References

References#

[AIG+22]

Mehwish Alam, Andreea Iana, Alexander Grote, Katharina Ludwig, Philipp Müller, and Heiko Paulheim. Towards Analyzing the Bias of News Recommender Systems Using Sentiment and Stance Detection. In Companion Proceedings of the Web Conference 2022, 448–457. Virtual Event, Lyon France, April 2022. ACM. URL: https://dl.acm.org/doi/10.1145/3487553.3524674 (visited on 2024-05-10), doi:10.1145/3487553.3524674.

[BD91]

Paul Beynon-Davies. Expert Database Systems: A Gentle Introduction. McGraw-Hill, 1991. ISBN 978-0-07-707240-7. Google-Books-ID: M6ZQAAAAMAAJ.

[CEVolkelB19]

Michael Chromik, Malin Eiband, Sarah Theres Völkel, and Daniel Buschek. Dark patterns of explainability, transparency, and user control for intelligent systems. In IUI workshops, volume 2327. 2019.

[DSDAK24]

Luca Deck, Jakob Schoeffer, Maria De-Arteaga, and Niklas Kühl. A Critical Survey on Fairness Benefits of Explainable AI. In The 2024 ACM Conference on Fairness, Accountability, and Transparency, 1579–1595. June 2024. arXiv:2310.13007 [cs]. URL: http://arxiv.org/abs/2310.13007 (visited on 2024-08-30), doi:10.1145/3630106.3658990.

[DHP+12]

Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel. Fairness through awareness. In Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, ITCS '12, 214–226. New York, NY, USA, January 2012. Association for Computing Machinery. URL: https://dl.acm.org/doi/10.1145/2090236.2090255 (visited on 2024-05-03), doi:10.1145/2090236.2090255.

[ESDCR23]

Upol Ehsan, Koustuv Saha, Munmun De Choudhury, and Mark O. Riedl. Charting the Sociotechnical Gap in Explainable AI: A Framework to Address the Gap in XAI. Proceedings of the ACM on Human-Computer Interaction, 7(CSCW1):1–32, April 2023. arXiv:2302.00799 [cs]. URL: http://arxiv.org/abs/2302.00799 (visited on 2024-09-02), doi:10.1145/3579467.

[FNS+21]

Xavier Ferrer, Tom Van Nuenen, Jose M. Such, Mark Cote, and Natalia Criado. Bias and Discrimination in AI: A Cross-Disciplinary Perspective. IEEE Technology and Society Magazine, 40(2):72–80, June 2021. URL: https://ieeexplore.ieee.org/document/9445793/ (visited on 2024-05-23), doi:10.1109/MTS.2021.3056293.

[FBG+22]

Jade S. Franklin, Karan Bhanot, Mohamed Ghalwash, Kristin P. Bennett, Jamie McCusker, and Deborah L. McGuinness. An Ontology for Fairness Metrics. In Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 265–275. Oxford United Kingdom, July 2022. ACM. URL: https://dl.acm.org/doi/10.1145/3514094.3534137 (visited on 2024-09-17), doi:10.1145/3514094.3534137.

[FSBH+23]

Sorelle Friedler, Ranjit Singh, Borhane Blili-Hamelin, Jacob Metcalf, and Brian J Chen. AI Red-Teaming Is Not a One-Stop Solution to AI Harms:. Technical Report, Data & Society, 2023.

[GBM17]

Sainyam Galhotra, Yuriy Brun, and Alexandra Meliou. Fairness testing: testing software for discrimination. In Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, 498–510. Paderborn Germany, August 2017. ACM. URL: https://dl.acm.org/doi/10.1145/3106237.3106277 (visited on 2024-05-03), doi:10.1145/3106237.3106277.

[HPPS16]

Moritz Hardt, Eric Price, Eric Price, and Nati Srebro. Equality of Opportunity in Supervised Learning. In D. Lee, M. Sugiyama, U. Luxburg, I. Guyon, and R. Garnett, editors, Advances in Neural Information Processing Systems, volume 29. Curran Associates, Inc., 2016. URL: https://proceedings.neurips.cc/paper_files/paper/2016/file/9d2682367c3935defcb1f9e247a97c0d-Paper.pdf.

[Hol24]

Tomasz Hollanek. The ethico-politics of design toolkits: responsible AI tools, from big tech guidelines to feminist ideation cards. AI and Ethics, August 2024. URL: https://link.springer.com/10.1007/s43681-024-00545-z (visited on 2024-08-29), doi:10.1007/s43681-024-00545-z.

[JW21]

Abigail Z. Jacobs and Hanna Wallach. Measurement and Fairness. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 375–385. March 2021. arXiv:1912.05511 [cs]. URL: http://arxiv.org/abs/1912.05511 (visited on 2023-11-22), doi:10.1145/3442188.3445901.

[KMR16]

Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan. Inherent Trade-Offs in the Fair Determination of Risk Scores. November 2016. arXiv:1609.05807 [cs, stat]. URL: http://arxiv.org/abs/1609.05807 (visited on 2024-05-03).

