This post consists of some notes that looking at the analogy of natural & artificial selection to design and its consequences. A worthwhile paper on a related but different topic is Christina Cogdell’s Products or Bodies? Streamline Design and Eugenics as Applied Biology (2003) Design Issues, 19(1), 36-53. doi:10.1162/074793603762667683
Types of Selection
The purpose of this page is to describe how natural selection can be used as a framing tool for recognizing how artifacts, services, and interventions can affect individuals and natural populations of humans and other species. The point is not to draw a direct analogy, but to try to link the effects of the things we make to the behaviors, growth, and flourishing of living things. These are not so much set rues as they are a set of guides that can help us reconsider the expected effects of changing our environment in order to evaluate the risk and alternative future possibilities involved in the production of technology from the most precursory to the most complex.
I was intrigued after a reading group discussion we had about anthropometrics. Wikipedia defines anthropometrics as the measurement of human to gather statistical data about the distribution of body dimensions in the population are used to optimize products. I would alter this definition slightly to say design products rather than optimize. Humans change and so do products.
We were a little unsettled by the focus only on human needs and the intent that anthropometry be entirely in support of comfort and ease of use. Taking a more critical approach, we started to brainstorm all of the different ways that design structures human and non-human behavior. We started to keep an eye open for ways that design and evolution can begin to interact. We hit some dead ends so I reached out.
I asked a group of colleagues if they knew of any comprehensive taxonomy of selection, and here is what one of them (Joel) contributed:
There are so many different ways to split selection up that it can be mind-boggling. To make it worse, those who study molecular evolution use different terms (positive, balancing) than those of us who study phenotypic selection. I don’t think there’s a way to taxonomize the terms satisfactorily, at least in a tree. It would probably look more like a convoluted Venn diagram.
That said, Joel laid out four areas that can be used to focus our attention. I’ve modified them from his interpretation, but they are basically agents, episodes, modes, and scales.
Here is how he originally wrote about it in his response to me:
In the phenotypic selection realm, I tend to split selection up in four different ways, based on agents, levels, fitness components, and mode.
The agent of selection, that is, the factor that causes fitness differences to arise, can be either ecological (phyisical or heterospecific) or conspecific. I would call the former ecological selection and the latter social selection (sensu West-Eberhard). The latter would tend to subsume sexual selection, which tends to be caused by male-male or male-female interactions. Includes frequency-dependent and density-dependent or other x-dependent.
The level of selection describes the units that exhibit fitness differences (which, annoyingly, Gould call “agents” of selection). This can be individual selection, and at higher levels, family selection, group selection, kin selection, social selection (sensu Wolf, Moore, and Brodie), etc. Hard and soft selection can fall under this category as well–Wade and Goodnight have good papers discussing this.
Third, selection can be split into different “episodes” by splitting total fitness into multiple components. This is usually done because it is empirically convenient, or to examine evolutionary trade-offs. This gives rise to terms like survival selection, fecundity selection, and sexual selection.
Finally, you can describe selection based on the shape of the fitness surface, i.e. the “mode.” This includes directional (linear), stabilizing, disruptive, and correlational (all three quadratic). Of course, the shape of the fitness surface is often complex, and you can have elements of all of these going on at once when you’re considering multiple traits.
Reframing Selection
We might think about what Joel said differently and transform it as the grammatical structure of a sentence. Where:
AGENT = SUBJECT
SELECTION =VERB
EPISODE = DIRECT OBJECT
MODE might be akin to diagramming the entire sentence. while SCALE is more like the context that the sentence takes place within (e.g. the paragraph or passage).
Agents
Agent refer to the most causal explanation for the response to selection. Agents provide the mechanistic explanation and frequently are the antagonists to the entity/entities experiencing the effects of selection.
From a designer’s perspective, these agents should be the artifacts or services we create either with the intent to exert some selective force or ameliorate it.
We can understand these as ecological agents that affect anything from the climate of our surroundings, our food supply, the structure or our living and working spaces, interactions with outer species (as in pets, disease, or domesticated laborers), and even perhaps to our conventional definitions of time that enable further articulations of the environment.
Similarly social agents work along the lines of our own perception, learned, and innate behaviors to enumerate male-male, male-female, family, and cooperative interactions. Sensation and display are extremely important because they distinguish among individuals to allow decisions about how to interact. Social agents range from clothing, jewelery and other status symbols to weapons, traditions, and business plans as agents of cooperation or competition.
There is a nice hybrid space too where ecological and social meet in the production of artifacts favoring or disfavoring reproduction–in vitro fertilization on one hand…and condoms on the other, for example.
