...We analyze aspects of government automation that complicate equity and inclusion as well as propose mitigating mechanisms that can improve digital government equity and inclusion. We identify findings from the broader literature and the articles included in this special issue.

In an introductory article, Susan Miller, Marc Schuilenburg, and I explore the concept of ‘digital government inclusion’: sciencedirect.com/science/arti....

Inclusion interrupted: Lessons from the making of a digital assistant by and for people with disability by Georgia van Toorn: sciencedirect.com/science/arti...

Exploring the potential and limits of digital tools for inclusive regulatory engagement with citizens by Chris Townley and Christel Koop: sciencedirect.com/science/arti...

Open data work for empowered deliberative democracy: Findings from a living lab study by Erna Ruijer, Carmen Dymanus, Erik-Jan van Kesteren, Laura Boeschoten, and Albert Meijer: sciencedirect.com/science/arti...

Promoting digital equality in co-production: The role of platform design by Pascale-Catherine Kirklies, Oliver Neumann, and Lisa Hohensinn: sciencedirect.com/science/arti...

Papers included in the special issue are:
Paradoxical digital inclusion: The mixed blessing of street-level intermediaries in reducing administrative burden by Mohammad Alshallaqi and Yaser Hasan Al-Mamary: sciencedirect.com/science/arti...

Seeking to move beyond entrenched debates, this special issue aims to shed light on the question: what technological, social, or organizational conditions can make digital government more inclusive?

As artificial intelligence and machine learning algorithms are rapidly being included in the work of government, concerns are raised about the exclusionary mechanisms of digital government tools and about the discriminatory effects of algorithm-assisted decision-making.

Information infrastructures are highly cost efficient and able to reduce administrative burdens in most cases for citizens. However, they also complicate procedural lawfulness and organizational and democratic control. Mitigation mechanisms should be designed into infrastructures.

3) While data-exchange will reduce administrative burdens for most citizens, they are negatively affected when trying to seek redress, exceptions, or correction of errors in data used for administrative decisions regarding their formal rights and obligations.

2) As data source and data user organizations establish a division of labor, the former are blindsided from the way data is used, and the latter are blindsided from the way data is collected and altered. This affects organizations’ ability to provide reasoning for their decision-making.

1) Data becomes decontextualized as organizations using data are no longer the ones collecting the data they use for their decision-making. Thereby, shared data supersedes observations of social reality at the operational level as well as the needs of specific legal contexts.

This has profound implications for the nature of data, for organizational accountability, and for citizens affected by decisions made with such data. We hypothesize that...

The whole of bureaucracy that is connected through data-exchange implies the organizational separation of the collection or gathering of government data from the exchange, modification, combination and/or analysis and subsequently its (re)use in decision-making processes.

Whether in automated administrative decision-making or algorithmic analyses, applications of data-driven government rest on a foundation of data. Increasingly, and especially in Western Europe, relevant data is exchanged among gov. organizations in information infrastructures.