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The Knowledge Barrier – Bibliography

The Knowledge Barrier

Bibliography

All sources cited in The Knowledge Barrier.

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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.
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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.
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March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87.
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Mikalef, P., Lemmer, K., Schaefer, C., et al. (2022). Enabling AI capabilities in government agencies. Government Information Quarterly, 39(4), Article 101596.
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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.
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Moon, M. J. (2002). The evolution of e-government among municipalities: Rhetoric or reality? Public Administration Review, 62(4), 424–433.
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National Association of Counties. (2024). AI County Compass. NACo AI Exploratory Committee.
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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.
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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.
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Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press. (Original work published 1962.)
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Saxenian, A. (1994). Regional advantage: Culture and competition in Silicon Valley and Route 128. Harvard University Press.
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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.
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U.S. Congress. (2004). ENHANCE 911 Act of 2004 (P.L. 108-494).
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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.

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