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

Models as ‘interested amateurs’

Community member post by Pete Barbrook-Johnson

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Pete Barbrook-Johnson (biography)

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

Dealing with deep uncertainty: Scenarios

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Laura Schmitt Olabisi (biography)

Community member post by Laura Schmitt Olabisi

What is deep uncertainty? And how can scenarios help deal with it?

Deep uncertainty refers to ‘unknown unknowns’, which simulation models are fundamentally unsuited to address. Any model is a representation of a system, based on what we know about that system. We can’t model something that nobody knows about—so the capabilities of any model (even a participatory model) are bounded by our collective knowledge.

One of the ways we handle unknown unknowns is by using scenarios. Scenarios are stories about the future, meant to guide our decision-making in the present. Continue reading

Uncertainty in participatory modeling – What can we learn from management research?

Community member post by Antonie Jetter

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Antonie Jetter (biography)

I frequently struggle to explain how participatory modeling deals with uncertainty. I found useful guidance in the management literature.

After all, participatory modeling projects and strategic business planning have one commonality – a group of stakeholders and decision-makers aims to understand and ultimately influence a complex system. They do so in the face of great uncertainty that frequently cannot be resolved – at least not within the required time frame. Businesses, for example, have precise data on customer behavior when their accountants report on annual sales. However, by this time, the very precise data is irrelevant because the opportunity to influence the system has passed.

Two key lessons from the management literature deal with the nature of uncertainty and responding to four major types of uncertainty. Continue reading

ICTAM: Bringing mental models to numerical models

Community member post by Sondoss Elsawah

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Sondoss Elsawah (biography)

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

Participatory processes and participatory modelling: The sustainable procedure framework

Community member post by Beatrice Hedelin

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Beatrice Hedelin (biography)

How can we resolve debates about participatory processes between proponents and skeptics? What role can participatory modelling play in improving participatory processes?

Proponents argue for the merits of participatory processes, which include learning; co-production of knowledge; development of shared understanding of a problem and shared goals; creation of trust; and local power and ownership of a problem.

Sceptics point to evidence of inefficient, time-consuming, participatory processes that escalate conflict and mistrust. They also highlight democratic problems; lack of transparency; and powerful actors that benefit in relation to weaker ones such as the unorganized, poor, and uneducated. Continue reading