Talk at the Stockholm workshop on "Analyzing the dynamics of social-ecological systems: Towards a typology of social-ecological interactions", SES-LINK project meeting - Stockholm, June 5-6, 2014.
Indigenous knowledge and cognitive justice: Towards a co-production of knowle...Carina van Rooyen
Presentation to SOTL@UJ on 11 September 2014. This was the third leg of the presentation; the other two was by Thea de Wet and Gert van der Westhuizen.
Dualism, socially just pedagogies and shame in South African higher educationVivienne Bozalek
This presentation looks at how the mechanisms of dualism which support othering inferiorisation and interiorisation can be addressed through socially just pedagogies and how the politics of shame can be productive
Presented at the 2010 Leadership Wisconsin Alumni Summit. An introduction to social media tools, and a deeper discussion of the ramifications of social media.
Indigenous knowledge and cognitive justice: Towards a co-production of knowle...Carina van Rooyen
Presentation to SOTL@UJ on 11 September 2014. This was the third leg of the presentation; the other two was by Thea de Wet and Gert van der Westhuizen.
Dualism, socially just pedagogies and shame in South African higher educationVivienne Bozalek
This presentation looks at how the mechanisms of dualism which support othering inferiorisation and interiorisation can be addressed through socially just pedagogies and how the politics of shame can be productive
Presented at the 2010 Leadership Wisconsin Alumni Summit. An introduction to social media tools, and a deeper discussion of the ramifications of social media.
Results of field testing the indicators for resilience of socio-ecological pr...Bioversity International
Presentation by Nadia Bergamini from Bioversity International.
This was presented during a seminar hosted at Bioversity International on 'The Indicators of Resilience in Socio-Ecological Production Landscapes and Seascapes (SEPLS)' in January 2014.
Find out more: http://www.bioversityinternational.org/research-portfolio/agricultural-ecosystems/landscapes/
Socio-ecological systems: Moving beyond the Human Exemptionalist ParadigmMadhusudan Katti
A talk given by Dr. Andrew Jones on Sep 24, 2010, in the Biology Colloquium at California State University, Fresno. He presents a historical overview of how Sociology came to discover its place within a broader ecological context and began addressing the metabolic rift resulting from human activities on this planet. He also presents the conecptual framework for analysis being developed under the new Urban Long-Term Research Area - Fresno And Clovis Ecosocial Study (ULTRA-FACES) project.
A talk given to the "Social.Path" workshop at the University of Surrey, June 2014.
It is well established that many human abilities are context-dependent, including: language, preference judgement, memory, reasoning, learning and perception. This is usually taken as a negative – that there will be limits on our understanding and modelling of these abilities. However, what is not always appreciated is that context-dependency can be a powerful tool in social coordination and communication. This paper pulls together several theories about the cognition of context, and presents a computational model of context-dependency. It then sketches its role in social communication, coordination and embedding. It looks at some of the approaches to dealing with context in the computer science and social science literature and concludes that none of these squarely faces the problem of context dependency. This points towards a substantial gap in the research and hence a future programme.
Towards Institutional System Farming
A talk at the Lorentz Workshop on "Emerging Institutions: Design or Evolution?" September 2016, Leiden, NL (https://www.lorentzcenter.nl/lc/web/2016/836/info.php3?wsid=836&venue=Oort)
Using Agent-Based Simulation to integrate micro/qualitative evidence, macro-q...Bruce Edmonds
Networks are an abstraction of complex social processes. Albeit themselves formal, the social processes on which they are based can be researched using both quantitative and qualitative methods. The problem in combining these approaches comes from the very different natures and levels on which they are based. Here we describe an approach which uses agent-based modelling (ABM) as a stepping stone towards the more abstract network models. These ABMs are more in the nature of complex and dynamic descriptions than general theories, and are ideally suited for integrating a variety of kinds of evidence into a coherent fashion - including quatitative evidence to inform the micro-level behaviours of agents, and quantitative evidence about the macro, aggregate levels. The assumptions behind these kinds of ABM are relatively transparent, and the ABMs used to generate networks in a precise manner. Thus this "staging" of the abstraction process allows a well-founded mixed-methods approach to social network research. A worked example of this on voting behaviour is presented.
Possibilistic prediction and risk analyses
A talk given at the EA annual Conference, Bonn, May 2015
Abstract:
It is in the nature of complex systems that predictions that give a probability are not possible.
Indeed I argue that giving "the most likely" or "rough" prediction is more harmful than useful.
Rather an approach which maps out some of the possible outcomes is outlined.
Agent-based modelling is ideal for producing these - including, crucially, possibilities that could not have been conceived just by thinking about it (due to the fact that events can combine in ways that are more complex than the human brain can cope with directly).
A characterisation of the real future possibilities and their nature allows some positive responses to events:
* putting in place 'early warning indicators' for the emergence of identified possibilities
* contingency planning for when they are indicated.
Such an approach would allow policy makers to better 'drive' their decision making, without abnegating responsibility to experts.
