The challenges and limits of big data algorithms in technocratic governance
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The risk-based approach is an effective solution to AI-specific risks such as data or algorithmic errors, data or algorithmic bias, or even data-embedded discrimination.
“and an effective solution to AI-specific risks such as data or algorithmic errors, data or algorithmic bias, or even data-embedded discrimination (Janssen & Kuk, 2016).”
From Data governance: Organizing data for trustworthy Artificial Intelligence (2020) · cites this paper as Janssen & Kuk, 2016
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“This approach is often advocated as a foundation for data governance (Rothstein, Borraz, & Huber, 2013) and an effective solution to AI-specific risks such as data or algorithmic errors, data or algorithmic bias, or even data-embedded discrimination (Janssen & Kuk, 2016).”
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“Algorithms can systematically introduce inadvertent bias, reinforce historical discrimination, favour a political orientation or reinforce undesired practices (Janssen & Kuk, 2016).”
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“To that end, using automated algorithms to support human decision-making is suggested to significantly reduce fraud and errors in service processing (Janssen and Kuk, 2016).”
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“Techno-driven approach does not take 'context' into consideration, rather expects technologies to fix all the glitches in cities (Janssen and Kuk, 2016) .”
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“Algorithms can introduce inadvertent bias, reinforce historical discrimination, favor a particular political orientation, or reinforce undesired practices (Janssen & Kuk, 2016b).”
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Artificial Intelligence and Public Values: Value Impacts and Governance in the Public Sector
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Transparency and accountability in digital public services: Learning from the Brazilian cases
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“…scholars argue that such inherent challenges of the algorithms can be mitigated through unraveling the imperceptibility, materiality, and governmentality of Li et al. how algorithms work (Janssen and Kuk, 2016b), and thus the algorithmic governance or AI governance becomes more and more important.”
Factors influencing the use of artificial intelligence in government: Evidence from China
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“There are, for example, taxonomies that classify socio-technical systems according to their degree of automation and complexity (Janssen and Kuk 2016).”
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“This is particularly important as algorithms are modified and become more complex over time, concentrating power in the hands of people who understand how they work (Janssen & Kuk, 2016).”
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“Data analytics is expected to provide valuable insights (Desouza and Jacob, 2017; Fosso Wamba et al., 2015; Janssen and Kuk, 2016; Kyriazis etal.,2020;Palma-RuizandG (cid:1) omez-Martínez,2019).”
BackgroundKim, E. S. (2020) · Technology in Society · doi:10.1016/j.techsoc.2020.101378 · Cited by 53 · see citing works
Wang, X., Wu, Y. C., Ji, X., & Fu, H. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1320277 · Cited by 81 · see citing works
“It highlights the need for algorithmic designers to abide by current laws that provide equal protection against discrimination to citizens and consumers (Janssen and Kuk, 2016).”
BackgroundRyan, M., Antoniou, J., Brooks, L., Jiya, T., Macnish, K., & Stahl, B. C. (2021) · Science and Engineering Ethics · doi:10.1007/s11948-021-00293-x · Cited by 59 · see citing works
Wang, G., Xie, S., & Li, X. (2022) · Public Management Review · doi:10.1080/14719037.2022.2070243 · Cited by 53 · see citing works
“…to public administration through the replacement of the human workforce, the limited role of ethics and professional competence, the reinforcement of biases in policymaking, and the lack of supervision and accessibility (e.g. Barth and Arnold 1999; Boyd and Wilson 2017; Janssen and Kuk 2016).”
BackgroundThe effects of different personal data categories on information privacy concern and disclosure
Chua, H. N., Ooi, J. S., & Herbland, A. (2021) · Computers & Security · doi:10.1016/j.cose.2021.102453 · Cited by 55 · see citing works
“Given that each piece of data leaves behind electronic trails of customer activities, individuals are concerned about how companies collect and use their private information (Janssen & Kuk, 2016; Morey et al., 2015).”
