There exists a variety of techniques to build a computational model in a participatory manner, including companion modeling (using agent-based models) and group model building (using system dynamics). Among them, Fuzzy Cognitive Maps (FCM) has been emphasized for problems with high uncertainty and vagueness and applied to critical settings (e.g. medical therapies) or settings where stakeholders’ perspectives can differ significantly (e.g. ecosystem management). While the typical process of participatory modeling involves inviting stakeholders and facilitating sessions, this is not always feasible as complex problems may require around the world (i.e. asynchronous model building) and skilled facilitators increase the costs of the model building. Consequently, software solutions have been developed such that FCMs can be constructed online (e.g. mentalmodeler.com). The next frontier to effectively use FCM in participatory modeling is to cope with a massive number of participants: that is, crowdsourcing a model. Latest technical advances are able to take in the causal structural of a model, automatically distribute it to crowds in order to compute relationship strengths, and assemble the results in a model. However, the power of the crowd is still under-utilized as participants are asked either all questions or a random subset, thus over-sampling when sufficient data has been gathered or wider confidence margins are acceptable, and under-sampling what may be critical parts of the model. We are thus developing efficient solutions to bring participatory modeling to the scale of a crowd, both through adaptive algorithms to acquire data, and through innovative solutions to aggregate it.
- Dr Andrew Tawfik, Northern Illinois University, USA
- Dr Steven Gray, Michigan State University, USA