How can we rely upon Social Network Measures? Agent-base modelling as the nex...Bruce Edmonds
All social network analysis of observed systems rely on assumptions, for example: how a link is defined is the right one, how the resulting network is analysed actually corresponds with our conclusions about it, etc. In other words the representation+analysis is a *model* of what we observe. Any model is fallible and thus needs independent validation, but this is rarely done in social network analysis due to the cost. Indeed, the only check is often that of face validity by the same person who collected the data and analysed it!
This lack of established validity is somewhat hidden by the divide within the field of social networks between the "formalists" who prove abstract properties of networks and those who apply its techniques to observed cases (who I will call "practioners"). The formalists might propose SN measures and prove their properties, but do not say anything about their applicability to any observed system. The practioners often proceed as if the measures will "work" on their networks - e.g. that a measure of centrality will tend to highlight the most influential actors.
However, agent-based models (ABM) might offer a potential solution to this. If a measure (or other SN technique) does not work with a plausible ABM of the phenomena (where we can actually check this), then we certainly can not rely on it for a similar model of observed phenomena. Some results and examples of this are given. Rather, it might be that SNA might be more reliable as a secondary analysis -- a model of a complex ABM of observed phenomena.
The slides from a class on the relationship of formal modelling and their use, with particular focus on different purposes for modelling and how they can go wrong.
Winter is coming! – how to survive the coming critical storm and demonstrate ...Bruce Edmonds
A talk at the 2014 European Social Simulation Association summer school, at UAB in Barcelona 8th sept 2014
The talk covers some of the symptoms of hype in social simulation and argues that it needs to be more careful and rigourous. In particular that the (current) purpose of a simulation needs to be distinguished between theoretical, explanatory or predictive. Each having their own critieria.
Analysing a Complex Agent-Based Model Using Data-Mining TechniquesBruce Edmonds
A talk given at "Social Simulation 2014" at Barcelona in September.
A complex “Data Integration Model” of voter behaviour is described. However it is very complex and hard to analyse. For such a model “thin” samples of the outcomes using classic parameter sweeps are inadequate. In order to get a more holistic picture of its behaviour data- mining techniques are applied to the data generated by many runs of the model, each with randomised parameter values.
Paper is at: http://cfpm.org/aacabm/analysing a complex model-v3.4.pdf
Policy Making using Modelling in a Complex worldBruce Edmonds
A talk given at the CECAN workshop, London July 2016
Abstract:
The consequences of complexity in the real world are discussed together with some meaningful ways of understanding and managing such situations. The implications of such complexity are that many social systems are fundamentally unpredictable by nature, especially when in the presence of structural change (transitions). This implies consequences for the way we model, but also for the way models are used in the policy process.
I discuss the problems arising from a too narrow focus on quantification in managing complex systems, in particular those of optimisation. I criticise some of the approaches that ignore these difficulties and pretend to approximately forecast using the impact of policy options using over-simple models. However, lack of predictability does not automatically imply a lack of managerial possibilities. We will discuss how some insights and tools from "Complexity Science" can help with such management. Managing complex systems requires a good understanding of the dynamics of the system in question - to know, before they occur, some of the real possibilities that might occur and be ready so they can be reacted to as responsively as possible. Agent based simulation will be discussed as a tool that is suitable for this task, especially in conjunction with model-informed data visualisation.
Results of field testing the indicators for resilience of socio-ecological pr...Bioversity International
Presentation by Nadia Bergamini from Bioversity International.
This was presented during a seminar hosted at Bioversity International on 'The Indicators of Resilience in Socio-Ecological Production Landscapes and Seascapes (SEPLS)' in January 2014.
Find out more: http://www.bioversityinternational.org/research-portfolio/agricultural-ecosystems/landscapes/
Socio-ecological systems: Moving beyond the Human Exemptionalist ParadigmMadhusudan Katti
A talk given by Dr. Andrew Jones on Sep 24, 2010, in the Biology Colloquium at California State University, Fresno. He presents a historical overview of how Sociology came to discover its place within a broader ecological context and began addressing the metabolic rift resulting from human activities on this planet. He also presents the conecptual framework for analysis being developed under the new Urban Long-Term Research Area - Fresno And Clovis Ecosocial Study (ULTRA-FACES) project.
A talk given to the "Social.Path" workshop at the University of Surrey, June 2014.
It is well established that many human abilities are context-dependent, including: language, preference judgement, memory, reasoning, learning and perception. This is usually taken as a negative – that there will be limits on our understanding and modelling of these abilities. However, what is not always appreciated is that context-dependency can be a powerful tool in social coordination and communication. This paper pulls together several theories about the cognition of context, and presents a computational model of context-dependency. It then sketches its role in social communication, coordination and embedding. It looks at some of the approaches to dealing with context in the computer science and social science literature and concludes that none of these squarely faces the problem of context dependency. This points towards a substantial gap in the research and hence a future programme.