Often, agent-based selection is described as selecting for trait ‘x’ and can even be more complicated when traits x, y, and z covary as a result of this selection. As a consequence we find that selection can be multi-facited and not reducible to a single interaction. Hence, we need to reconsider the cumulative effects of each agent’s contribution.
Episodic
Moving along the causal chain (if we can indeed identify it), we would then want to understand the factors or physical attributes that are on the receiving end of the agents’ work. From an empirical perspective, this is often where conflict begins and fluctuates in an ever-present set of trade-offs. We can split the effects into many different components looking at reproduction, lifespan, health, outlook, social status, niche, range, communicativeness, and, perhaps most importantly, agency (as the ability of an individual to act as its own agent).
This is the main point of interest in design–i.e. what, where, when do the effects of the design work manifest in nature?
Mode and Variance
In order to understand what patterns are present, evolutionary biologists look at variation and the response of a particular trait or episode to selection from agents. Here attention is focused on the values of the entire population in contrast to just the trait itself. We can certainly use these visualizations and modes to describe the distributions of episodic traits, but here there is explicit quantitative emphasis on the response to selection over one or more generations.
We can think about it in different ways: populational and interactional or hard and soft.
Populational
Populational patterns include the ideal types of directional (linear), stabilizing, disruptive, and correlational (all three quadratic), and null (no selection). The shape of the fitness surface is often complex, and you can have elements of all of these going on at once when you’re considering multiple traits.
This graph depicts four abstract types of natural selection. The colors are used only to differentiate between types. The axes show the proportion of individuals in the population as a function of their trait values through time.
The graph below is composed of four of these types where the axes show the proportion of the population as a function of trait values through time. The shaded areas represent the part of those populations that is being selected for. The color simply differentiates between types. Correlational selection is not shown because it consists of the interaction of multiple traits in response to selection, and we would need a 3-dimensional graph to show just two of those traits changing.
From the graph you can see the response of a population to null selection. Because mutation-based variation is not selected out of the population, the shape of the distribution randomly changes and will not fit a “standard” distribution.
The blue, directionally-selected distributions move (you guessed it) directionally because of pressure against one end of the distribution.
Likewise, stabilizing selection in green is like directional, but instead of one end the pressures are exerted to stabilize the mean.
For diversifying (aka disruptive) selection in red, the mean is selected against–leaving greater proportions near the previous tails of the distribution.
Interactional
The second way is what I call interactional, meaning it depends on the interactions among agents, often in space. Here, ecological agents and social agents exert their effects. The goal of this description is to capture the meaning behind the mechanism (thus, interaction) rather than the change over time. When coupled with population visualization techniques, one begins to get a dynamic picture of evolutionary change.
We may be able to consider correlational selection as a special case of interactional (and not populational) because the internal constraints within a population’s gene pool and genomic regulation are effectively a suite of internal genetic interactors at a different scale.
Normally however, we can think of interactional patterns in terms of frequency-dependence, density-dependence, or some other x-dependent factor related to ecological or social agents. So frequency-dependence, for example, is just a way of describing the total effect of agents…or of saying that the trait in question responds in a way that is frequency-dependent.
The main difference is that interactional describes the mechanism of selection itself (within a generation), while populational describes the response to selection (change between generations).
Putting the two together means we could graph dynamic change.
Hard
Both hard selection and soft selection are relative to the population as a whole. Hard selection is like a bat chasing an insect. The insect has some maximum speed that it can flee and the bat has some speed that it can chase. Assuming it is only the bat and the insect, then there is hard selection for the speed at which the insect can flee.
Soft
Of course insects are probably not alone since they tend to aggregate in large populations. Soft selection takes this into account and considers the effect of more than one insect fleeing. Here the insect needs not be faster than the bat, just faster than the other insects that the bat is following!
The major difference is one of absolute value or of percentage. Hard selection works on the absolute value of a trait while soft selection works on a percentage of the distribution of trait values.
Scale
The scope of impact of a particular service of artifact is also important, especially when we ask the question, “for whom?” Is it working on a emergent trait or even creating one? Examples might include political systems or policies that increase or decrease emmigration, the locating of a hazard that increases mutation rates, or one child policy.
Whereas before we were only considering a single ideal population, what happens when we include multiple populations? Does the work of the designer or design team affect traits that span across individuals and include qualities that can only be formed from collective-action?
Some levels of scale might include: individual, family, kin, group, social, community, or ecological.