[KKKL+24]

Rik Koncel-Kedziorski, Michael Krumdick, Viet Lai, Varshini Reddy, Charles Lovering, and Chris Tanner. Bizbench: a quantitative reasoning benchmark for business and finance. 2024. URL: https://arxiv.org/abs/2311.06602, arXiv:2311.06602.

[KKT+21]

Adriano Koshiyama, Emre Kazim, Philip Treleaven, Pete Rai, Lukasz Szpruch, Giles Pavey, Ghazi Ahamat, Franziska Leutner, Randy Goebel, Andrew Knight, Janet Adams, Christina Hitrova, Jeremy Barnett, Parashkev Nachev, David Barber, Tomas Chamorro-Premuzic, Konstantin Klemmer, Miro Gregorovic, Shakeel Khan, and Elizabeth Lomas. Towards Algorithm Auditing: A Survey on Managing Legal, Ethical and Technological Risks of AI, ML and Associated Algorithms. SSRN Electronic Journal, 2021. URL: https://www.ssrn.com/abstract=3778998 (visited on 2024-05-14), doi:10.2139/ssrn.3778998.

[Les20]

David Leslie. Understanding Bias in Facial Recognition Technologies. SSRN Electronic Journal, 2020. URL: https://www.ssrn.com/abstract=3705658 (visited on 2024-08-12), doi:10.2139/ssrn.3705658.

[LGM20]

Q Vera Liao, Daniel Gruen, and Sarah Miller. Questioning the ai: informing design practices for explainable ai user experiences. In Proceedings of the 2020 CHI conference on human factors in computing systems, 1–15. 2020.

[MGB+21]

Vikram Mehta, Daniel Gooch, Arosha Bandara, Blaine Price, and Bashar Nuseibeh. Privacy Care: A Tangible Interaction Framework for Privacy Management. ACM Transactions on Internet Technology, 21(1):1–32, February 2021. URL: https://dl.acm.org/doi/10.1145/3430506 (visited on 2024-07-09), doi:10.1145/3430506.

[OSM+13]

Richard Owen, Jack Stilgoe, Phil Macnaghten, Mike Gorman, Erik Fisher, and Dave Guston. A Framework for Responsible Innovation. In Richard Owen, John Bessant, and Maggy Heintz, editors, Responsible Innovation, pages 27–50. Wiley, 1 edition, April 2013. URL: https://onlinelibrary.wiley.com/doi/10.1002/9781118551424.ch2 (visited on 2024-11-18), doi:10.1002/9781118551424.ch2.

[PC88]

Kamran Parsaye and Mark Chignell. Expert systems for experts. In Expert Systems for Experts, chapter 2.2.3, pages 42–53. John Wiley & Sons, Inc., New York, NY, USA, 1988.

[PLW02]

Leo L. Pipino, Yang W. Lee, and Richard Y. Wang. Data quality assessment. Communications of the ACM, 45(4):211–218, April 2002. URL: https://dl.acm.org/doi/10.1145/505248.506010 (visited on 2024-04-16), doi:10.1145/505248.506010.

[RM95]

Lance A. Ramshaw and Mitchell P. Marcus. Text Chunking using Transformation-Based Learning. May 1995. arXiv:cmp-lg/9505040. URL: http://arxiv.org/abs/cmp-lg/9505040 (visited on 2024-04-15), doi:10.48550/arXiv.cmp-lg/9505040.

[RRD24]

Shaina Raza, Deepak John Reji, and Chen Ding. Dbias: detecting biases and ensuring fairness in news articles. International Journal of Data Science and Analytics, 17(1):39–59, January 2024. URL: https://doi.org/10.1007/s41060-022-00359-4 (visited on 2024-04-15), doi:10.1007/s41060-022-00359-4.

[SHG+15]

D. Sculley, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips, Dietmar Ebner, Vinay Chaudhary, Michael Young, Jean-François Crespo, and Dan Dennison. Hidden technical debt in machine learning systems. In C. Cortes, N. Lawrence, D. Lee, M. Sugiyama, and R. Garnett, editors, Advances in Neural Information Processing Systems, volume 28. Curran Associates, Inc., 2015. URL: https://proceedings.neurips.cc/paper_files/paper/2015/file/86df7dcfd896fcaf2674f757a2463eba-Paper.pdf.

[SPK+21]

Timo Spinde, Manuel Plank, Jan-David Krieger, Terry Ruas, Bela Gipp, and Akiko Aizawa. Neural Media Bias Detection Using Distant Supervision With BABE - Bias Annotations By Experts. In Marie-Francine Moens, Xuanjing Huang, Lucia Specia, and Scott Wen-tau Yih, editors, Findings of the Association for Computational Linguistics: EMNLP 2021, 1166–1177. Punta Cana, Dominican Republic, November 2021. Association for Computational Linguistics. URL: https://aclanthology.org/2021.findings-emnlp.101 (visited on 2024-04-15), doi:10.18653/v1/2021.findings-emnlp.101.