Towards Institutional System Farming
A talk at the Lorentz Workshop on "Emerging Institutions: Design or Evolution?" September 2016, Leiden, NL (https://www.lorentzcenter.nl/lc/web/2016/836/info.php3?wsid=836&venue=Oort)
Using Agent-Based Simulation to integrate micro/qualitative evidence, macro-q...Bruce Edmonds
Networks are an abstraction of complex social processes. Albeit themselves formal, the social processes on which they are based can be researched using both quantitative and qualitative methods. The problem in combining these approaches comes from the very different natures and levels on which they are based. Here we describe an approach which uses agent-based modelling (ABM) as a stepping stone towards the more abstract network models. These ABMs are more in the nature of complex and dynamic descriptions than general theories, and are ideally suited for integrating a variety of kinds of evidence into a coherent fashion - including quatitative evidence to inform the micro-level behaviours of agents, and quantitative evidence about the macro, aggregate levels. The assumptions behind these kinds of ABM are relatively transparent, and the ABMs used to generate networks in a precise manner. Thus this "staging" of the abstraction process allows a well-founded mixed-methods approach to social network research. A worked example of this on voting behaviour is presented.
Possibilistic prediction and risk analyses
A talk given at the EA annual Conference, Bonn, May 2015
Abstract:
It is in the nature of complex systems that predictions that give a probability are not possible.
Indeed I argue that giving "the most likely" or "rough" prediction is more harmful than useful.
Rather an approach which maps out some of the possible outcomes is outlined.
Agent-based modelling is ideal for producing these - including, crucially, possibilities that could not have been conceived just by thinking about it (due to the fact that events can combine in ways that are more complex than the human brain can cope with directly).
A characterisation of the real future possibilities and their nature allows some positive responses to events:
* putting in place 'early warning indicators' for the emergence of identified possibilities
* contingency planning for when they are indicated.
Such an approach would allow policy makers to better 'drive' their decision making, without abnegating responsibility to experts.
How can we rely upon Social Network Measures? Agent-base modelling as the nex...Bruce Edmonds
All social network analysis of observed systems rely on assumptions, for example: how a link is defined is the right one, how the resulting network is analysed actually corresponds with our conclusions about it, etc. In other words the representation+analysis is a *model* of what we observe. Any model is fallible and thus needs independent validation, but this is rarely done in social network analysis due to the cost. Indeed, the only check is often that of face validity by the same person who collected the data and analysed it!
This lack of established validity is somewhat hidden by the divide within the field of social networks between the "formalists" who prove abstract properties of networks and those who apply its techniques to observed cases (who I will call "practioners"). The formalists might propose SN measures and prove their properties, but do not say anything about their applicability to any observed system. The practioners often proceed as if the measures will "work" on their networks - e.g. that a measure of centrality will tend to highlight the most influential actors.
However, agent-based models (ABM) might offer a potential solution to this. If a measure (or other SN technique) does not work with a plausible ABM of the phenomena (where we can actually check this), then we certainly can not rely on it for a similar model of observed phenomena. Some results and examples of this are given. Rather, it might be that SNA might be more reliable as a secondary analysis -- a model of a complex ABM of observed phenomena.
The slides from a class on the relationship of formal modelling and their use, with particular focus on different purposes for modelling and how they can go wrong.
Winter is coming! – how to survive the coming critical storm and demonstrate ...Bruce Edmonds
A talk at the 2014 European Social Simulation Association summer school, at UAB in Barcelona 8th sept 2014
The talk covers some of the symptoms of hype in social simulation and argues that it needs to be more careful and rigourous. In particular that the (current) purpose of a simulation needs to be distinguished between theoretical, explanatory or predictive. Each having their own critieria.
Analysing a Complex Agent-Based Model Using Data-Mining TechniquesBruce Edmonds
A talk given at "Social Simulation 2014" at Barcelona in September.
A complex “Data Integration Model” of voter behaviour is described. However it is very complex and hard to analyse. For such a model “thin” samples of the outcomes using classic parameter sweeps are inadequate. In order to get a more holistic picture of its behaviour data- mining techniques are applied to the data generated by many runs of the model, each with randomised parameter values.
Paper is at: http://cfpm.org/aacabm/analysing a complex model-v3.4.pdf
Policy Making using Modelling in a Complex worldBruce Edmonds
A talk given at the CECAN workshop, London July 2016
Abstract:
The consequences of complexity in the real world are discussed together with some meaningful ways of understanding and managing such situations. The implications of such complexity are that many social systems are fundamentally unpredictable by nature, especially when in the presence of structural change (transitions). This implies consequences for the way we model, but also for the way models are used in the policy process.
I discuss the problems arising from a too narrow focus on quantification in managing complex systems, in particular those of optimisation. I criticise some of the approaches that ignore these difficulties and pretend to approximately forecast using the impact of policy options using over-simple models. However, lack of predictability does not automatically imply a lack of managerial possibilities. We will discuss how some insights and tools from "Complexity Science" can help with such management. Managing complex systems requires a good understanding of the dynamics of the system in question - to know, before they occur, some of the real possibilities that might occur and be ready so they can be reacted to as responsively as possible. Agent based simulation will be discussed as a tool that is suitable for this task, especially in conjunction with model-informed data visualisation.
