Mental Modeling Technology (MMT)

Effective risk communication requires contributions from subject matter experts, who know the issues; analysts, who can identify the essential ones; behavioral scientists, who can address audience members’ information needs; and specialists, who can create channels for trusted two-way communication between the parties. The mental models approach provides a framework for organizing the information needed to accomplish this task. However, it takes deep personal and organizational commitment to bring and keep the parties together. Mental Modeling shows how to make that happen, integrating theory and practice.
The range of its applications is remarkably broad, including plastic surgery, climate change, dairy farming, deep mining, biosolids, nuclear power, and carbon capture and sequestration. So is the range of stakeholders and audiences, including physicians, patients, regulators, laborers, engineers, land use planners, and river managers. And, so are the methods, including community workshops, in-depth interviews, expert elicitation sessions, computer models, worker training, and broad and narrowband communication. These ranges of topics, audiences, and method show the generality of the approach and the creativity of the authors in its use.
Readers of Mental Modeling will acquire an understanding of the theory underlying the approach, with its basic principles illustrated in diverse, practical examples. Readers will learn methods that they can apply directly and strategies for generating their own. And they will come away with an appreciation of the diligence needed to create communications worthy of the stakes riding on them. Although not easy, the work is exciting — and gratifying.

Baruch Fischhoff, PhD
Pittsburgh, PA

Cognitive Analysis Software Suite (CASS)

The Cognitive Analysis Software Suite (CASS) that is specifically designed to efficiently support the unique empirical methods embodied in the research component of MMT from developing graphical depictions of the systems being modeled, through coding, analysis of qualitative data, back to graphical depiction of research results. CASS was developed to enable researchers to hypothesize, visualize, tabulate, analyze, and report on individuals’ mental models of complex social and technical issues. It provides the analytical framework for conducting and analyzing mental models research.

Matthew D. Wood, Sarah Thorne, Daniel Kovacs, Gordon Butte, Igor Linkov
Mental Modeling Approach — Risk Management Application Case Studies, Springer