The Black Box Society: The Secret Algorithms That Control Money and Information
Abstract
the Watchers 140 6 Toward an Intelligible Society
Integrity signals
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AI systems are often black boxes.
“AI systems are often”
From Discrimination, artificial intelligence, and algorithmic decision-making (2025) · cites this paper as Pasquale 2015
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Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., et al. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.08.002 · Cited by 4,611 · see citing works
“The wider consequences of this phenomenon have been referred to as creating a “ black box society ” (Pasquale, 2015), and have profound implications for governments which, by de fi nition, are bound to citizen expectations of transparency and accountability.”
BackgroundEuropean Union Regulations on Algorithmic Decision Making and a “Right to Explanation”
Goodman, B., & Flaxman, S. (2017) · AI Magazine · doi:10.1609/aimag.v38i3.2741 · Cited by 2,131 · see citing works
Mittelstadt, B., Russell, C., & Wachter, S. (2019) · Proceedings of the Conference on Fairness, Accountability, and Transparency · doi:10.1145/3287560.3287574 · Cited by 794 · see citing works
Shneiderman, B. (2020) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3419764 · Cited by 768 · see citing works
Governing artificial intelligence: ethical, legal and technical opportunities and challenges
Cath, C. (2018) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2018.0080 · Cited by 745 · see citing works
The Chinese approach to artificial intelligence: an analysis of policy, ethics, and regulation
Roberts, H., Cowls, J., Morley, J., Taddeo, M., Wang, V., & Floridi, L. (2021) · AI & SOCIETY · doi:10.1007/s00146-020-00992-2 · Cited by 573 · see citing works
“care accessed across the population and on the integrity of the self (Andorno, 2004; Pasquale, 2015),(14) at least for those who are unable to afford human care.”
BackgroundWhere fairness fails: data, algorithms, and the limits of antidiscrimination discourse
Hoffmann, A. L. (2019) · Information, Communication & Society · doi:10.1080/1369118x.2019.1573912 · Cited by 535 · see citing works
Legal and human rights issues of AI: Gaps, challenges and vulnerabilities
Rodrigues, R. (2020) · Journal of Responsible Technology · doi:10.1016/j.jrt.2020.100005 · Cited by 494 · see citing works
Transparency in Algorithmic and Human Decision-Making: Is There a Double Standard?
Zerilli, J., Knott, A., Maclaurin, J., & Gavaghan, C. (2019) · Philosophy & Technology · doi:10.1007/s13347-018-0330-6 · Cited by 420 · see citing works
Explanations as Mechanisms for Supporting Algorithmic Transparency
Rader, E., Cotter, K., & Cho, J. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173677 · Cited by 388 · see citing works
Breaking the vicious cycle of algorithmic management: A virtue ethics approach to people analytics
Gal, U., Jensen, T. B., & Stein, M.-K. (2020) · Information and Organization · doi:10.1016/j.infoandorg.2020.100301 · Cited by 342 · see citing works
People analytics—A scoping review of conceptual boundaries and value propositions
Tursunbayeva, A., Di Lauro, S., & Pagliari, C. (2018) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2018.08.002 · Cited by 263 · see citing works
DeVito, M. A., Birnholtz, J., Hancock, J. T., French, M., & Liu, S. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173694 · Cited by 244 · see citing works
Passi, S., & Jackson, S. J. (2018) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3274405 · Cited by 225 · see citing works
Discrimination, artificial intelligence, and algorithmic decision-making
Borgesius, F. Z. (2025) · arXiv · doi:10.48550/arxiv.2510.13465 · Cited by 152 · see citing works
“27 Pasquale 2015.”
Reviewable Automated Decision-Making: A Framework for Accountable Algorithmic Systems
Cobbe, J., Lee, M. S. A., & Singh, J. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3442188.3445921 · Cited by 150 · see citing works
“This includes proposals for transparency of algorithms themselves, making code, model benchmarks, or other aspects of the model lifecycle available for scrutiny [10, 23, 45, 50, 56, 57].”