Slides that describe a modelling framework to represent the process of making things. Presented at the Feb 2016 project meeting of the Digital DIY project..
Risk-aware policy evaluation using agent-based simulationBruce Edmonds
A talk about how modelling of complex issues of policy relevance. It covers some of the tensions and difficulties, as well as some of the unrealistic expectations of this kind of modelling. Rather it is suggested these kinds of model should be used as a kind of risk-analysis. Two examples of this are given.
Talk given in Reykjavik at University of Iceland, 30th Nov 2016.
Staged Models for Interdisciplinary ResearchBruce Edmonds
A talk give n at CosyDy, Leeds 12th May 2016.
The papers can be read at: http://arxiv.org/abs/1604.00903 (this work, soon in PLoSOne) and http://arxiv.org/abs/1508.04024 (the further simplification step, soon in EPJ-B)
The models are at: http://openabm.org/model/4368 and http://openabm.org/model/4686
Context dependency and the development of social institutionsBruce Edmonds
A talk at the 1st Constructed Complexities workshop on "" at the University of Surrey, July 2013. http://constructedcomplexities.wordpress.com/
-----------------------
It is well established that many aspects of human cognition are context-dependent, including: memory, preferences, language, perception, reasoning and emotion. What seems to occur is that the kind of situation is recognised and information stored with respect to that. This means that when faced with a similar situation, beliefs, expectations, habits, defaults, norms, procedures etc. that are relevant to the context can be brought to bear. I will call this mental correlate of the kind of situation the “context”. Thus the mental context frames conscious thinking by preferentially providing the relevant information making learning and reasoning practical, as well as allowing relatively “crisp” and logical thought within this frame. This is the “context heuristic” that seems to have been built into us by the process of evolution.
This recognition seems to occur in a rich, fuzzy and largely unconscious manner, which means that it can be hard to give distinct identities and talk about these contexts. It can thus be problematic to talk about “the” context in many cases, and indeed one cannot assume that different people are thinking about the same situation as (effectively) the same context from a third party perspective. Indeed one of the powerful aspects of the context heuristic is that it allows us flip between mental contexts allowing us to thing about a situation or problem from different contextual frames. Due to our facility at automatically identifying context and the indefinable way it is recognised it is hard for people to retrieve what is or signals a context (in contrast to what is relevant when recognised). However, they do seem to be sensitive to when they have the wrong context.
Thus learning is not just a matter of recording beliefs, expectations, habits, defaults, norms, procedures etc. but also a matter of learning to recognise the kinds of situation to organise their remembrance. A large part of our world is humanly constructed, or common (e.g. shared human emotions or a shared environment). Our classification of these kinds of situation is thus heavily coordinated among people of the same society – we learn to recognise situations in effectively the same way and hence remember the relevant beliefs, expectations, habits, defaults, norms, procedures etc. for the same kinds of situation. A shared body of knowledge (in its wisest sense) that constitutes a culture does not only include the foreground beliefs, norms etc. but also how the world is divided into kinds of situation. Some of these contexts will have universal roots, such as the emotion of fear or being hungry, and thus might be approximately the same across cultures (without transmission), others will be specific to cultures.
The
Personal understanding and publically useful knowledge in Social SimulationBruce Edmonds
There are two different ways in which social simulation can help a researcher - by honing their intution about how certain models and mechanisms (roughly what Polanyi meant by "Personal Knowledge") and in demonstrating hypotheses that might be interesting and relevant to other researchers in the field (roughly what Popper meant by "Objective Knowledge"). Both are valid goals and useful, indeed I would argue both are essential to real progress in social simulation. However, too often, these are conflated and confused, to the detriment of social simulation. This talk aims to clearly distringuish between the two modes, including the different ways of obtaining them, their different (and complementary) uses as well as when and how these are appropriate to communicate to others. In short a "model" of simulation usefullness is outlined with implications for the method of social simulation.
Mundane Rationality as a basis for modelling and understanding behaviour wit...Bruce Edmonds
The paper starts out by pointing out the context-dependency of human cognition and behaviour, pointing out that (a) human behaviour can change sharply across contexts but also that (b) behaviour within a given context can sometimes be described in relatively simple terms . It thus argues against a grand theory of rationality that seeks to explain and/or generate human behaviour across of contexts. Rather it suggests an alternative approach whereby "mundane" accounts of rationality are used which are specific to a limited number of contexts. Such an approach has its particular difficulties, but allows the integration of narrative accounts of possible behaviours using a variety of social mechanisms at the micro level with comparisons with aggregate macro data. It is noted that in the resulting simulations that equilibria are simply not relevant within plausible timescales.
The Scandal of Generic Models in the Social SciencesBruce Edmonds
Despite overwhelming evidence that many aspects of human cognition are highly context-dependent, generic (that is models that are supposed to hold across different contexts) abound, including: most models of rationality and decision making, and most models that are based on statistically fitting equations to data. Context itself, especially social context, has been systematically by-passed by both quantitative and qualitative researchers. Quantitative researchers claim to be only interested in those patterns that are cross-context. Qualitative researchers only deal with accounts within context. Neither tackle the nature of context itself: how it works, in what ways it impacts upon behaviour.