Accuracy and Fairness for Juvenile Justice Risk Assessments
Berk, R. (2019) · Journal of Empirical Legal Studies · doi:10.1111/jels.12206 · Cited by 50 · see citing works
A Framework and Databases for Measuring Entrepreneurial Ecosystems
Johnson, E., Hemmatian, I., Lanahan, L., & Joshi, A. M. (2021) · Research Policy · doi:10.1016/j.respol.2021.104398 · Cited by 49 · see citing works
Seven HCI Grand Challenges Revisited: Five-Year Progress
Stephanidis, C., Salvendy, G., Antona, M., Duffy, V. G., Gao, Q., Karwowski, W., Konomi, S., Nah, F. F., Ntoa, S., Rau, P. P., et al. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2450411 · Cited by 54 · see citing works
“…algorithms often suffer from the very same biases and errors of human decision-makers, or even amplify existing social prej-udices, as shown in a number of real-world cases (Janssen & Kuk, 2016; Kordzadeh & Ghasemaghaei, 2022; Kovacova et al., 2019; Panch et al., 2019; Raghavan et al., 2020).”
Scherr, S., Haim, M., & Arendt, F. (2018) · New Media & Society · doi:10.1177/1461444818801010 · Cited by 48 · see citing works
Algorithmic transparency and bureaucratic discretion: The case of SALER early warning system
Criado, J. I., Valero, J., & Villodre, J. (2020) · Information Polity · doi:10.3233/ip-200260 · Cited by 47 · see citing works
Public AI canvas for AI-enabled public value: A design science approach
Fatima, S., Desouza, K. C., Buck, C., & Fielt, E. (2022) · Government Information Quarterly · doi:10.1016/j.giq.2022.101722 · Cited by 47 · see citing works
Data in Policing: An Integrative Review
Afzal, M., & Panagiotopoulos, P. (2024) · International Journal of Public Administration · doi:10.1080/01900692.2024.2360586 · Cited by 51 · see citing works
“Subsequently, the unstructured, complex, dynamic, and heterogeneous nature of large data sets led to the development of data analytics (Janssen & Kuk, 2016; Mergel et al., 2016; Ruijer et al., 2023).”
Platform-based innovation ecosystems: Entering new markets through holographic strategies
Barile, S., Simone, C., Iandolo, F., & Laudando, A. (2022) · Industrial Marketing Management · doi:10.1016/j.indmarman.2022.07.003 · Cited by 41 · see citing works
Citizen conceptions of democracy and support for artificial intelligence in government and politics
König, P. D. (2022) · European Journal of Political Research · doi:10.1111/1475-6765.12570 · Cited by 46 · see citing works
“Strikingly, the evidence hardly supports the idea that a technocratic notion of democracy is associated with greater AI support – even though theoretical contributions have pointed to a clear affinity between technocracy and a social ordering via AI (e.g., Janssen & Kuk, 2016; Sætra, 2020).”
Canadian smart cities: Are we wiring new citizen‐local government interactions?
Johnson, P. A., Acedo, A., & Robinson, P. J. (2020) · Canadian Geographies / Géographies canadiennes · doi:10.1111/cag.12623 · Cited by 44 · see citing works
Replicating Smart Cities: The City-to-City Learning Programme in the Replicate EC-H2020-SCC Project
Calzada, I. (2020) · Smart Cities · doi:10.2139/ssrn.3689054 · Cited by 40 · see citing works
Public Values in the Age of Big Data: A Public Information Perspective
Ingrams, A. R. (2018) · Policy & Internet · doi:10.1002/poi3.193 · Cited by 41 · see citing works
Whether AI adoption challenges matter for public managers? The case of Polish cities
Sienkiewicz-Małyjurek, K. (2023) · Government Information Quarterly · doi:10.1016/j.giq.2023.101828 · Cited by 46 · see citing works
Mining service quality feedback from social media: A computational analytics method
Lee, H. J., Lee, M., Lee, H., & Cruz, R. A. (2021) · Government Information Quarterly · doi:10.1016/j.giq.2021.101571 · Cited by 38 · see citing works
Kempeneer, S. (2021) · Government Information Quarterly · doi:10.1016/j.giq.2021.101578 · Cited by 44 · see citing works
de Sousa, W. G., Fidelis, R. A., Bermejo, P. H. D. S., Gonçalo, A. G. D. S., & Melo, B. D. S. (2021) · Government Information Quarterly · doi:10.1016/j.giq.2021.101660 · Cited by 38 · see citing works
Transparency in policy making: A complexity view
Brunswicker, S., Priego, L. P., & Almirall, E. (2019) · Government Information Quarterly · doi:10.1016/j.giq.2019.05.005 · Cited by 41 · see citing works
Forecasting and explaining emergency department visits in a public hospital
Petsis, S., Karamanou, A., Kalampokis, E., & Tarabanis, K. A. (2022) · Journal of Intelligent Information Systems · doi:10.1007/s10844-022-00716-6 · Cited by 35 · see citing works
“…need to be addressed including ethical challenges, such as the lack of trust in AI-based decisions (Sun & Medaglia, 2019) and bias of algorithms in policy making (Janssen & Kuk, 2016), organizational and managerial challenges, such as resistance to data sharing (World Bank, 2020), and others.”
