This contribution discusses the development of the Data Ethics Decision Aid (DEDA), a framework for reviewing government data projects that considers their social impact, the embedded values and the government’s responsibilities in times of data-driven public management. Drawing from distinct qualitative research approaches, the DEDA framework was developed in an iterative process (2016–2018) and has since then been applied by various Dutch municipalities, the Association of Dutch Municipalities, and the Ministry of General Affairs (NL). We present the DEDA framework as an effective process to moderate case-deliberation and advance the development of responsible data practices. In addition, by thoroughly documenting the deliberation process, the DEDA framework establishes accountability. First, this paper sheds light on the necessity for data ethical case deliberation. Second, it describes the prototypes, the final design of the framework, and its evaluation. After a comparison with other frameworks, and a discussion of the findings, the paper concludes by arguing that the DEDA framework is a useful process for ethical evaluation of data projects for public management and an effective tool for creating awareness of ethical issues in data practices.

Research on algorithms and artificial intelligence in the hiring process tends to focus on applicant screening and is often centered on the employer perspective. The role played by intermediaries, such as employment Web sites in the distribution of information about employment opportunities, tends to be overlooked. This paper examines the role of search algorithms on employment Web sites and their retrieval of employment opportunities for job seekers based on gendered search terms. Through a basic algorithm audit of the search engines used by three major employment Web sites active in the Dutch job market, we explore whether their search algorithms neutralize or reinforce gendered language, in case of the latter thereby naturalizing stigmas and pre-existing bias. According to our findings, employment Web sites can cause allocative harm if they repeatedly fail to show all opportunities relevant to job seekers.

This article has been peer reviewed through the double-blind process of Open Library of Humanities, which is a journal published by the Open Library of Humanities.

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Humanities scholarship is essential in the present-day datafied society. This contribution discusses the interdisciplinary research platform Utrecht Data School (UDS) and its entrepreneurial research approach for investigating the impact of datafication and algorithmization on culture and society. This research approach is informed by close cooperation with external partners, including (local) government organizations, (public) media, companies, and NGOs and accelerates areas in which traditional academic research in the humanities have often said to fall short: societal engagement, knowledge transfer, and the application of research findings. However, as reflected on in the conclusion, it is not without its challenges.