LAY THEORIES, MENTAL MODELS AND FUTURISTS

As Jason pointed out in his latest blog posts (e.g. An Archetype for Future(s) Clients?), a great deal might be learned of how clients perceive Future Studies and the Futurist Profession. Analysing the differences in understanding of laypeople and futurists might be helpful as well. Differences between laypeople and expert opinions and perceptions regarding complex domains like climate change, the labor market, growth, and redistribution policies and risk are well documented (see e.g. Bostrom et al., 1994; Enste, Haferkamp and Fetchenhauer, 2009; Slovic, 1987). Interdisciplinary research tries to explain these differences by how expert and laypeople form their own theories.

Lay Theories and Experts

Laypeople are willing to make judgments about causation concepts they do not understand, even though they admitted to lack the necessary knowledge (Leiser and Aroch, 2009). They develop simplified lay theories of the world that serve as an orientation for their actions and allow them to understand everyday live and complex interrelationships. Research indicates that laypeople form their understandings based on everyday experience, media coverage, and social interaction and that they judge by fairness, ideas of value or morality. Their causation is often limited in such a way that they cluster variables into groups, within which increases in “ingroup” variables go hand in hand with increases in other “ingroup” variables and decreases in “outgroup” variables – the good-begets-good heuristic (Leiser and Aroch, 2009). Generally speaking, laypeople are rather occupied with answers to the questions of why something is happening to them and/or their social group and why now (Popay, n.d.). Experts, on the other hand, have access to specialist knowledge, can spend more time in their field and tend to be less prone to cognitive biases (or prone to different ones) and judge based on efficiency goals and scientific models. Experts are concerned with the question of causality and explanations for phenomena and problems.

However, both groups develop so called mental models – simplified representations of their understanding of how the world, or certain aspects thereof, function (See Norman (1983) for a comprehensive definition). Or as Norman (1983: p 7) puts it “Mental models are naturally evolving models. That is, through interaction with a target system, people formulate mental models of that system. These models need not be technically accurate (and usually are not), but they must be functional.” Research already tries to elicit expert’s and laypeople’s mental models to improve policy making, team work and product design as well as communication, especially in the domain of risks. Furthermore mental models are part of Causal Layered Analysis and System Dynamics.

What Do Lay Theories and Mental Models Got to Do with Future Studies?

Treating the futurist as an expert and his client or the public as the layperson, there might be implications for Future Studies. Before I conclude with implications, I would like to point out a procedure proposed by a paper of the OECD (2004; based on the work of Bostrom et al. (1992)) revealing differences in mental models between two groups that I slightly adapted to fit to a Future Studies context.

Implications for Future Studies

Firstly, elicitation of mental models could help to better understand clients and improve communication.

Identifying gaps and similarities in the mental models of the futurist in charge and his client can ensure clearer communication and also increase efficiency of the futurist’s work.

As stated in the beginning, laypeople tend to ask “why me” and “why now” questions, while experts are concerned with causation and explanations. So involving laypeople and incorporating and understanding laypeople’s perceptions can enrich future work to another level.

Secondly, research insights into mental models and lay theories might serve as a selling point for Future Studies.

“Future-History-Gap”: A paper of Sevón (1984) finds that subject’s (Caution: Only 3 subjects: banker, manager and politician) mental models of factors such as future unemployment or inflation are less sophisticated and consist of less impact and effect chains than mental models of historic unemployment or inflation.

On a side note, Sevón also finds that the participant’s overall understanding of future inflation is represented mostly by elements that lower future inflation; thus, lower future inflation is subliminally anticipated – think about self-fulfilling prophecies.

Another selling point might be derived from work of Chermack (2003) and Glick et al. (2012). They argue that scenario planning can be used as a tool to improve and reconcile mental models.

Thirdly, take forward the discussion within the futurist community about a common ground regarding definitions in the field of Future Studies and the professionalization of Future Studies.

Fourthly,identify a possible gap between the perception of the futurist profession in the public/ media and the self-perception of futurists. As in risk communication, differences in understanding of laypeople and futurists might be used to clarify the profession of futurists.

The important point to recognize is that, regardless of whether or not something can be proven scientifically – “If a person believes that the lines in his palm foretell his future, this belief must be taken account in explaining certain of his expectations and actions” (Heider, 1958: 5). And challenging and refuting mental models can be a difficult task. There are theories like the Theory of Cognitive Dissonance which assumes that people have an urge to create a consistency with their beliefs when their preferred self-picture and/or the picture of the world is challenged (Festinger, 1962). This is achieved by altering beliefs or pursing actions in favor of their preferred (inadequate or incorrect) beliefs. Thus, especially for controversial topics like health care policies, questions of ethics or climate change, people might be not willing to accept scientifically validated knowledge (there are cases of benzene workers stating that the chemicals they are working with are not hazardous; as cited in Akerlof and Dickens, 1982).

References

• Akerlof, G. A., & Dickens, W. T. (1982). The economic consequences of cognitive dissonance. The American Economic Review, 307-319.

  
  

• Bostrom, A., Morgan, M. G., Fischhoff, B., & Read, D. (1994). What do people know about global climate change? 1. Mental models. Risk Analysis, 14(6), 959-970.

  
  

• Bostrom, A., Fischhoff, B., & Morgan, M. G. (1992). Characterizing mental models of hazardous processes: A methodology and an application to radon. Journal of Social Issues, 48(4), 85-100.

  
  

• Chermack, Thomas J. (2003). The role of scenarios in altering mental models and building organizational knowledge. Futures Research Quarterly, Spring, 25-41.

  
  

• Enste, D. H., Haferkamp, A., & Fetchenhauer, D. (2009). Unterschiede im Denken zwischen Ökonomen und Laien–Erklärungsansätze zur Verbesserung der wirtschaftspolitischen Beratung. Perspektiven der Wirtschaftspolitik, 10(1), 60-78.

• Festinger, L. (1962). A theory of cognitive dissonance (Vol. 2). Stanford university press

  
  

• Glick, M. B., Chermack, T. J., Luckel, H., & Gauck, B. Q. (2012). Effects of scenario planning on participant mental models. European Journal of Training and Development, 36(5), 488-507.

  
  

• Heider, F. (1958). The psychology of interpersonal relations.

  
  

• Leiser, D., & Aroch, R. (2009). Lay Understanding of Macroeconomic Causation: The Good Begets Good Heuristic. Applied Psychology, 58(3), 370-384.

  
  

• Norman, D. A. (1983). Some observations on mental models. Mental models, 1.

  
  

• Popay, J. (n.d.). The contribution of lay knowledge to reducing health inequalities. Retrieved from: http://www.gcph.co.uk/assets/0000/0354/Jennie_Popay_Slideshow.pdf

  
  

• OECD (2004). The Mental Models Approach to Risk Research – an RWM Perspective. Secretariat Paper.

  
  

• Sevón, G. (1984). Cognitive maps of past and future economic events. Acta Psychologica, 56(1), 71-79.

  
  

• Slovic, P. (1987). Perception of risk. Science, 236(4799), 280-285.