Dutch mayors are expected to act both as moral person and as moral managers. However, the extent to which council members express such requirements when selecting candidates remains underexplored. To identify possible changes in these expectations following the implementation of a 2016 integrity law, which made the mayor responsible for ‘advancing the administrative integrity of the municipality’, the current article quantitatively analyses 349 vacancy texts for Dutch mayoralty for the time period 2008-2019. Unexpectedly, the authors find that moral person requirements still feature prominently in job advertisements, but that attention is declining. In addition, they find a significant shift from moral-person requirements to moral-management requirements, which indicates that vacancy texts mirror the increasing importance of moral leadership requirements for Dutch mayors. Further, whereas the complex integrity concept requires tailoring to the unique circumstances in municipalities, the authors find that councilors make little effort to provide their own definition of integrity in vacancy texts, which leaves ample room for local customization.

Predictive tools as instruments for understanding and responding to risky behaviour as early as possible are increasingly becoming a normal feature in local and state agencies. A risk that arises from the implementation of these predictive tools is the problem of dirty data. The input of incorrect or illegally obtained information (‘dirty data’) can influence the quality of the predictions used by local and state agencies, such as the police. The article focuses on the risks of dirty data in predictive policing by the Dutch Police. It describes the possibilities to prevent dirty data from being used in predictive policing tools, such as the Criminality Anticipation System (CAS). It concludes by emphasizing the importance of transparency for any serious solution looking to eliminate the use of dirty data in predictive policing.

Technological advancements in the field of data analytics, algorithms and AI have dramatically increased opportunities for workplace monitoring. In this article, we discuss some of these digital technologies, and examine their impact on employment relationships and the quality of work. Based on desk research, literature review and interviews, the Rathenau Institute examined a wide range of digital instruments, their scientific basis, implications for the quality of work and relevant legal frameworks. Digital monitoring technologies often quantify work activities. We argue that it is important for organisations to realise that such quantification often negatively impacts both job quality and employment relationships. Responsible use of digital monitoring tools not only requires a broad societal and political dialogue about privacy, discrimination and workload but also a critical reflection on the aim of organisations to use data to understand workers, while not everything of value can be captured in data.