T14P03 - The Data/Sensor Revolution and Public Policy

Topic : Science, Internet and Technology Policy

Panel Chair : Jouke de Vries - jouke.de.vries@rug.nl

Panel Second Chair : Gideon Shimshon - g.j.shimshon@fgga.leidenuniv.nl

Panel Third Chair : Sarah Giest - s.n.giest@fgga.leidenuniv.nl

Objectives and Scientific Relevance of the panel

One of the central assumptions in theories on decision- and policymaking has been that there is not
enough information to take the best possible decision. The psychologist and Nobel Prize winner
Herbert Simon stated that decision-making is never 100% rational, because rationality itself is limited.
Rationality is bounded due to the limited capacities of human intelligence, brain dysfunction, and all
kind of difficulties within the political and administrative system. The solutions within a complex political
and administrative system are thus suboptimal, which is why it is difficult to solve complicated societal
issues. This bounded rationality assumption became dominant in theories on decision- and
policymaking in political science and public administration. Decision- and policymaking was no longer
rational-synoptic, but was more incremental and political.

The assumption of bounded rationality has led to different theories on decision- and policymaking. The
rational-synoptic model was succeeded by the theory of incrementalism. According to this model, the
essence of decision-making was to take small steps. Of course empirical and theoretical work led to a
synthesis between the rational decision-making model and incrementalism: the model of mixed
scanning.

At the end of the twentieth century, new models on decision- and policymaking received more
attention. These new models were based on chaos and complexity theory from the natural sciences
and theoretical biology. Based on the assumption that planning of decision-making is difficult due to
relations no longer being linear, coincidence became a crucial element in explaining processes of
decision-making. Two models shaped this development. The first one is the work of John W. Kingdon
on political agendas. Kingdon makes a distinction between three streams: societal problems,
alternatives and politics. Only when these three streams overlap can there be fundamental decision
making. The second model is termed the punctuated equilibrium model. (Baumgartner & Jones)Most
of the time political and administrative systems are confronted with stability, yet sometimes the
decision-making process becomes more turbulent. This border between stability and turbulence is the
punctuated equilibrium.

The process of digitalization is changing the dynamics related to decision- and policymaking:
information is no longer scarce in society and in political and administrative systems. To the contrary,
data are everywhere now. Decision makers are no longer confronted with a lack of information, but
rather with an endless sea of information and data. This development will continue because of new
developments in the IT-sector: nanocomputers, the Internet of things and artificial intelligence. Many of
these developments are discussed with the term Big Data Revolution.

As a result, the notion of limited rationality is debatable nowadays. If this central assumption is no
longer correct because of the Big Data Revolution, this must have consequences for different theories
that have been dominant in political science and public administration for a long period. The central
question of our panel is: What are the consequences of the Data and Sensor Revolution for decisionand
policymaking, both theoretically and empirically?
This general question leads to different partial questions:
- What are the consequences of the Big Data Revolution for theories on decision- and
policymaking?
- Is it possible to incorporate the consequences of the Big Data Revolution into decision- and
policymaking models?
- What are the consequences of the Big Data Revolution in the daily practice of political and
administrative systems?

Call for papers

The Big Data Revolution challenges some of the assumptions made in the field of decision- and
policymaking connected to bounded rationality. Decision makers are no longer confronted with a lack
of information, but rather with an endless sea of information and data. Under these circumstances,
new questions arise that have consequences for different theories dominating political science and
public administration. This panel wishes to examine these challenges for decision-making processes
and political administrative systems. Our focus is on novel theoretical and empirical perspectives
moving the field towards identifying and incorporating the consequences of the Big Data Revolution in
these processes.

The panel calls for papers that address the dynamics of decision- and policymaking in the context of
the big data revolution. Submissions can cover a wide range of topics connected to decision-making
models, data-aided decision support, evidence-based policymaking or the digitization of
administrations. Addressing the leading question of what the consequences of big data will be for
decision- and policymaking, the papers can offer methodological developments based on big data,
case studies of data-driven decision-making as well as challenges of incorporating this type of
information into daily public practices. We welcome both theoretical and empirical papers. Of course
the combination of both theory and empirical research is also possible.

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