Abstract
Based on a series of four case studies, we present a process model for asynchronous stakeholder consultations with visualized problem structuring in the form of argument mapping. The consultations deal with matters of policy advice in the field of science, technology and society, with a focus on bioethics and business ethics. We start with a short description of the technique of argument mapping, followed by a detailed explanation of how argument mapping supports the consultation process. The consultation process is divided into the phases (1) research, (2) stakeholder interviews, (3) the conduct of an opinion poll concerning the arguments discussed, and (4) a final report. For the opinion poll, we used a newly invented tool that we call Argument Browser. Challenges that we encountered in the process mainly concerned issues of motivating participants, the structuring of complex topics, and the achievement of impartiality in deliberation. These challenges were addressed by the use of Participation Design (as a general framework of thinking about improvements within the consultation process), the employment of argumentation schemes, and other means. Lessons learned particularly concern the use-value of visualization and how argument mapping can support conflict analysis during the consultation process.
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Notes
- 1.
What exactly proponents and opponents in a debate have to present evidence for depends upon how burden of proof is distributed. In some situations, opponents just have to show that the proponent’s claims are false in order to win the argument. In risk assessment, for example, the proponent often has to prove for sure that risks can be excluded – regardless whether or not there are signs which positively indicate the existence of risks in the particular case. See Walton (2010) for a more systematic treatment of how burden of proof is distributed in different dialogue situations.
- 2.
The distinction between formal and informal argument mapping is not exhaustive. There are also approaches for argument mapping which rely on a formal semantic and allow nevertheless for ‘informal’ arguments which appeal to probability (instead to logical necessity). Carneades is an example of a computational model based on such an approach (see Gordon 2007).
- 3.
It is mostly our experiences with using argument maps a part of the participative online-reports which leads us to this conclusion. Although maps had several thousand clicks, just very few readers explicitly referred to them in their comments in the online-forum.
- 4.
Evidence for this was the high quality of comments and the seemingly thoughtful evaluations of arguments we received through the survey.
- 5.
See also Betz (2012) for how logical reconstruction can detect inconsistencies in an argument. Betz’ example is the analysis of an argument in favor of climate-engineering-R&D.
- 6.
There also was another interpretative issue in this case: In the very long run, workers in Bangladesh will gain more than western consumers, even in absolute terms! It all depends on the length of the time period under consideration. There also is an upward trend: As time goes by, the position of the textile workers relative to those of western consumers gets better, not worse. This also might add to the conclusion that economic growth does reduce unfairness, all things considered.
- 7.
This conflict is known as the Collingridge-Dilemma: Societal effects of a new technology are difficult to assess. But once the technology is implemented and the effects become clear, it is too late to do anything about them.
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Acknowledgements
Funding by the Robert Bosch Foundation (for the consultations on Ethics of Sweatshop Labour and NIPD) and by the Barmer GEK (for the consultation on NIPD) is gratefully acknowledged. The author also wishes to thank Thomas F. Gordon for constructive comments and many helpful discussions.
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Groetker, R. (2014). Visualized Problem Structuring for Stakeholder Consultations. In: Okada, A., Buckingham Shum, S., Sherborne, T. (eds) Knowledge Cartography. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-1-4471-6470-8_14
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