MethodStudent Vulnerability, Agency and Learning Analytics: An Exploration
Prinsloo, P., & Slade, S. (2016) · Journal of Learning Analytics · doi:10.18608/jla.2016.31.10 · Cited by 147 · see citing works
GLocalX—From Local to Global Explanations of Black Box AI Models
Setzu, M., Guidotti, R., Monreale, A., Turini, F., Pedreschi, D., & Giannotti, F. (2021) · Artificial Intelligence · doi:10.1016/j.artint.2021.103457 · Cited by 140 · see citing works
Parker, L., Halter, V., Karliychuk, T., & Grundy, Q. (2019) · International Journal of Law and Psychiatry · doi:10.1016/j.ijlp.2019.04.002 · Cited by 129 · see citing works
Grundy, Q., Chiu, K., Held, F., Continella, A., Bero, L., & Holz, R. (2019) · BMJ · doi:10.1136/bmj.l920 · Cited by 164 · see citing works
“18 Currently, within the “big data” industry, users do not own or control their personal data 10 11 ; at minimum, regulators should insist on full transparency, requiring sharing as opposed to privacy policies.”
BackgroundAlgorithmic Literacy and the Role for Libraries
Ridley, M., & Pawlick-Potts, D. (2021) · Information Technology and Libraries · doi:10.6017/ital.v40i2.12963 · Cited by 111 · see citing works
Decision Provenance: Harnessing Data Flow for Accountable Systems
Singh, J., Cobbe, J., & Norval, C. (2019) · IEEE Access · doi:10.1109/access.2018.2887201 · Cited by 110 · see citing works
Can a machine think (anything new)? Automation beyond simulation
Fazi, M. B. (2019) · AI & SOCIETY · doi:10.1007/s00146-018-0821-0 · Cited by 62 · see citing works
Ethics of Artificial Intelligence
(2019) · Research Library Issues · doi:10.29242/rli.299 · Cited by 59 · see citing works
Leonardi, P. M. (2025) · Information and Organization · doi:10.1016/j.infoandorg.2025.100582 · Cited by 47 · see citing works
Asthana, S., Im, J., Chen, Z., & Banovic, N. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642180 · Cited by 34 · see citing works
Taking Algorithms to Courts: A Relational Approach to Algorithmic Accountability
Metcalf, J., Singh, R., Moss, E., Tafesse, E., & Watkins, E. A. (2023) · 2023 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3593013.3594092 · Cited by 21 · see citing works
Hillo, J., Vento, I., & Erkkilä, T. (2026) · Public Administration · doi:10.1111/padm.70028 · Cited by 22 · see citing works
“This is important, given that algorithmic governance is often perceived as a “black box”, where the algorithm's logical functions and the data used are not publicly known (Pasquale 2016), leading to calls for algorithmic transparency (Aula and Erkkilä 2024).”
Trust and power in Airbnb's digital rating and reputation system
Christiaens, T. (2025) · Ethics and Information Technology · doi:10.1007/s10676-025-09825-6 · Cited by 11 · see citing works
“Apart from systematic biases in the data or platform design, there is, lastly, the matter of algorithmic mistakes (Amoore, 2020, 118; Pasquale, 2016, 40).”
Robust agents learn causal world models
Richens, J., & Everitt, T. (2024) · arXiv · doi:10.48550/arxiv.2402.10877 · Cited by 5 · see citing works
“It has been argued that a reliance on black-box models could greatly widen the gap between capabilities and understanding (Pasquale, 2015).”
BackgroundIorio, L. (2026) · Athens Journal of Law · doi:10.30958/ajl.12-2-3
الرحمن, ع. ا. ع., النقبي, م. ع., سيد, ك., & أبوالعزم (2025) · Revue Marocaine des Etudes Juridiques et Economiques · doi:10.65040/remeje.2025.012103
- Venue
- Choice Reviews Online
- Publisher
- American Library Association
- Published
- 2015-05-20
- Volume
- 52
- Issue
- 10
- Pages
- 52-5426-52-5426
- ISSN
- 0009-4978 (ISSN-L)
- 1523-8253
- OpenAlex
- W3046920401
- Cited by
- 533
- References
- 0
- Citations by year
- 2025: 73 · 2024: 66 · 2023: 76 · 2022: 78 · 2021: 65 · 2020: 43 · 2019: 70 · 2018: 34 · 2017: 13 · 2016: 11 · 2015: 3 · 2014: 1
- Type
- book review
- Language
- en
- Open access
- closed
- Locations
- Choice Reviews Online (publishedVersion)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Law › Digitalization, Law, and Regulation
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Keywords
- algorithmic control, money, information control, surveillance, algorithmic governance, social control
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