Citizens ‘on mute’ in digital public service delivery (Part 1)
This article is written by Sarah Giest, Assistant Professor at the Institute of Public Administration — Leiden University, based in the Faculty of Governance and Global Affairs. She researches public policy, big data, sustainability and innovation. Sarah is also a member of Young Academy Leiden, and of the Editorial Board of the Data & Policy Journal. It is followed by another contribution with a focus on the academic and societal challenge behind digital welfare systems.
Various countries are digitalizing their welfare system in the larger context of austerity considerations and fraud detection goals, but these changes are increasingly under scrutiny. In short, digitalization of the welfare system means that with the help of mathematical models, data and/or the combination of different administrative datasets, algorithms issue a decision on, for example, an application for social benefits (Dencik and Kaun 2020).
Several examples exist where such systems have led to unfair treatment of welfare recipients. In Europe, the Dutch SyRI system has been banned by court, due to human rights violations in the profiling of welfare recipients, and the UK has found errors in the automated processes leading to financial hardship among citizens. In the United States and Canada, automated systems led to false underpayment or denial of benefits. A recent UN report (2019) even warns that countries are ‘stumbling zombie-like into a digital welfare dystopia’. Further, studies raise alarm that this process of digitalization is done in a way that it not only creates excessive information asymmetry among government and citizens, but also disadvantages certain groups more than others.
A closer look at the Dutch Childcare Allowance case highlights this. In this example, low-income parents were regarded as fraudsters by the Tax Authorities if they had incorrectly filled out any documents. An automated and algorithm-based procedure then also singled out dual-nationality families. The victims lost their allowance without having been given any reasons. Even worse, benefits already received were reclaimed. This led to individual hardship, where financial troubles and the categorization as a fraudster by government led for citizens to a chain of events from unpaid healthcare insurance and the inability to visit a doctor to job loss, potential home loss and mental health concerns (Volkskrant 2020).
Given these country-specific examples, there is a general lack in current discussions about the lived experience of citizens while dealing with a digital welfare system. This disregard of citizens’ experience of such Kafkaesque circumstances in a digital system can lead to a decline of citizen trust in government (Wichowsky and Moynihan 2008; Grimmelikhuijsen 2012), negatively affect political participation (Vigoda-Gadot 2007; Eubanks 2011; Kim and Lee 2012) and cause opacity for both citizens and bureaucrats (Peeters and Widlak 2018).
In this context, there are increasing calls that in this digitalization process of public services, user voices are needed to shape accessible systems. Democracy relies on some ability to scrutinize and challenge decisions being made. As data utilization and algorithmic processes are becoming an integral part of categorizing, profiling and scoring individuals and households in order to allocate public services, voice in the process is increasingly an issue (Dencik and Kaun 2020; Ananny 2016; Sandvig et al. 2016).
End of Part 1. Part 2 is available here.
References
Ananny, M. 2016. Toward an Ethics of Algorithms: Convening, Observation, Probability, and Timeliness. Science, Technology, & Human Values 41 (1), 93–117.
Dencik, L. and A. Kaun. 2020. Datafication and the Welfare State. Communication and Media 1(1), 1–8.
Eubanks, V. 2011. Digital Dead End, Fighting for Social Justice in the Information Age. Cambridge, US: MIT Press.
Grimmelikhuijsen, S. G. 2012. Transparency and trust. An experimental study of online disclosure and trust in government (Master’s thesis). Utrecht University, The Netherlands.
Kim, S. and J. Lee. 2012. E‐Participation, Transparency, and Trust in Local Government. Public Administration Review 72(6), 819–828.
Peeters, R. and A. Widlak. 2018. The digital cage: Administrative exclusion through information architecture–The case of the Dutch civil registry’s master data management system. Government Information Quarterly 35(2), 175–83.
Sandvig, C., Hamilton, K., Karahalios, K. and C. Langbort. 2016. When the Algorithm Itself Is a Racist: Diagnosing Ethical Harm in the Basic Components of Software. International Journal of Communication 10, 4972–4990.
United Nations (UN). 2019. Report of the Special Rapporteur on extreme poverty and human rights. General Assembly, October 11, 2019. Available at: undocs.org/A/74/493.
Vigoda-Gadot, E. 2007. Citizens’ Perceptions of Politics and Ethics in Public Administration: A Five-Year National Study of Their Relationship to Satisfaction with Services, Trust in Governance, and Voice Orientations. Journal of Public Administration Research and Theory 17(2), 285–305.
Volkskrant. 2020. Gedupeerde ouder ‘Esther’ weet nog wél heel goed te reconstrueren wat er fout ging in de toeslagenaffaire. Volkskrant, December 3, 2020. Available at: https://www.volkskrant.nl/columns-opinie/gedupeerde-ouder-esther-weet-nog-wel-heel-goed-te-reconstrueren-wat-er-fout-ging-in-de-toeslagenaffaire~bc5239a7.
Wichowsky, A. and D. Moynihan. 2008. Measuring how administration shapes citizenship: A policy feedback perspective on performance management. Public Administration Review 68, 908–920.
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