Dealing with context is notoriously hard: the concept is slippery and its effects hard to identify. However, I claim it is not impossible to research. A combination of rich datasets and newer computational methods could help (a) identify some social contexts and (b) relate what happens within a context to how contexts are collectively constructed. Such a step could help relate quantitative and qualitative evidence in a way that is better founded and hence, perhaps, open the way to the unification of the social sciences as a coherent discipline.
Social Context
An invited talk at the 2018 Surrey Sociology Conference, Barnett Hill, Surrey, November 2018.
Although there is much evidence that context is crucial to much human cognition and social behaviour, it remains a difficult area to research. In much social science research it is either by-passed or ignored. In some qualitative research context is almost deified with any level of generalisation across contexts being left to the reader. At the other extreme, some qualitative research restricts itself to patterns that are generally detectable - that is the patterns that are left when one aggregates over many different contexts. Context is often used as a 'dustbin concept' to which otherwise unexplained variation is attributed.
This talk looks at some of the ways social context might be actively represented, understood and researched. Firstly the ideas of cognitive then social context are distinguished. Then some possible approaches to researching this are discussed, including: agent-based simulation, a context-sensitive analysis of narrative data and machine learning.
How social simulation could help social science deal with contextBruce Edmonds
An invited plenary at Social Simluation 2018, Stockholm.
This points out how context-sensitivity is fundamental to much human social behaviour, but largely bypassed or ignored in social science. I more formal social science, it is usual to assume or fit universal models, even if this covers a lot of different contexts. In qualitative social science context is almost deified, and any generalisation across contexts is passed on to those that learn from it. Agent-based modelling allows for context-sensitive models to be developed and hence the role of context explored and better understood. The talk discussed a framework for analysing narrative text using the Context-Scope-Narrative-Elements (CSNE) framework. It also illustrates a cognitive model that allows for context-dependent knowledge to be implemented wthin an agent in a simulation. The talk ends with a plea to avoid uncecessary or premature summarisation (using averages etc.).
This is the presentation that Elmarie Costandius gave at the SOTL@UJ: Towards a socially just pedagogy seminar series on the Graphic arts and social justice
socio cultural perspective in psychologyAQSA SHAHID
What is the Social-Cultural Perspective? The social-cultural perspective considers the way that different individuals interact with their social groups and how these social groups influence different individuals and how they develop throughout their lives.
Staging Model Abstraction – an example about political participationBruce Edmonds
A presentation at the workshop on ABM and Theory (From Cases to General Principles), Hannover, July 2019
This reports on work where we started with a complex, but evidence driven model, and then modelled that model sto understand and abstract from it. As reported in the paper:
Lafuerza LF, Dyson L, Edmonds B, McKane AJ (2016) Staged Models for Interdisciplinary Research. PLoS ONE, 11(6): e0157261. DOI:10.1371/journal.pone.0157261
Some supporting slides on modelling purposes and pitfalls when using ABM in policy contexts to accompany discussion on Modelling Pitfalls at the ESSA Summer School, Aberdeen, June 2019
A talk at the workshop on "Agent-Based Models in Philosophy: Prospects and Limitations", Rurh University, Bochum, Germany
Abstract:
ABMs (like other kinds of model) can be used in a purely abstract way, as a kind of thought experiment - a way of thinking about some aspect of the world that is too complicated to hold in our mind (in all its detail). In this way it both informs and complements discursive thought. However there is another set of uses for ABMs - empirical uses - where the mapping between the model and sets of observation-derived data are crucial. For these uses, one has to (a) use the mapping to get from some data to the model (b) use the model for some inference and (c) use the mapping again back to data. This includes both predictive and explanatory uses of ABMs. These are easily distinguishable from abstact uses becuase there is a fixed and well-defined relationship between the model and the data, this is not flexible on a case by case basis. In these cases the reliability comes from the composite (a)-(b)-(c) mapping, so that simplifying step (b) can be counterproductive if that means weakening steps (a) and (c) because it is the strength of the overall chain that is important. Taking the use of models in quantum mechanics as an example, one can see that sometimes the evolution of the formal models driven by empirical adequacy can be more important than the attendent abstract models used to get a feel for what is happening. Although using ABM's for empirical purposes is more challenging than for purely abstract purposes, they are being increasingly used for empirical explanation rather than thought experiments, and there is no reason to suppose that robust empirical adequacy is unachievable.
Mixing fat data, simulation and policy - what could possibly go wrong?Bruce Edmonds
A talk given at the CECAN workshop on "What Good Data could do for Evaluation" at the Alan Turing Institute, 25th Feb. 2019.
Abstract:
In complex situations (which includes most where humans are involved) it is infeasible to predict the impact of any particular policy (or even what is probable). Randomised Control Trials do not tell one: what kinds of situation a policy might work in, what are enablers and inhibitors of the effectiveness of a policy. Here I suggest that using 'fat' data and simulation might allow a possibilistic analysis of policy impact - namely an exploration of what could go surprisingly wrong (or indeed right). Whilst this does not allow the optimisation of policy, it does inform the effective monitoring of policy, and basic contingency planning. However, this requires a different approach to policy - from planning and optimisation to an adaptive approach, with richer continual monitoring and a readiness to tune or adapt policy as data comes in. Examples of this are given concerning domestic water consumption (in the main talk), and in supplementary slides: voter turnout and fishing.
