie as first female result. [link]
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Maria De-Arteaga, Alexey Romanov, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, and Adam Tauman Kalai. 2019. Bias in bios: A case study of semantic representation bias in a high-stakes setting. In Conference on Fairness, Accountability, and Transparency. 120–128.
Ana Luisa Zago de Moraes, Lutiana Valadares Fernandes Barbosa, and Viviane Ceolin Dallasta Del Grossi. 2022. Inteligência artificial e direitos humanos: aportes para um marco regulatório no Brasil. Editora Dialética
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Michael Feldman, Sorelle A Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian. 2015. Certifying and removing disparate impact. In ACM SIGKDD. 259–268
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Viraj Gaur. 2022. Deepfakes Invade LinkedIn, Delhi Firm Offers ‘Ready to Use’ Profiles: Report. [link].
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Shirin Ghaffary. 2021. Racist trolls attacked England’s soccer team. Fans fought back. [link].
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James Griffiths. 2016. New Zealand passport robot thinks this Asian man’s eyes are closed. [link].
Ben Guarino. 2016. Google faulted for racial bias in image search results for black teenagers. [link].
Haleluya Hadero. 2023. Deepfake porn could be a growing problem amid AI race. [link].
Moritz Hardt, Eric Price, and Nati Srebro. 2016. Equality of opportunity in supervised learning. Advances in neural information processing systems 29 (2016), 3315–3323
GM Harshvardhan, Mahendra Kumar Gourisaria, Manjusha Pandey, and Siddharth Swarup Rautaray. 2020. A comprehensive survey and analysis of generative models in machine learning. Computer Science Review 38 (2020), 100285
Alex Hern. 2020. Twitter apologises for ’racist’ image-cropping algorithm. [link].
Kashmir Hill. 2016. Facebook recommended a psychiatrist’s patients friend each other — and there’s no clear explanation. [link].
ALex Horton. 2018. A fake photo of Emma González went viral on the far right, where Parkland teens are villains. [link].
Ayanna Howard and Jason Borenstein. 2018. The ugly truth about ourselves and our robot creations: the problem of bias and social inequity. Science and engineering ethics 24, 5 (2018), 1521–1536
Claran Jones. 2018. Facial recognition wrongly identified 2,000 people as possible criminals when Champions League final came to Cardiff. [link].
Edward Ongweso Jr. 2022. Scammers Use Elon Musk Deepfake to Steal Crypto. [link].
Edward Ongweso Jr. 2022. This Startup Is Selling Tech to Make Call Center Workers Sound Like White Americans. [link].
JTA. 2016. Microsoft Pulls Robot After It Tweets ’Hitler Was Right I Hate the Jews’. [link].
Faisal Kamiran and Toon Calders. 2012. Data preprocessing techniques for classification without discrimination. Knowledge and Information Systems 33, 1 (2012), 1–33.
Paramjit Kaur, Kewal Krishan, Suresh K Sharma, and Tanuj Kanchan. 2020. Facial-recognition algorithms: A literature review. Medicine, Science and the Law 60, 2 (2020), 131–139
Siobhan Kennedy. 2017. Potentially deadly bomb ingredients are ‘frequently bought together’ on Amazon. [link].
Oluwanifemi Kolawole. 2020. Why Facebook labelled content from #LekkiMassacre2020 incident ’false’. [link].
Adam DI Kramer, Jamie E Guillory, and Jeffrey T Hancock. 2014. Experimental evidence of massive-scale emotional contagion through social networks. National Academy of Sciences 111, 24 (2014), 8788–8790
Preethi Lahoti, Krishna P Gummadi, and Gerhard Weikum. 2019. ifair: Learning individually fair data representations for algorithmic decision making. In Conference on Data Engineering (ICDE). IEEE, 1334–1345
David Lazer, Ryan Kennedy, Gary King, and Alessandro Vespignani. 2014. The parable of Google Flu: traps in big data analysis. Science 343, 6176 (2014), 1203–1205
Dave Lee. 2016. Tay: Microsoft issues apology over racist chatbot fiasco. [link]
Sam Levin. 2016. A beauty constest was judged by AI and the robots didn’t like dark skin. [link].
