The Knowledge Barrier
Bibliography
All sources cited in The Knowledge Barrier.
Back to The Knowledge Barrier- Ahn & Chen (2022)
- Ahn, M. J., & Chen, Y.-C. (2022). Digital transformation toward AI-augmented public administration. Government Information Quarterly, 39(2), Article 101664.
- Aldag, Warner, & Bel (2020)
- Aldag, A. M., Warner, M. E., & Bel, G. (2020). It depends on what you share: The elusive cost savings from service sharing. Journal of Public Administration Research and Theory, 30(2), 275–289.
- Alon-Barkat & Busuioc (2023)
- Alon-Barkat, S., & Busuioc, M. (2023). Human-AI interactions in public sector decision making: “Automation bias” and “selective adherence” to algorithmic advice. Journal of Public Administration Research and Theory, 33(1), 153–169.
- Angwin et al. (2016)
- Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016, May 23). Machine bias: There’s software used across the country to predict future criminals. And it’s biased against Blacks. ProPublica.
- Becker et al. (2025)
- Becker, J., Rush, N., Barnes, E., & Rein, D. (2025). Measuring the impact of early-2025 AI on experienced open-source developer productivity. METR. arXiv:2507.09089.
- Bel & Sebo (2021)
- Bel, G., & Sebo, M. (2021). Does inter-municipal cooperation really reduce delivery costs? Urban Affairs Review, 57(1), 153–188.
- Bergen & Labonte (2020)
- Bergen, N., & Labonte, R. (2020). Detecting and limiting social desirability bias in qualitative research. Qualitative Health Research, 30(5), 783–792.
- Brayne (2020)
- Brayne, S. (2020). Predict and surveil: Data, discretion, and the future of policing. Oxford University Press.
- Brynjolfsson, Li, & Raymond (2023)
- Brynjolfsson, E., Li, D., & Raymond, L. (2023). Generative AI at work. NBER Working Paper No. 31161. Published in Quarterly Journal of Economics.
- Buolamwini & Gebru (2018)
- Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. Proceedings of Machine Learning Research, 81, 1–15.
- Burns & Yeaton (2008)
- Burns, T. J., & Yeaton, K. G. (2008). Success factors for implementing shared services in government. IBM Center for the Business of Government.
- Caldera (2024)
- Caldera, C. (2024, March 29). NYC’s AI chatbot is telling businesses to break the law. The Markup.
- Chaurasia et al. (2025)
- Chaurasia, S., Datar, A., Singh, P., Eggers, W. D., & Kishnani, P. (2025). Scaling gen AI in governments. Deloitte Insights, Deloitte Center for Government Insights.
- CivicPulse (2024)
- CivicPulse. (2024). The digital divide between small towns and big cities. CivicPulse Research.
- City of San José (2023–2024)
- City of San José. (2023–2024). GovAI Coalition: Resources, templates, & AI FactSheet. City of San José Information Technology Department.
- Commonwealth of Pennsylvania (2024)
- Commonwealth of Pennsylvania. (2024). ChatGPT Enterprise Pilot Program results. Office of Administration.
- Cummings (2025)
- Cummings, R. (2025). Algorithms as public service. ICMA Public Management.
- Davis (1989)
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
- Dell’Acqua et al. (2023)
- Dell’Acqua, F., McFowland, E., Mollick, E. R., et al. (2023). Navigating the jagged technological frontier. Harvard Business School Working Paper No. 24-013.
- E&I Cooperative Services (2023)
- E&I Cooperative Services. (2023). The true costs of an RFP. National procurement cost survey.
- Epstein (2022)
- Epstein, B. (2022). Two decades of e-government diffusion among local governments in the United States. Government Information Quarterly, 39(1), Article 101665.
- Eubanks (2018)
- Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin’s Press.
- Feiock (2013)
- Feiock, R. C. (2013). The institutional collective action framework. Policy Studies Journal, 41(3), 397–425.
- Hatz et al. (2025)
- Hatz, S., Dreksler, N., Wei, K., & Zhang, B. (2025). Local US officials’ views on the impacts and governance of AI. PLOS ONE, 20(10), e0332919.
- Hill (2020)
- Hill, K. (2020, June 24). Wrongfully accused by an algorithm. The New York Times.
- Ho et al. (2022)
- Ho, S., Burke, G., Arasu, S., & Linderman, J. (2022, April 29). An algorithm that screens for child neglect raises concerns. Associated Press.
- ICMA (2024)
- ICMA. (2024). Artificial intelligence in local government: Summary of 2024 survey results. ICMA Survey Research.
- Kwon, Feiock, & Bae (2014)
- Kwon, S.-W., Feiock, R. C., & Bae, J. (2014). The roles of regional organizations for interlocal resource exchange. American Review of Public Administration, 44(3), 339–357.
- Lecher (2018)
- Lecher, C. (2018, March 21). What happens when an algorithm cuts your health care. The Verge.