Using agent-based simulation for socio-ecological uncertainty analysisBruce Edmonds
A talk given in the MMU Big Data Centrem, 30th October 2018.
Both social and ecological systems can be highly complex, but the interaction between these two worlds - a socio-ecological system (SES) - can add even greater levels. However, the maintenance of SES are vital to our well being and the health of the planet. We do not know how such systems work in practice and we lack good data about them (especially the ecological side) so predicting the effect of any particular policy is infeasible. Here we present an approach which tries to understand some of the ways in which SES may go wrong, but constructing different complex simulation models and analysing the emergent outcomes. These, in silico, examples can allow for the institution of targeted data gathering instruments that give the earliest possible warning of deleterious outcomes, and thus allow for timely remedial responses. An example of this approach applied to fisheries is described.
Agent-based modelling,laboratory experiments,and observation in the wildBruce Edmonds
An invited talk at the workshop on "Social complexity and laboratory experiments – testing assumptions and predictions of social simulation models with experiments" at Social Simulation 2018, Stockholm
Culture trumps ethnicity!– Intra-generational cultural evolution and ethnoce...Bruce Edmonds
Essential to understanding the impact of in-group bias on society is the micro-macro link and the complex dynamics involved. Agent-based modelling (ABM) is the only technique that can formally represent this and thus allow for the more rigorous exploration of possi-ble processes and their comparison with observed social phenomena. This talk discusses these issues, providing some examples of some relevant ABMs.
A talk given at the BIGSSS summer school on conflict, Bremen, Jul/Aug 2018.
An Introduction to Agent-Based ModellingBruce Edmonds
An introduction to the technique with two example models of in-group bias and voter turnout.
An invited talk at the BIGSSS Summer Schools in Computational Social Science, at the Jacobs Bremen University, July 2018.
Mixing ABM and policy...what could possibly go wrong?Bruce Edmonds
Invited talk at 19th International Workshop on Multi-Agent Based Simulation at Stockholm on 14th July 2018.
Mixing ABM and Policy ... what could possibly go wrong?
This talk looks at a number of ways in which using ABM in the context of influencing policy can go wrong: during model construction, with model application and other.
It is related to the book chapter:
Aodha, L. and Edmonds, B. (2017) Some pitfalls to beware when applying models to issues of policy relevance. In Edmonds, B. & Meyer, R. (eds.) Simulating Social Complexity - a handbook, 2nd edition. Springer, 801-822.
Different Modelling Purposes - an 'anit-theoretical' approachBruce Edmonds
Models are a tool, not a picture of reality. There are many different uses for models. The intended use of a model - its 'purpose' - affects how it is judged, checked and developed. Much confusion and bad practice in modelling can be attributed to not clearly identifying the intended 'purpose' for a model. Neo-classical Economics is used to illustrate some of these confusions. In some (but not all) uses the model stands in for a theory (at least key aspects of it), but this can happen in different ways and at different levels of abstraction. The talk looks at some of these different ways and advocates a staged, inductive methodology for theory development instead of one that jumps to high generality and simple models which confuse different uses.
A talk given at the Workshop on "From Cases To General Principles - Theory Development Through Agent-Based Modeling" see http://abm-theory.org
Socio-Ecological Simulation - a risk-assessment approachBruce Edmonds
An invited talk in Tromsoe, 5 June 2018.
Both social and ecological systems are complex, but when they combine (as when human societies farm/hunt) there is a double complexity. This complexity means it is infeasible to predict the outcome of their interaction and unwise to rely on any prediction. An alternative approach is to use complex simulations to try and discover some possible ways that such systems can go wrong. This can reveal risks that other approaches might miss, due to the fact that more of the complexity is included within the model. Once a risk is identified then measures to monitor its emergence can be implemented, allowing the earliest possible warning of this. An example of this approach applied to a fisheries ecosystem is described.
A talk at the workshop on "Thinking toys (or games) for commoning, Basel, 5/6 April, Switzerland.
This describes a simple model of anonymous donation of resources, with minimal group structuring.
Am open-access paper on this model is at: http://cfpm.org/discussionpapers/152
The model can be freely downloaded from:
http://openABM.org/model/4744
A talk at ESSA@Work, TUHH (Technical University of Hamburg), 24th Nov 2017.
Abstract: Simulation models can only be justified with respect to the models purpose or aim. The talk looks at six common purposes for modelling: prediction, explanation, analogy, theoretical exposition, description, and illustration. Each of these is briefly described, with an example and an brief analysis of the risks to achieving these, and hence how they should be demonstrated. The importance of being explicitly clear about the model purpose is repeatedly emphasised.
The Post-Truth Drift in Social SimulationBruce Edmonds
A talk at the Social Simulation Conference, Dublin, September 2017.