Bing Liu and Lei Zhang. 2012. A Survey of Opinion Mining and Sentiment Analysis. Springer US, Boston, MA, 415–463
Linyuan Lü, Matúš Medo, Chi Ho Yeung, Yi-Cheng Zhang, Zi-Ke Zhang, and Tao Zhou. 2012. Recommender systems. Physics reports 519, 1 (2012), 1–49
Kristian Lum and James Johndrow. 2016. A statistical framework for fair predictive algorithms. (2016)
Justin McCurry. 2021. South Korean AI chatbot pulled from Facebook after hate speech towards minorities. [link].
Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, and Aram Galstyan. 2021. A survey on bias and fairness in machine learning. ACM Comput. Surv. 54, 6 (2021), 1–35.
Ruby Mellen. 2020. Buenos Aires is using facial recognition system that tracks child suspects, rights group says. [link].
Maria Mellor. 2020. Why is TikTok creating filter bubbles based on your race? (2020). [link].
Petra Molnar. 2019. Technology on the margins: AI and global migration management from a human rights perspective. Cambridge International Law Journal 8 (12 2019), 305–330. https://doi.org/10.4337/cilj.2019.02.07
Jornal Nacional. 2022. Deepfake: conteúdo do Jornal Nacional é adulterado para desinformar os eleitores. [link].
Mark Newman. 2010. Networks: An Introduction. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199206650.001.0001.
CBS news. 2019. Doctored Nancy Pelosi video highlights threat of "deepfake" tech. [link].
Safiya Umoja Noble. 2018. Algorithms of oppression. In Algorithms of oppression. New York University Press
Alexandra Olteanu, Carlos Castillo, Fernando Diaz, and Emre Kiciman. 2019. Social data: Biases, methodological pitfalls, and ethical boundaries. Frontiers in Big Data 2 (2019), 13
Dana Pessach and Erez Shmueli. 2022. A review on fairness in machine learning. ACM Computing Surveys (CSUR) 55, 3 (2022), 1–44.
Rute Pina. 2022. Feminismo: Google mostra anúncio que deturpa conceito como 1º resultado. [link].
Geoff Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, and Kilian Q Weinberger. 2017. On fairness and calibration. Advances in Neural Information Processing Systems 30 (2017), 5680–5689
Kevin Roose. 2019. The Making of a YouTube Radical. [link].
Adam Rose. 2010. Are Face-Detection Cameras Racist? [link]
Adam Satariano and Paul Mozur. 2023. The People Onscreen Are Fake. The Disinformation Is Real. [link].
Tatiana Serafin. 2022. Ukraine’s President Zelensky Takes the Russia/Ukraine War Viral. Orbis 66, 4 (2022), 460–476
Tom Simonite. 2018. When It Comes to Gorillas, Google Photos Remains Blind. [link].
Tom Simonite. 2019. Artificial Intelligence Is Coming for Our Faces. [link].
Jacob Snow. 2018. Amazon’s Face Recognition Falsely Matched 28 Members of Congress With Mugshots. [link].
Felix Stahlberg. 2020. Neural machine translation: A review. Journal of Artificial Intelligence Research 69 (2020), 343–418
Catherine Stupp. 2019. Fraudsters Used AI to Mimic CEO’s Voice in Unusual Cybercrime Case. [link].
Kristi Sturgill. 2020. Santa Cruz becomes the first U.S. city to ban predictive policing. [link].
Anisa Subedar and Will Yates. 2015. The disturbing YouTube videos that are tricking children. [link]
Shiliang Sun, Chen Luo, and Junyu Chen. 2017. A review of natural language processing techniques for opinion mining systems. Information Fusion 36 (2017), 10–25.
Latanya Sweeney. 2013. Discrimination in online ad delivery. Queue 11, 3 (2013), 10–29.
Kat Tenbarge. 2023. Found through Google, bought with Visa and Mastercard: Inside the deepfake porn economy. [link].
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Publicado
23/10/2023
Como Citar
MINATEL, Diego; DOS SANTOS, Nícolas Roque; DA SILVA, Angelo Cesar Mendes; CÚRI, Mariana; MARCACINI, Ricardo Marcondes; LOPES, Alneu de Andrade.
Unfairness in Machine Learning for Web Systems Applications. In: SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 29. , 2023, Ribeirão Preto/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 144–153.
