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Prof. Dr. Ralf Klischewski has received the award for the best research paper at the 20th Annual International Conference on Digital Government Research

In GUC News
Monday, July 8, 2019

The conference was held in June at Dubai’s Mohammed Bin Rashid School of Government with the theme “Governance in the Age of Artificial Intelligence.“  The awarded research unfolds a perspective to understand the intertwinement of human action and technology performance while designing and shaping the upcoming digitalization of government operations. This perspective assumes an intended primacy of the people in the citizen-government relationship and perceives the marginalization of humans as a significant threat to applying social values in governance, especially when situated action is required. Based on identifying a variety of ‘monster’ challenges, the paper points to opportunities for decomposition of human and machine agency and advocates the alignment and composition of both agencies as a long-term learning process that involves both citizens and technology and requires safeguarding by multiple stakeholders.

 

TOPIC of PAPER:

Will the Government Machine Turn into a Monster?

Why and How We Should Compose Human and Machine Agency in Digital Government

 

PAPER ABSTRACT:

IT artifacts and systems increasingly act autonomously and interact non-deterministically, and we have not yet learned how to deal with this empowerment of machine agency in digital government. Following the socio-materiality discourse, this research unfolds a perspective from which digital government research can understand the intertwinement of human action and technology performance while designing and shaping the upcoming digitalization of government operations. This perspective assumes an intended primacy of the people in the citizen-government relationship and perceives the marginaliza­tion of humans as a significant threat to applying social values in governance, especially when situated action is required. Using Mintzberg’s models of managing government, we identify a variety of ‘monster’ challenges, point to opportunities for decomposi­tion of human and machine agency and advocate the alignment and composition of both agencies as a long-term learning process that involves both citizens and technology and requires safeguarding by multiple stakeholders