Abstract
The paper identifies a danger in the field of social simulation a danger of using weasel words to give a false impression to the world about the achievements of our field. Whether this is intentional or unintentional, the effect might be to damage the reputation of the field and impair its development. At the root of this is a need for brutal honesty and openness, something that can be personally difficult and that needs social support. The paper considers some of the subtle ways that this kind of post-truth drift might occur, including: confusion/conflation of modelling purpose, wishing to justify pragmatic limitations in our work, falling back to unvalidated theory, confusing using a model for a way of looking at the world for something more reliable, and seeking protection from critique in vagueness. It calls on social simulation researchers to firmly reject such a drift.
Drilling down below opinions: how co-evolving beliefs and social structure mi...Bruce Edmonds
A talk at ODCD2017, Jocob's University, Bremen, July 2017. (http://odcd2017.user.jacobs-university.de/)
The talk looks at an alternative to "linear" models which deal with a euclidean space of opinions (usually a 1D space). This is a model of belief change, where both social influence and internal consistency of beliefs co-evolve with social structure. Thus this goes beyond most opinion dynamics models in a number of ways: (a) it deals with beliefs that may underlie measured opinions (b) the internal coherency among sets of beliefs is important as well as social influence (c) the social structure co-evolves with belief change and (d) the social structures are complex and continually dynamic. The internal consistency of beliefs is based on Thagard's theory of explanatory coherence, which has some empirical support. The model seems to display some of the tensions and processes that are observed in politics, for example: the tension between moderating views so as to connect with the public vs. reinforcing the in-group coherency. It displays a dynamic that can reflect a number of different courses including those that result turning points in opinions.
A talk at the ESSA Silico Summer School in Wageningen, June 2017. It looks at some of the different purposes for a simulation model, and how complicated one should make one's model
Modelling Innovation – some options from probabilistic to radicalBruce Edmonds
A talk on the various kinds of innovation based on Margret Boden's types of creativity . Given at the European Academy, Ahrweiler, Germany 31st May 2017.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Social complexity and coupled Socio-Ecological Systems
1. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 1
Social complexity and coupled SES
Bruce Edmonds
Centre for Policy Modelling
Manchester Metropolitan University
2. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 2
This Talk
• A synthetic talk, brining together a variety of ideas
towards understanding SES over the longer term
• Parts will be familiar to people from different fields
• Goes back to the roots of human intelligence and
survival and its relationship with structural change
• In particular, the importance of social abilities in
the construction of collective ways of surviving
• E.g. the importance of culture, social embedding,
social norms and context-dependency
• I.e. parts of the picture towards understanding
human adaption to its environment
3. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 3
Structural Change in Ecology
– the long view
• Structural change is continually occurring in ecologies
everywhere (e.g. power law of extinction events)
• But at different time scales and to different extents
• Not only due to external factors, but also the
endogenous spread and emergence of species
• There is no steady state, no equilibrium, no
preservation of “an” ecology in the long run
• At the moment the overwhelming structural change is
due to humankind, not only as the new omni-predator,
but a changer of environments, an agent of species
spread and now even creating new species
4. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 4
Social Intelligence Hypothesis
Kummer, H., Daston, L., Gigerenzer, G. and Silk, J. (1997)
• The brain does not give an isolated individual
much of an advantage, compared to specialists
• The crucial evolutionary advantages that human
intelligence gives are its social abilities
• Groups of humans are able develop individual
cultures that allow them to inhabit a variety of
ecological niches (e.g. Inuit or Kalahari)
• Thus protected from specific crises, i.e. somewhat
insulated from any particular structural change (as
a whole species, not particular groups)
5. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 5
An Evolutionary Perspective on SIH
Social intelligence implies that:
• Groups of humans can develop their own (sub)cultures of
technologies, etc. (Boyd and Richerson 1985)
• These allow the group with their culture to inhabit a variety
of niches (e.g. the Kalahari, Polynesia) (Reader 1980)
• Thus humans, as a species, are able to survive
catastrophes that effect different niches in different ways
(group specialisation)
• This is not necessarily the case when we all inhabit a
single, global, niche!
• Human intelligence has emerged to create cultures that
enable it to exploit different ecologies
• Cultures can adapt to maintain enough of its environment
to survive or actively destroy it (e.g. Easter Island)
6. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 6
Implications of SIH
• That different complex “cultures” of knowledge are
significant
• An important part of those cultures is how to
socially organise, behave, coordinate etc.
• One should expect different sets of social
knowledge for different groups of people
• That these might not only be different in terms of
content but imply different ways of coordinating,
negotiating, cooperating etc.