BackgroundGenerating Value from Government Data Using AI: An Exploratory Study
Gao, Y., & Janssen, M. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-57599-1_24 · Cited by 34 · see citing works
“With the use of AI algorithm, the data collection and processing become less visible [34].”
MethodSelf-citationPolicy capacity and rise of data‐based policy innovation labs
Kim, S., WELLSTEAD, A. M., & Heikkila, T. (2022) · Review of Policy Research · doi:10.1111/ropr.12494 · Cited by 32 · see citing works
Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector
Fischer-Abaigar, U., Kern, C. A., Barda, N., & Kreuter, F. (2024) · Government Information Quarterly · doi:10.1016/j.giq.2024.101976 · Cited by 49 · see citing works
The use of public sector data analytics in the Netherlands
van Veenstra, A. F., Grommé, F., & Djafari, S. (2020) · Transforming Government People Process and Policy · doi:10.1108/tg-09-2019-0095 · Cited by 32 · see citing works
Inteligencia Artificial (y Administración Pública)
Criado, J. I. (2021) · EUNOMÍA. Revista en Cultura de la Legalidad · doi:10.20318/eunomia.2021.6097 · Cited by 38 · see citing works
“…de una característica esencial para entender su potencial: los algoritmos coevolucionan con datos, sistemas y humanos dentro de complejos sistemas sociotécnicos «algorithms dynamically co-evolve with data, systems, and humans within a complex socio-technical system» (Janssen & Kuk, 2016, p. 372).”
BackgroundInfluentialFilgueiras, F. D. B. (2021) · AI & Society · doi:10.1007/s00146-021-01201-4 · Cited by 35 · see citing works
The problem with trust: on the discursive commodification of trust in AI
Krüger, S., & Wilson, C. (2022) · AI & Society · doi:10.1007/s00146-022-01401-6 · Cited by 30 · see citing works
“…2018), processes and policy frameworks that protect citizens in the slightest case of doubt (Balaram et al. 2018; Brundage et al. 2020; Dignum 2019; Janssen and Kuk 2016; Kemper and Kolkman 2019; Kolkman 2020; Lee 2018; Mulgan 2016; Reisman et al. 2018; Vassilakopoulou 2020), or public-sector…”
Background
- Authors
- Janssen, M., & Kuk, G.
- Affiliations
- Delft University of Technology (NL)
- Nottingham Trent University (GB)
- Corresponding author
- Janssen, Marijn
- Venue
- Government Information Quarterly
- Publisher
- Elsevier BV
- Published
- 2016-07
- Volume
- 33
- Issue
- 3
- Pages
- 371-377
- ISSN
- 0740-624X (ISSN-L)
- OpenAlex
- W2527349292
- Cited by
- 363
- References
- 32
- Citations by year
- 2026: 64 · 2025: 42 · 2024: 43 · 2023: 31 · 2022: 48 · 2021: 47 · 2020: 39 · 2019: 27 · 2018: 16 · 2017: 5 · 2016: 1
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Government Information Quarterly (publishedVersion)
- Nottingham Trent University's Institutional Repository (Nottingham Trent Repository) (submittedVersion)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Political Science and International Relations › E-Government and Public Services
- Physical Sciences › Engineering › Media Technology › Smart Cities and Technologies
- Keywords
- big data algorithms, technocratic governance, algorithmic bias, algorithmic accountability, governmentality, algorithmic transparency, data curation, algorithmic discrimination, institutional logics, algorithmic governance
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