research-article

Beyond transparency: a proposed framework for accountability in decision-making AI systems

Authors:

Janelle Berscheid,

Francois Roewer-DespresAuthors Info & Claims

AI Matters, Volume 5, Issue 2

Pages 13 - 22

https://doi.org/10.1145/3340470.3340476

Published: 05 August 2019 Publication History

Abstract

Transparency in decision-making AI systems can only become actionable in practice when all stakeholders share responsibility for validating outcomes. We propose a three-party regulatory framework that incentivizes collaborative development in the AI ecosystem and guarantees fairness and accountability are not merely afterthoughts in high-impact domains.

References

[1]

Angwin, J., & Larson, J. (2016, May). Machine Bias. Retrieved 2019-01-09, from https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing

[2]

Diallo, I. (2018, June). The Machine Fired Me. Retrieved 2019-01-02, from https://idiallo.com/blog/when-a-machine-fired-me

[3]

Freedland, J. (2018, April). Zuckerberg got off lightly. Why are politicians so bad at asking questions? The Guardian. Retrieved 2019-02-16, from https://www.theguardian.com/commentisfree/2018/apr/11/mark-zuckerberg-facebook-congress-senate

[4]

GDPR. (2016, May). Regulation (eu) 2016/679 of the european parliament and of the council of 27 april 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing directive 95/46/ec. Official Journal of the European Union, L119, 1--88.

[5]

Good, B. J. (1993). Medicine, rationality and experience: an anthropological perspective. Cambridge University Press.

[6]

Kang, C., Kaplan, T., & Fandos, N. (2018, April). Knowledge Gap Hinders Ability of Congress to Regulate Silicon Valley. The New York Times. Retrieved 2019-02-16, from https://www.nytimes.com/2018/04/12/business/congress-facebook-regulation.html

[7]

Merchant, B. (2018, December). Predictim Claims Its AI Can Flag 'Risky' Babysitters. So I Tried It on the People Who Watch My Kids. Retrieved 2018-12-27, from https://gizmodo.com/predictim-claims-its-ai-can-flag-risky-babysitters-so-1830913997

[8]

Miller, T., Howe, P., & Sonenberg, L. (2017, December). Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences. arXiv:1712.00547 {cs}. Retrieved 2019-01-08, from http://arxiv.org/abs/1712.00547 (arXiv: 1712.00547)

[9]

Mozur, P. (2018, October). A Genocide Incited on Facebook, With Posts From Myanmar's Military. The New York Times. Retrieved 2019-01-11, from https://www.nytimes.com/2018/10/15/technology/myanmar-facebook-genocide.html

[10]

Perry, T. S. (2018, September). Intel Execs Address the AI Talent Shortage, AI Education, and the "Cool" Factor. Retrieved 2019-01-10, from https://spectrum.ieee.org/view-from-the-valley/robotics/artificial-intelligence/intel-execs-address-the-ai-talent-shortage-ai-education-and-the-cool-factor

[11]

Ribeiro, M. T., Singh, S., & Guestrin, C. (2016). "Why Should I Trust You?": Explaining the Predictions of Any Classifier. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '16 (pp. 1135--1144). San Francisco, California, USA: ACM Press. Retrieved 2019-01-08, from http://dl.acm.org/citation.cfm?doid=2939672.2939778

Digital Library

[12]

Sculley, D., Holt, G., Golovin, D., Davydov, E., Phillips, T., Ebner, D., . . . Dennison, D. (2015). Hidden technical debt in machine learning systems. In Advances in neural information processing systems (pp. 2503--2511).

Digital Library

[13]

Smith, A. (2018, November). Public Attitudes Toward Computer Algorithms. Retrieved 2019-01-05, from http://www.pewinternet.org/2018/11/16/attitudes-toward-algorithmic-decision-making/

[14]

Soon, C. S., Brass, M., Heinze, H.-J., & Haynes, J.-D. (2008, May). Unconscious determinants of free decisions in the human brain. Nature Neuroscience, 11(5), 543--545. Retrieved 2019-02-16, from http://www.nature.com/articles/nn.2112

[15]

Storm, D. (2016, May). Faception can allegedly tell if you're a terrorist just by analyzing your face. Retrieved 2019-01-01, from https://www.computerworld.com/article/3075339/security/faception-can-allegedly-tell-if-youre-a-terrorist-just-by-analyzing-your-face.html

[16]

Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., & Fergus, R. (2013). Intriguing properties of neural networks. arXiv:1312.6199 {cs}. Retrieved 2019-01-08, from http://arxiv.org/abs/1312.6199 (arXiv: 1312.6199)

[17]

Tversky, A., & Kahneman, D. (1981, January). The framing of decisions and the psychology of choice. Science, 211(4481), 453--458. Retrieved 2019-02-16, from http://www.sciencemag.org/cgi/doi/10.1126/science.7455683

[18]

Whittaker, M., Crawford, K., Dobbe, R., Fried, G., Mathur, V., West, S. M., . . . Schwartz, O. (2018, December). AI Now Report 2018 (Tech. Rep.). AI Now Institute, New York University. Retrieved from https://ainowinstitute.org/AI_Now_2018_Report.pdf

[19]

y Arcas, B. A., Mitchell, M., & Todorov, A. (2017, May). Physiognomy's New Clothes. Retrieved 2019-01-07, from https://medium.com/@blaisea/physiognomys-new-clothes-f2d4b59fdd6a

