It’s been a while since the last post but I intend to add more content from now on. To start with; almost a year ago I held my inaugural lecture, the text of which can be found here (in Dutch).
The lecture deals with the promises and pitfalls of digitalisation in government. Digital technologies such as AI (artificial intelligence) seem attractive to achieve as much as possible in an increasingly complex society such as government. Better service, less fraud, more responsive policies, more effective and efficient business operations. There is a lot of optimism about the opportunities, based on the possibilities of technology and the idea that the challenges mentioned can be solved technically. Yet, there is also pessimism: digital technology is sometimes almost seen as the source of the loss of human scale and public values in general. There is a call for normative and ethical requirements, frameworks and guidelines.
In the lecture, I speak of the nuance that is needed in the conversation about the use of AI and other digital technology in the public sector. In my research, I seek to look at how policy and implementation at different layers deal with the tension between on the one hand the beckoning perspective of rapid innovation, sometimes driven by an almost mythical image of what data, ICT, and AI can do, and often driven from the need to make better use of data and systems. And on the other hand, the slowness of unyielding existing systems and practices. Realism is about how these two (can) work at the same time.The realism that is based on unprecedented numbers of systems and applications, based on data that has been collected and structured in a way that they sometimes hardly lend themselves to this.” According to Klievink, the role of data and digitization is the big blind spot when it comes to theory development in policy implementation.