Abstract
Many of humanity’s most pressing and challenging problems – such as environmental degradation, physical and economic security, and public health – are inherently complex (involve many different interacting components) as well as widely impactful (effect many diverse stakeholders). Solving such problems requires crowd-scale deliberation in order to cover all the types of disciplinary expertise needed, as well as to take into account the many impacts the decision will have. Current approaches to group decision-making, however, fail at scale, producing outcomes that are needlessly suboptimal for all the parties involved. This chapter will investigate why group decision-making fails in this way, explaining the problems of achieving Pareto optimality and noting the tendency to miss win-win solutions that are not the “dream choices” of any participant. It will go on to describe how recent advances in social computing technology can address these failings, for example, through the use of deliberation maps, idea filtering, and crowd-scale complex negotiation.
Notes
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i.e., the summed utility of the stakeholders involved.
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Acknowledgments
This work has been supported by the JST CREST program in Japan, the FP7 program in the European Union, the National Science Foundation in the United States, and the Templeton Foundation.
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Klein, M. (2020). Crowd-Scale Deliberation for Group Decision-Making. In: Kilgour, D.M., Eden, C. (eds) Handbook of Group Decision and Negotiation. Springer, Cham. https://doi.org/10.1007/978-3-030-12051-1_40-1
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