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Since 2004
DIMACS and LAMSADE have been running a joint research program on Computer
Science and Decision Theory (see DIMACS/LAMSADE
partnership). Already in October 2004, 2006 and 2008 we
organized a joint workshop (see page). We are
now planning a more focused workshop on Evidence Based Policy Making part of
their joint project on Algorithmic Decision Theory (see more at the COST Action IC0602 and the DIMACS Special Focus
on the same subject. In recent
years there has been a lot of discussion about "evidence based policy
making", an approach through which policy makers should conceive
policies (better policies) based on "evidence". However, despite
the literature circulating on this subject, it is not crystal clear (at least
for people working in the area of decision analysis, where supporting policy
making is current practice) what this term evokes and how it can influence both theory and practice
within decision sciences and technologies. What is
evidence? Is it something we just have to find around us or does it have to be constructed combining information and values?
Can policy making be conceived just as the result of better using information
and knowledge and how values have to be taken into account? How easy is it to
extract information out of the huge amounts of data today available and how
easy is to transform that into evidence? How do we "measure"
complex natural or social phenomena such as climate change or poverty? What
happens in case such "evidence" needs to be used within some
participative decision process where multiple perceptions, stakes and values
need to be taken into account at the same time? Questions such as the above
arise in multiple policy making situations such as conceiving adaptation and
mitigation policies for climate change, policies for reducing dramatic social
phenomena such as poverty, social exclusion and deviating behaviour
of social groups, implementing strategies for land use and regional planning,
managing natural resources under a sustainable development perspective. The
workshop aims at putting together decision and computer scientists working on
the above issues under different perspectives including among others: - how to model and construct evidence? - how to handle extremely large amounts of information and
how to extract meaningful information? - how to combine information, knowledge and values? - how to measure complex phenomena? - how to
develop algorithmic support for evidence-based decision making The
workshop aims at establishing a reference on how decision and computer scientists
should approach evidence-based policy making both in theory and in practice
and looks at: -
surveying the state of the art; -
identifying key application areas and relevant case studies; -
identifying research opportunities at a national and international level; - setting
a future research agenda. The
possibility of publishing a special issue of a major scientific journal is
being considered.
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