[TCM+20]

Anja Thieme, Ed Cutrell, Cecily Morrison, Alex Taylor, and Abigail Sellen. Interpretability as a dynamic of human-AI interaction. Interactions, 27(5):40–45, September 2020. URL: https://dl.acm.org/doi/10.1145/3411286 (visited on 2024-09-02), doi:10.1145/3411286.

[WPHK25]

Angelina Wang, Michelle Phan, Daniel E. Ho, and Sanmi Koyejo. Fairness through difference awareness: measuring desired group discrimination in llms. 2025. URL: https://arxiv.org/abs/2502.01926, arXiv:2502.01926.

[WDA+16]

Mark D. Wilkinson, Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, Myles Axton, Arie Baak, Niklas Blomberg, Jan-Willem Boiten, Luiz Bonino da Silva Santos, Philip E. Bourne, Jildau Bouwman, Anthony J. Brookes, Tim Clark, Mercè Crosas, Ingrid Dillo, Olivier Dumon, Scott Edmunds, Chris T. Evelo, Richard Finkers, Alejandra Gonzalez-Beltran, Alasdair J. G. Gray, Paul Groth, Carole Goble, Jeffrey S. Grethe, Jaap Heringa, Peter A. C. ’t Hoen, Rob Hooft, Tobias Kuhn, Ruben Kok, Joost Kok, Scott J. Lusher, Maryann E. Martone, Albert Mons, Abel L. Packer, Bengt Persson, Philippe Rocca-Serra, Marco Roos, Rene van Schaik, Susanna-Assunta Sansone, Erik Schultes, Thierry Sengstag, Ted Slater, George Strawn, Morris A. Swertz, Mark Thompson, Johan van der Lei, Erik van Mulligen, Jan Velterop, Andra Waagmeester, Peter Wittenburg, Katherine Wolstencroft, Jun Zhao, and Barend Mons. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3(1):160018, March 2016. Publisher: Nature Publishing Group. URL: https://www.nature.com/articles/sdata201618 (visited on 2024-04-16), doi:10.1038/sdata.2016.18.

[WIL+23]

Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David Rosenberg, and Gideon Mann. Bloomberggpt: A large language model for finance. arXiv preprint arXiv:2303.17564, 2023. Type: Journal Article.

[YHW90]

Richard M. Young, Andrew Howes, and Joyce Whittington. A knowledge analysis of interactivity. In Dan Diaper, David J. Gilmore, Gilbert Cockton, and Brian Shackel, editors, INTERACT 90 - 3rd IFIP International Conference on Human-Computer Interaction, 115–120. Cambridge, UK, August 27-31 1990. Elsevier Science Publishers B.V.

[ZWS+13]

Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi, and Cynthia Dwork. Learning fair representations. In Sanjoy Dasgupta and David McAllester, editors, Proceedings of the 30th International Conference on Machine Learning, volume 28 of Proceedings of Machine Learning Research, 325–333. Atlanta, Georgia, USA, 17–19 Jun 2013. PMLR. URL: https://proceedings.mlr.press/v28/zemel13.html.

[CentrefDEaInnovationDepartmentfScienceITechnology24]

Centre for Data Ethics and Innovation and Department for Science, Innovation & Technology. Public attitudes to data and AI: Tracker survey (Wave 3) (Section 6: Attitudes towards AI). Technical Report, Centre for Data Ethics and Innovation, 2024. URL: https://www.gov.uk/government/publications/public-attitudes-to-data-and-ai-tracker-survey-wave-3/public-attitudes-to-data-and-ai-tracker-survey-wave-3.

[EHRC24]

EHRC. Artificial intelligence: checklist for public bodies in England \textbar EHRC. 2024. URL: https://www.equalityhumanrights.com/guidance/artificial-intelligence-checklist-public-bodies-england (visited on 2024-06-10).

[PRNewswire23]

PRNewswire. Large Language Model (LLM) Market Size to Grow USD 40.8 Billion by 2029 at a CAGR of 21.4% \textbar Valuates Reports. September 2023. URL: https://finance.yahoo.com/news/large-language-model-llm-market-151500260.html (visited on 2024-05-20).

[TheBoEngland22]

The Bank of England. Machine learning in UK financial services. Technical Report, The Bank of England, 2022. URL: https://www.bankofengland.co.uk/report/2022/machine-learning-in-uk-financial-services (visited on 2024-05-20).

[TheBoEngland23]

The Bank of England. Financial Policy Summary and Record of the Financial Policy Committee meeting on 21 November. Technical Report, The Bank of England, 2023. URL: https://www.bankofengland.co.uk/-/media/boe/files/financial-policy-summary-and-record/2023/fpc-summary-and-record-december-2023.pdf (visited on 2024-05-20).

Reading Recommendations#

  1. Zicari et al. 2022. How to Assess Trustworthy AI in Practice