• That these will relate as a complete “package” to
some extent
• That human cognition has a core social purpose –
providing abilities for such cultures to develop
7. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 7
Social Embedding
• Granovetter (1985)
• Contrasts with the under- and over-socialised
models of behaviour
• That the particular patterns of social
interactions between individuals matter
• In other words, only looking at individual
behaviour or aggregate behaviour misses
crucial aspects
• That the causes of behaviour might be spread
throughout a society – “causal spread”
• Shown clearly in some simulation models
8. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 8
Illustration of Causal Complexity
Lines indicate causal link in behaviour, each box an agent
(Edmonds 1999)
9. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 9
Implications of Social Embedding
• In many circumstances agents can learn to
exploit the computation and knowledge in their
society, rather than do it themselves (invest in
what Warren Buffet invests in)
• Knowledge is often not explicit but is
something learned – this takes time
• This is particularly true of social knowledge –
studying guides as to living in a culture are not
the same as living there for a time
• Social embedding means that human
behaviour can not be understood well separate
from its cultural context
10. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 10
Social Norms
• Come from society to effectively constrain the
action of individuals
• Not same as “group goals” or utility considerations
• Are linked to the relevant reference group
• Are a complex phenomena – a dynamic
combination of cognitive and social phenomena
• An individual’s perception of others is important
• Norms emerge, become established, maybe
become explicit, and fall into disuse
• Maybe more important in determining action than
rational choice of action within constraints
11. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 11
Implications of Social Norms
• Social norms are a very powerful way of aiding
coordination and control
• Can be very effective in limiting damage to
environment
• Are not ‘rational’ but usually have a rationale
• Once established can ‘lock in’, even when the
‘reasons’ for them have long disappeared
• In the longer run, dependent on occasional
reinforcement (e.g. policing) for maintenance
• An enforcement-norms-habit structure
• Often more significant than punishment, reward
12. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 12
Context-Dependency of Cognition
• Many aspects of human cognition are context-
dependent, including: memory, visual perception,
choice making, reasoning, emotion, and language
• The brain somehow deals with situational context
effectively, abstracting kinds of situations so relevant
information can be easily and preferentially accessed
• Learning new information, reasoning, deciding new
action occurs with respect to the particular context
• It is not known how the brain does this, and probably
does this in a rich, unconscious and complex way that
might prevent easy labeling/reification of contexts
13. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 13
The Social Co-Development of Shared
Recognised Context
• Over time, due to their similarities, certain kinds of
situation become recognised as similar by participants
• This facilitates the development of a set of shared
habits, norms, knowledge, language etc. that is
specific to the context
• The more this happens the more distinctive that kind
of situation becomes and hence more recognisable by
newcomers
• Eventually these may become institutionalised in
terms of infranstructure, training etc. (e.g. how to
behave in a lecture theatre)
• This co-development of context may be the reason for
its social/evolutionary value
14. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 14
Implications of the Context-
Dependency of Human Behaviour
• Behaviour of observed actors might change sharply
across different social contexts
• The relevant behaviour, norms, kinds of interaction
etc. might also change
• Social contexts are co-developed and changing
• They may be different for different groups
• Some kinds of social behaviour seem to be inherently
context-dependent (compliance)
• It is unlikely that a lot of key social knowledge, norms,
behaviour etc. will be generic
• Models that assume a cross-context engine of human
behaviour may be deeply misleading!
15. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 15
A Picture of Social Rationality
• Yes, individuals are somewhat rational, in the sense
of having identifiable goals and tending to act to
further their goals but…
• …but the roots and characteristics of our intelligence
are substantially social in nature
• Most of our individual goals are social in nature – they
cannot be achieved on our own
• Many of our goals are created by society
• How we think about action is socially formed
• Dependent on information from others
• What we do is constrained by social norms, laws
habits, suggestions, imagined possibilities
16. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 16
Adaption
Different kinds of adaption involved…
• Groups of humans spread to many parts of the world,
inhabiting various different environments
• Groups of humans develop very different ways of
organising, living, technologies, cultures…
• …partly in response to their environments, but also
creatively in response to each other
• Some of these groups of humans persist for a time
and some fail
• Some cultures seem to have adapted to fit into their
local environment, many very creative
• but some seemed to get “locked-in” to a way of life
• sometimes success is due to doing very stupid things
17. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 17
The Complexity of Long-Term
Co-existence
• We no longer live in separate ecological niches so
failing will not just affect one place, one group
• Some short-term problems may be amenable to
scientific study and solutions, stepping outside culture
and looking at particular situations
• Others might be solvable via political action within the
current structures and culture of society
• But the longer-term, more difficult problem is how to
understand then structure how our society works so
humans can survive and maintain ecological diversity
• And so avoid ecological problems and adapt to
subsequent problems within a global context
18. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 18
How we might do this
• Study ecological, cognitive and social aspects
together or (at least, in the context of each other)
• Abandon individual rationality as a starting point and
rather look at rationality as largely social
• Including such as social norms, status, power
structures, cultures, ways of communicating
• Look at scenarios where the aim is not just solve a
simple “game theoretic” problem, but respond to a
complex and adaptive environment
• Where a complex society is embedded within a
complex ecology
• Look at longer scales of adaption to provide context
for short-term studies
19. Social complexity and coupled SES, Bruce Edmonds, SES-LINK, Stockholm, June 2104. slide 19
The End!
Centre for Policy Modelling:
http://cfpm.org
I will upload these slides to:
http://slideshare.net/BruceEdmonds