Bram Kievink
Bram Klievink, professor of Public Administration & Digitalisation Leiden University

CLOSER CITIES aims to create a bridge between urban science and urban practice. By collecting cases on urban practice, analysing them on the shoulders of urban science and sharing research outcomes, urban knowledge becomes shareable. In the ‘5 questions’ series, we ask scientists to briefly reflect on their research and the shareability of their insights and projects.

1. What is the main focus of your research (topic, theme, region)?

I study the interface between digitalisation and public governance. I am interested in both sides of this relationship: on the one hand how digital innovations challenge the incumbent practices and institutions of public governance, and on the other how these innovations might be used to support good and effective governance.

2. Can you give a brief description of your research?

The research I and some of my teammembers do, broadly concerns the use and challenges of ICT in government. For instance, we empirically study the role of algorithms in governance, notably in public policy making and decision making. Furthermore, we study how digital platforms support actors in taking up new roles, and how this challenges existing institutions of public governance.

3. How much influence does ‘local context’ have in your field of work? Can results or solutions from your research be shared with other regions easily?

The current debate on algorithmic governance is fairly ‘techno-optimist’ despite that adoption is sometimes slow and uneven across institutional and policy contexts. Context matters and we aim to improve the understanding of how the tenets of big data and algorithms juxtapose with the messy nature of public governance and policy processes. I think that such a perspective is very relevant across contexts, as is the consistent finding that context matters.

4. What are the main lessons learned that can be used by urban initiatives?

To select one: Although big data and algorithms hold great promises, but be aware of the hype-trap. Context-specificity applies to many advantages and disadvantages. Algorithms and the trade-offs made in selecting or applying them are often politically significant. In context, generating value from these innovations is not so much a question of technology but rather a question of alignment, conversation about trade-offs, and mutual understanding between the technical/analytical and political/administrative.

5. How do you think cities can implement these lessons?

Have realistic expectations of what novel technologies may offer by improving alignment between the various professionals that are involved in their use. And accept that adoption and value creation will remain uneven as some application areas or data sources may offer greater potential than others.