Community member post by Richard Taylor and John Forrester
Policy problems are complex and – while sometimes simple solutions can work – complexity tools and complexity thinking have a major part to play in planning effective policy responses. What is ‘complexity’ and what does ‘complexity science’ do? How can agent-based modelling help address the complexity of environment and development policy issues?
At the most obvious level, one can take complexity to mean all systems that are not simple, by which we mean that they can be influenced but not controlled. Complexity can be examined through complexity science and complex system models. Continue reading →
How can we improve the often poor interaction and lack of genuine discussions between policy makers, experts, and those affected by policy?
As a social scientist who makes and uses models, an idea from Daniel Dennett’s (2013) book ‘Intuition Pumps and Other Tools for Thinking’ struck a chord with me. Dennett introduces the idea of using lay audiences to aid and improve understanding between experts. Dennett suggests that including lay audiences (which he calls ‘curious nonexperts’) in discussions can entice experts to err on the side of over-explaining their thoughts and positions. When experts are talking only to other experts, Dennett suggests they under-explain, not wanting to insult others or look stupid by going over basic assumptions. This means they can fail to identify areas of disagreement, or to reach consensus, understanding, or conclusions that may be constructive.
For Dennett, the ‘curious nonexperts’ are undergraduate philosophy students, to be included in debates between professors. For me, the book sparked the idea that models could be ‘curious nonexperts’ in policy debates and processes. I prefer and use the term ‘interested amateurs’ over ‘curious nonexperts’, simply because the word ‘amateur’ seems slightly more insulting towards models! Continue reading →
Do we need a protocol for documenting how research tackling complex social and environmental problems was undertaken?
Usually when I read descriptions of research addressing a problem such as poverty reduction or obesity prevention or mitigation of the environmental impact of a particular development, I find myself frustrated by the lack of information about what was actually done. Some processes may be dealt with in detail, but others are glossed over or ignored completely.
For example, often such research brings together insights from a range of disciplines, but details may be scant on why and how those disciplines were selected, whether and how they interacted and how their contributions to understanding the problem were combined. I am often left wondering about whose job it was to do the synthesis and how they did it: did they use specific methods and were these up to the task? And I am curious about how the researchers assessed their efforts at the end of the project: did they miss a key discipline? would a different perspective from one of the disciplines included have been more useful? did they know what to do with all the information generated? Continue reading →
How can we capture the highly qualitative, subjective and rich nature of people’s thinking – their mental models – and translate it into formal quantitative data to be used in numerical models?
This cannot be addressed by a single method or software tool. We need multi-method approaches that have the capacity to take us through the learning journey of eliciting and representing people’s mental models, analysing them, and generating algorithms that can be incorporated into numerical models.
More importantly, this methodology should allow us to see in a transparent way the progression on this learning journey. Continue reading →
As a modeller, I often get requests from research or policy colleagues along the lines of ‘we want a model of the health system’. It’s relatively easy to recognise that ‘health system’ is too vague and needs explicit discussion about the specific issue to be modelled. It is much less obvious that the term ‘model’ also needs to be refined. In practice, different modelling methods are more or less appropriate for different questions. So how is the modelling method chosen? Continue reading →
La modélisation participative cherche à impliquer un groupe de personnes dans la conception et la révision d’un modèle. L’objectif à terme consiste à mieux caractériser les problèmes actuels et imaginer collectivement comment tenter de les résoudre. Dans le domaine de l’environnement en particulier, il apparaît nécessaire que les acteurs concernés se sentent impliqués dans la démarche de modélisation, afin qu’ils puissent exprimer leurs propres points de vue, mais aussi pour mieux s’engager dans des décisions collectives. De ce fait, pour aborder la gestion intégrée des ressources, il est nécessaire de mettre les acteurs au centre des préoccupations de recherche, à la fois lors de la phase la conception du modèle mais aussi pour l’exploration de ces scénarios. Continue reading →