2015
DOI: 10.1002/cplx.21680
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Models and people: An alternative view of the emergent properties of computational models

Abstract: Computer models can help humans gain insight into the functioning of complex systems. Used for training, they can also help gain insight into the cognitive processes humans use to understand these systems. By influencing humans understanding (and consequent actions) computer models can thus generate an impact on both these actors and the very systems they are designed to simulate. When these systems also include humans, a number of self-referential relations thus emerge which can lead to very complex dynamics.… Show more

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Cited by 5 publications
(8 citation statements)
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“…With such integration across different dimensions (Hamilton et al , 2015), there is the possibility to better understand uncertainty, and to improve model predictions, particularly in the estimate of human exposures to environmental hazards, which is a fundamental step in human health risk assessment and health impact assessment. Particularly exciting will be the development of systems that so tightly couple real-time sensor data with models, that they produce information that actively engages with the public and informs stakeholders (Voinov et al ., 2010; Boschetti, 2015) towards improving public health in a seamless and transparent manner – true ubiquitous sensing and computing. Here, recent developments for instance in the development of Geospatial Information Infrastructures (Diaz et al , 2013) provide useful examples and can inform progress towards integrated environmental modelling (Laniak et al , 2013).…”
Section: Discussionmentioning
confidence: 99%
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“…With such integration across different dimensions (Hamilton et al , 2015), there is the possibility to better understand uncertainty, and to improve model predictions, particularly in the estimate of human exposures to environmental hazards, which is a fundamental step in human health risk assessment and health impact assessment. Particularly exciting will be the development of systems that so tightly couple real-time sensor data with models, that they produce information that actively engages with the public and informs stakeholders (Voinov et al ., 2010; Boschetti, 2015) towards improving public health in a seamless and transparent manner – true ubiquitous sensing and computing. Here, recent developments for instance in the development of Geospatial Information Infrastructures (Diaz et al , 2013) provide useful examples and can inform progress towards integrated environmental modelling (Laniak et al , 2013).…”
Section: Discussionmentioning
confidence: 99%
“…This is essential, as transparency and traceability of data flows and processing methods are key requirements to assess the quality of data. Such science-policy interfaces need to reflect stakeholders’ conceptual and mental models (alternatives, preferences, utility, and drivers) embedded in decision science frameworks, integrating those (mainly) qualitative models with (quantitative) biophysical models and decisions (see Wood et al , 2012; Boschetti, 2015 and section 7).…”
Section: Figmentioning
confidence: 99%
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“…Modellers are deeply aware of uncertainty in input data and model parameterisation (dark tall bar on the left). Because of their professional expertise and possible professional bias, they believe that ecological computer models are reasonable representations of real ecological processes, as shown by the terminology they use to describe them ("micro-cosmos", "virtual ecosystem", "virtual laboratory") [18]. As a result, ecological computer models (dark short uncertainty bar in the middle) are believed to constrain the uncertainty arising from input data, by enforcing ecological and physical consistency on the model results.…”
Section: An Issue Of Communication About Models?mentioning
confidence: 99%
“…As result, in communication about model projects, modellers may focus on the ecological computer model while decision makers may expect the focus to be on input data. ("micro-cosmos", "virtual ecosystem", "virtual laboratory") [18]. As a result, ecological computer models (dark short uncertainty bar in the middle) are believed to constrain the uncertainty arising from input data, by enforcing ecological and physical consistency on the model results.…”
Section: An Issue Of Communication About Models?mentioning
confidence: 99%