Chapter 22: Further Reading — Whistleblowing and Ethical Dissent in AI Organizations

Organized by topic. Annotations describe each source's key contribution and appropriate audience.

The Foundational Cases

1. Bender, E. M., Gebru, T., McMillan-Major, A., and Shmitchell, S. "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?" Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2021, pp. 610–623. The paper at the center of the Timnit Gebru firing. Essential reading not merely for its content — which remains one of the most important analyses of the risks of large language model development — but for understanding what kind of research can provoke organizational retaliation. The paper's arguments about environmental cost, bias encoding, and power concentration have become central themes in AI ethics discourse.

2. Haugen, F. Senate Commerce Subcommittee Testimony. US Senate, October 5, 2021. Available publicly through the Senate Commerce Committee's website. Haugen's prepared testimony and the Q&A session provide the most accessible account of the Facebook whistleblower case and the specific concerns about algorithmic amplification of harm that motivated her disclosure. Essential reading for understanding what an effective whistleblower disclosure looks like in practice.

3. Hao, K. "We Read the Paper That Forced Timnit Gebru Out of Google. Here's What It Says." MIT Technology Review, December 4, 2020. Clear explanation of the Stochastic Parrots paper's arguments for a non-specialist audience. Useful for readers who want to understand the paper's actual content before analyzing the organizational events that surrounded it.

Psychological and Organizational Foundations

4. Bandura, A. "Moral Disengagement in the Perpetration of Inhumanities." Personality and Social Psychology Review, vol. 3, no. 3, 1999, pp. 193–209. The foundational academic presentation of Bandura's moral disengagement theory. More technical than a business audience typically requires, but the original source for a concept central to understanding organizational ethics failures. Recommended for practitioners who want depth in the psychological mechanisms discussed in Section 22.2.

5. Edmondson, A. C. The Fearless Organization: Creating Psychological Safety in the Workplace for Learning, Innovation, and Growth. Wiley, 2018. The definitive accessible treatment of psychological safety, drawing on two decades of research by Harvard Business School's Amy Edmondson. Essential reading for anyone designing organizational cultures that welcome dissent. Clear, practical, and evidence-based. Recommended for managers, HR professionals, and organizational leaders.

6. Morrison, E. W. "Employee Voice and Silence." Annual Review of Organizational Psychology and Organizational Behavior, vol. 1, 2014, pp. 173–197. Comprehensive review of the research literature on why employees stay silent about problems they observe. Covers the individual, interpersonal, and organizational factors that produce organizational silence. Important for understanding the full spectrum of barriers to ethical dissent beyond the most obvious career risk.

7. Near, J. P., and Miceli, M. P. "Organizational Dissidence: The Case of Whistle-Blowing." Journal of Business Ethics, vol. 4, no. 1, 1985, pp. 1–16. One of the foundational academic articles on whistleblowing in organizational contexts. Establishes conceptual distinctions that remain in use in the literature — between internal and external whistleblowing, between observers and participants, between allegations of illegal activity and ethical concerns. Useful background for practitioners seeking grounding in the research tradition.

8. Moberly, R. E. "Unfulfilled Expectations: An Empirical Analysis of Why Sarbanes-Oxley Whistleblowers Rarely Win." William & Mary Law Review, vol. 49, 2007, pp. 65–155. Empirical analysis of why Sarbanes-Oxley whistleblower cases so rarely succeed for claimants, documenting the legal and procedural barriers that make existing whistleblower protections less effective than they appear on paper. Essential for practitioners advising employees on the realistic prospects of legal protection in whistleblower situations.

9. Dworkin, T. M. "SOX and Whistleblowing." Michigan Law Review, vol. 105, 2007, pp. 1757–1780. Analysis of the Sarbanes-Oxley whistleblower provisions and their limitations. Provides essential context for understanding what existing federal protections cover and why they are inadequate for AI ethics concerns specifically.