- Lum, Koper, & Willis (2017)
- Lum, C., Koper, C. S., & Willis, J. (2017). Understanding the limits of technology’s impact on police effectiveness. Police Quarterly, 20(2), 135–163.
- Lum & Isaac (2016)
- Lum, K., & Isaac, W. (2016). To predict and serve? Significance, 13(5), 14–19.
- Madan & Ashok (2023)
- Madan, R., & Ashok, M. (2023). AI adoption and diffusion in public administration. Government Information Quarterly, 40(1), Article 101774.
- March (1991)
- March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87.
- Mikalef et al. (2022)
- Mikalef, P., Lemmer, K., Schaefer, C., et al. (2022). Enabling AI capabilities in government agencies. Government Information Quarterly, 39(4), Article 101596.
- MissionSquare (2024)
- MissionSquare Research Institute. (2024). State and local workforce: 2024 survey findings. Washington, DC.
- MissionSquare (2025)
- MissionSquare Research Institute. (2025). Artificial intelligence in the workforce: What do state and local government employees think? Washington, DC.
- Moon (2002)
- Moon, M. J. (2002). The evolution of e-government among municipalities: Rhetoric or reality? Public Administration Review, 62(4), 424–433.
- NACo (2024)
- National Association of Counties. (2024). AI County Compass. NACo AI Exploratory Committee.
- Nedovic-Budic & Godschalk (1996)
- Nedovic-Budic, Z., & Godschalk, D. R. (1996). Human factors in adoption of geographic information systems. Public Administration Review, 56(6), 554–567.
- Neumann, Guirguis, & Steiner (2024)
- Neumann, O., Guirguis, K., & Steiner, R. (2024). Exploring artificial intelligence adoption in public organizations. Public Management Review, 26(1), 114–141.
- New America (2024)
- New America, Open Technology Institute. (2024). Sustaining AI in local government.
- Norris & Reddick (2013)
- Norris, D. F., & Reddick, C. G. (2013). Local e-government in the United States: Transformation or incremental change? Public Administration Review, 73(1), 165–175.
- Noy & Zhang (2023)
- Noy, S., & Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science, 381, 187–192.
- OECD (2019)
- OECD. (2019). Recommendation of the Council on Artificial Intelligence. OECD/LEGAL/0449.
- O’Reilly & Tushman (2013)
- O’Reilly, C. A., III, & Tushman, M. L. (2013). Organizational ambidexterity. Academy of Management Perspectives, 27(4), 324–338.
- Pew Charitable Trusts (2025)
- Pew Charitable Trusts. (2025). Slowdown in private sector jobs a boon for state and local hiring. March 10, 2025.
- Pfeffer & Sutton (2000)
- Pfeffer, J., & Sutton, R. I. (2000). The knowing-doing gap. Harvard Business School Press.
- Prinvil, Stern, & Ramos (2025)
- Prinvil, C., Stern, A., & Ramos, K. (2025). A new approach to helping local governments navigate generative AI. Urban Institute.
- Puente (2019)
- Puente, M. (2019, April 24). LAPD to end use of controversial program that aimed to predict where crimes would occur. Los Angeles Times.
- Rogers (2003)
- Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press. (Original work published 1962.)
- Saxenian (1994)
- Saxenian, A. (1994). Regional advantage: Culture and competition in Silicon Valley and Route 128. Harvard University Press.
- Shorey (2025)
- Shorey, S. (2025). AI and government workers: Use cases in public administration. Roosevelt Institute.
- Tony Blair Institute (2024)
- Tony Blair Institute for Global Change. (2024). Future-ready councils: How AI could transform local government.
- U.S. Congress (2004)
- U.S. Congress. (2004). ENHANCE 911 Act of 2004 (P.L. 108-494).
- U.S. GAO (2004)
- U.S. Government Accountability Office. (2004). Uneven implementation of wireless Enhanced 911 (Report GAO-04-55).
- Williams et al. (2021)
- Williams, M. C., Jr., et al. (2021). Body-worn cameras in policing: Benefits and costs. NBER Working Paper No. 28622.
- Yigitcanlar et al. (2025)
- Yigitcanlar, T., Desouza, K. C., Butler, L., & Roozkhosh, F. (2025). Public perceptions of responsible AI in local government: Cross-national study across Australia, Spain, and the United States.
Legal Cases Cited
- Jacobs v. Gillespie (2018)
- No. 4:16-cv-00396 (E.D. Ark. 2018). Arkansas Medicaid algorithm case.
- K.W. v. Armstrong (2016)
- No. 1:12-cv-00022 (D. Idaho 2016). Idaho Medicaid budget tool case.
- Loomis v. Wisconsin (2016)
- 881 N.W.2d 749 (Wis. 2016), cert. denied, 137 S. Ct. 2290 (2017). COMPAS algorithm sentencing case.
© 2026 Alton Henley. The Knowledge Barrier.
altonhenley.com · LinkedIn