Cited By

Vann Yaroson EAbadie ARoux M(2025)Human-artificial intelligence collaboration in supply chain outcomes: the mediating role of responsible artificial intelligenceAnnals of Operations Research10.1007/s10479-025-06534-7Online publication date: 1-Mar-2025
https://doi.org/10.1007/s10479-025-06534-7
Deck LSchoeffer JDe-Arteaga MKühl N(2024)A Critical Survey on Fairness Benefits of Explainable AIProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3658990(1579-1595)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3630106.3658990
Swaminathan NDanks D(2024)Governing Ethical Gaps in Distributed AI DevelopmentDigital Society10.1007/s44206-024-00088-03:1Online publication date: 15-Feb-2024
https://doi.org/10.1007/s44206-024-00088-0
Show More Cited By

Recommendations

Transparency and Accountability After 2015: e-Parliament for Citizens' Engagement in the Ghanaian Environment
ICEGOV '15-16: Proceedings of the 9th International Conference on Theory and Practice of Electronic Governance

Beyond providing information, Information and Communication Technology (ICT) really contributes to citizens' participation to public debate. With the use of ICT, Civil societies have played a big role especially in the areas of training, research, ...
Beyond Transparency: Exploring Algorithmic Accountability
GROUP '20: Companion Proceedings of the 2020 ACM International Conference on Supporting Group Work

Many of the ubiquitous algorithmic systems permeating society have come under scrutiny due to their lack of accountability. As algorithmic decision making increasingly affects our lives, calls to improve the transparency of these systems are met with ...
Privacy transparency patterns
EuroPLoP '15: Proceedings of the 20th European Conference on Pattern Languages of Programs

This paper describes two privacy patterns for creating privacy transparency: the Personal Data Table pattern and the Privacy Policy Icons pattern, as well as a full overview of privacy transparency patterns. It is a first step in creating a full set of ...

Comments

Information & Contributors

Information

Published In

cover image AI Matters

AI Matters Volume 5, Issue 2

June 2019

44 pages

EISSN:2372-3483

DOI:10.1145/3340470

Editors:
Amy McGovern
U. Oklahoma
,
Iolanda Leite
KTH

Issue’s Table of Contents

Copyright © 2019 Authors.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 August 2019

Published in SIGAI-AIMATTERS Volume 5, Issue 2

Check for updates

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

14
Total Citations
View Citations
409
Total Downloads

Downloads (Last 12 months)27
Downloads (Last 6 weeks)4

Reflects downloads up to 08 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Vann Yaroson EAbadie ARoux M(2025)Human-artificial intelligence collaboration in supply chain outcomes: the mediating role of responsible artificial intelligenceAnnals of Operations Research10.1007/s10479-025-06534-7Online publication date: 1-Mar-2025
https://doi.org/10.1007/s10479-025-06534-7
Deck LSchoeffer JDe-Arteaga MKühl N(2024)A Critical Survey on Fairness Benefits of Explainable AIProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3658990(1579-1595)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3630106.3658990
Swaminathan NDanks D(2024)Governing Ethical Gaps in Distributed AI DevelopmentDigital Society10.1007/s44206-024-00088-03:1Online publication date: 15-Feb-2024
https://doi.org/10.1007/s44206-024-00088-0
Saheb TSaheb T(2023)Topical review of artificial intelligence national policies: A mixed method analysisTechnology in Society10.1016/j.techsoc.2023.10231674(102316)Online publication date: Aug-2023
https://doi.org/10.1016/j.techsoc.2023.102316
Krüger SWilson C(2023)The problem with trust: on the discursive commodification of trust in AIAI & Society10.1007/s00146-022-01401-638:4(1753-1761)Online publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1007/s00146-022-01401-6
Gudigantala NMadhavaram SBicen P(2023)An AI decision‐making framework for business value maximizationAI Magazine10.1002/aaai.1207644:1(67-84)Online publication date: 5-Apr-2023
https://dl.acm.org/doi/10.1002/aaai.12076
Deshpande ASharp HConitzer VTasioulas JScheutz MCalo RMara MZimmermann A(2022)Responsible AI Systems: Who are the Stakeholders?Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society10.1145/3514094.3534187(227-236)Online publication date: 26-Jul-2022
https://dl.acm.org/doi/10.1145/3514094.3534187
Enayati SPishro-Nik H(2022)Asymmetric Change-of-Probability Measures for Tail Risk Management2022 IEEE International Systems Conference (SysCon)10.1109/SysCon53536.2022.9773926(1-7)Online publication date: 25-Apr-2022
https://doi.org/10.1109/SysCon53536.2022.9773926
de Hond ALeeuwenberg AHooft LKant INijman Svan Os HAardoom JDebray TSchuit Evan Smeden MReitsma JSteyerberg EChavannes NMoons K(2022)Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping reviewnpj Digital Medicine10.1038/s41746-021-00549-75:1Online publication date: 10-Jan-2022
https://doi.org/10.1038/s41746-021-00549-7
Wilson Cvan der Velden M(2022)Sustainable AI: An integrated model to guide public sector decision-makingTechnology in Society10.1016/j.techsoc.2022.10192668(101926)Online publication date: Feb-2022
https://doi.org/10.1016/j.techsoc.2022.101926
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Issue’s Table of Contents