10. European Commission. Report on the Application of the Whistleblower Protection Directive. European Commission, 2023. Assessment of implementation of the EU Whistleblower Protection Directive across member states. Important for understanding how the EU framework has been implemented in practice and what variation exists across member states. Directly relevant for organizations operating in the EU and for comparative analysis of US and EU whistleblower protection approaches.

11. Government Accountability Project. Whistleblower Protection Manual: A Practical Guide for Federal Employees. GAP, 2022. While focused on federal employees, this manual from one of the most experienced whistleblower advocacy organizations in the US provides the most practical guide to navigating whistleblower legal frameworks. Useful as a reference for practitioners advising employees on their options and protections.

Industry-Specific Analysis

12. Whittaker, M. "The Steep Cost of Capture." Proceedings of the ACM on Human-Computer Interaction, vol. 5, no. CSCW2, 2021. Analysis of the structural dynamics that lead to the co-optation of AI ethics functions within large technology companies. Argues that the organizational placement and incentive structure of internal AI ethics functions systematically limits their independence and effectiveness. Essential reading for understanding why internal AI ethics functions at large technology companies face structural constraints on their effectiveness.

13. Birhane, A., Kalluri, P., Card, D., Bender, E. M., Agley, B., and Larson, B. "The Values Encoded in Machine Learning Research." Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2022. Systematic analysis of what values are implicit in mainstream machine learning research, identifying patterns in what is measured, what is optimized, and whose interests are centered. Important context for understanding why internal AI ethics dissent can be structurally difficult in environments where the research culture does not foreground social impact.

14. Crawford, K. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press, 2021. The most comprehensive critical examination of AI's organizational and social context available for a general audience. Chapter on AI companies' internal culture and governance is directly relevant to the dynamics discussed in this chapter. Essential reading for students seeking deep context for the organizational patterns examined in Chapters 21 and 22.

Responsible Disclosure and Journalist Relationships

15. Greenwald, G. No Place to Hide: Edward Snowden, the NSA, and the US Surveillance State. Metropolitan Books, 2014. First-person account of working with a major national security whistleblower, written by the journalist who broke the Snowden story. While the national security context differs significantly from AI ethics, the account of how the journalist-source relationship worked in a high-stakes disclosure is instructive. Recommended for understanding the practical mechanics of significant whistleblowing.

16. Mitchell, A., and Brady, J. "The Insider's Guide to Working with Whistleblowers." Columbia Journalism Review, 2022. Practical guidance from journalists on how they work with whistleblower sources — what they need, what they can and cannot promise, how sources can protect themselves. Directly applicable to AI ethics employees considering external disclosure. Recommended before any contact with journalists about organizational concerns.

Future Directions

17. Pasquale, F. The Black Box Society: The Secret Algorithms That Control Money and Information. Harvard University Press, 2015. Analysis of the opacity of algorithmic systems and the governance challenges that opacity creates. Important context for understanding why external accountability mechanisms — including whistleblowing — are essential when algorithmic systems are not transparent to users, regulators, or the public.

18. Raji, I. D., Kumar, I. E., Horowitz, A., and Selbst, A. "The Fallacy of AI Functionality." Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2022. Analysis of the gap between how AI systems are represented and how they actually function, with implications for the governance mechanisms needed to close that gap. Relevant to understanding why internal employee knowledge of AI system behavior is irreplaceable as a governance input.

19. Wachter-Boettcher, S. Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech. W.W. Norton, 2017. Accessible account of the organizational and cultural dynamics that produce biased and harmful technology, with extensive analysis of the internal culture of technology organizations. Useful for non-technical audiences seeking to understand why the organizational barriers to ethical dissent discussed in this chapter are so persistent.

20. Brayne, S. Predict and Surveil: Data, Discretion, and the Future of Policing. Oxford University Press, 2020. Study of AI systems deployed in policing, based on fieldwork inside the Los Angeles Police Department. While primarily sociological, the account of how AI systems are adopted, used, and contested within law enforcement organizations provides important context for understanding the organizational dynamics of AI deployment in high-stakes contexts. Recommended for practitioners working in or with public sector AI applications.