Complexity and Agent-based Modelling

Community member post by Richard Taylor and John Forrester

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Richard Taylor (biography)

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?

Complexity

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

Argument-based tools to account for uncertainty in policy analysis and decision support

Community member post by Sven Ove Hansson and Gertrude Hirsch Hadorn

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Sven Ove Hansson (biography)

Scientific uncertainty creates problems in many fields of public policy. Often, it is not possible to satisfy the high demands on the information input for standard methods of policy analysis such as risk analysis or cost-benefit analysis. For instance, this seems to be the case for long-term projections of regional trends in extreme weather and their impacts.

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Gertrude Hirsch Hadorn (biography)

However, we cannot wait until science knows the probabilities and expected values for each of the policy options. Decision-makers often have good reason to act although such information is missing. Uncertainty does not diminish the need for policy advice to help them determine which option it would be best to go for.

When traditional methods are insufficient or inapplicable, argument-based tools for decision analysis can be applied. Such tools have been developed in philosophy and argumentation theory. They provide decision support on a systematic methodological basis. Continue reading

Overturning the design of outcome measures

Community member post by Diana Rose

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Diana Rose (biography)

Outcome measures in research about treatment and service provision may not seem a particularly controversial or even exciting domain for citizen involvement. Although the research landscape is changing – partly as a result of engaging stakeholders in knowledge production and its effects – the design of outcome measures has been largely immune to these developments.

The standard way of constructing such measures – for evaluating treatment outcomes and services – has serious flaws and requires an alternative that grounds them firmly in the experiences and situations of the people whose views are being solicited. Continue reading

Critical Back-Casting

Community member post by Gerald Midgley

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Gerald Midgley (biography)

How can we design new services or strategies when the participation of marginalized stakeholders is vital to ethicality? How can we liberate people’s creativity so we can move from incremental improvements to more fundamental change?

To answer these questions, I have brought together insights from Russ Ackoff and Werner Ulrich to develop a new method that I call Critical Back-Casting.

Russ Ackoff, writing in the 1980s, is critical of organizations that focus on incremental improvements without ever asking whether they are doing the right thing in the first place. Thus, they are at risk of continually ‘improving’ the wrong thing, when they would be better off going for a more radical redesign. Ackoff makes two far-reaching prescriptions to tackle this problem. Continue reading

Citizen science and participatory modeling

Community member post by Rebecca Jordan and Steven Gray

Rebecca Jordan (biography)

As investigators who engage the public in both modeling and research endeavors we address two major questions: Does citizen science have a place within the participatory modeling research community? And does participatory modeling have a place in the citizen science research community?

Let us start with definitions. Citizen science has been defined in many ways, but we will keep the definition simple. Citizen science refers to endeavors where persons who do not consider themselves scientific experts work with those who do consider themselves experts (around a specific issue) to address an authentic research question. Continue reading

Getting to a shared definition of a “good” solution in collaborative problem-solving

Community member post by Doug Easterling

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Doug Easterling (biography)

How can collaborative groups move past their divisions and find solutions that advance their shared notions of what would be good for the community?

Complex problems – such as how to expand access to high-quality health care, how to reduce poverty, how to remedy racial disparities in educational attainment and economic opportunity, and how to promote economic development while at the same time protecting natural resources – can’t be solved with technical remedies or within a narrow mindset. They require the sort of multi-disciplinary, nuanced analysis that can only be achieved by engaging a variety of stakeholders in a co-creative process.

Bringing together stakeholders with diverse perspectives allows for a comprehensive analysis of complex problems, but this also raises the risk of a divisive process. Continue reading