Disaggregation among natural and social scientific communities can lead to misunderstandings about the different components of disaster management and socio-ecological systems. Terms like resilient, adaptive, robust are often used to describe systems and their processes and come up in the literature, policy, and the media very frequently. They have catch my attention because they have different use patterns in the field I know a little about: biology.
Adaptation, coping, resilience, and robustness have similar definitions, but they sometimes have different technical definitions across disciplines. Their different meanings contribute to their value, and they highlight the differences in perspectives that each scientific community contributes. However, the details matter for distinguishing important components of systems and what aspects might be suggestive for new insights or that might be responsive to intervention or assessment. It’s also important to establish common ground meanings when communities get together and work towards common goals.
The following represents some of my notes and thinking as I try to sort out the definitions on my own. For me, it means asking how different perspectives contribute to the ways in which we interact in socio-ecological systems.
Adaptation
The Intergovernmental Panel on Climate Change (IPCC) 4th Assessment Report defines adaptation as:
Initiatives and measures to reduce the vulnerability of natural and human systems against actual or expected climate change effects. Various types of adaptation exist, e.g. anticipatory and reactive, private and public, and autonomous and planned. Examples are raising river or coastal dikes, the substitution of more temperature-shock resistant plants for sensitive ones, etc.
This definition takes its function from the ability of humans to manipulate their environment, making it better suited to human-identified goals and interests, even if acting on behalf of other organisms. Some synonyms include alteration, modification, redesign, remodeling, revamping, reworking, reconstruction, conversion, adjustment, acclimatization, acclimation, accommodations, habituation, acculturation, assimilation, and integration.
Adaptation is also used to describe genetically-accumulated evolutionary change over time in organisms as a response to natural selection. This is different from the case where manipulating the environment substitutes in the short-term replaces the pressure of genetic adaptation over the long term.
So I suppose this is why it calls to mind a version of evolution based on characters acquired in its lifetime (commonly known as Lamarckian inheritance)–if only for the appropriation of the term adaptation to refer to intra (within) generational processes and not inter (between) generational processes.
Adaptation for evolutionary biologists typically means processes through which a population becomes better suited to its environment over the course of many generations, often through natural selection. A great deal of debate and research has been directed at how we recognize adaptation in hindsight. This is because it can be difficult to state the causes for the evolution of a trait when we do not have direct observation and only historical signatures to learn from. Most notably this was discussed in “The Spandrels of San Marco”, a paper by Stephen Gould and Richard Lewontin (1979) that uses an analogy from architecture for the evolution of organismal form and function.
I agree that changing the environment in the ways mentioned in the IPCC definition will likely limit vulnerabilities for humans and other populations. However, there is an implicit assumption here that the goal should be for humans NOT to have to adapt over a course of generations–despite the inevitability of genetic change over time. It presupposes an assumption of stasis – and a very western one when compared to eastern notions of change and mutability. Richard Nisbett catalogues how some of these assumptions about change and stasis in his book The Geography of Thought. For me, it depends on what time scale one is looking to understand if stasis or change is more relevant. Still, I think its difficult to argue anymore that stasis is more relevant than change.
The necessary question should not be IF we should adapt (genetically or by manipulating the environment). Instead we should ask, “What are we adapting to and how are we getting there?” Will humans and other populations be adapting to artificially-supported ‘vulnerability balloons’ as we are almost surely doing now through our uses of technology and fossil fuels?
This question of adaptive goal is important because the IPCC definitions include definitions of costs and benefits with its description of adaptation. To what goal are these costs and benefits applied? Within the frame of a generation or an organism’s lifetime, explicating goals may make sense, but ascribing goals to a ecosystem – much less whole populations – gets very very slippery. You start to need some way to implicate who or what is writing that mission statement.
Similarly the IPCC includes adaptive capacity in its glossary as the ability, institutions, and resources that can be used to implement adaptation measures.
I think this is all a bit confusing, and I feel it makes more sense to reserve the definition of adaptation for genetic, phenotypic, and behavioral attenuation of organisms or systems to their environment across generations. To describe the processes that organisms and systems use during their lifetimes I think we need a term that encompasses more variability, one that is less blatantly anthropocentric and functionalist in its approach to socio-ecological coevolution. We also need a long view on systems not ones that are limited to single generations only – something that the biological definition of adaptation retains but that the socio-technical one does not.
Borrowing from the literature of evolutionary biology, behavior, and developmental biology, plasticity seems far better suited to the processes of environmental manipulation being described by the IPCC. This is because it references a material (plastic) that maintains its basic molecular structure while having variable capacity to take on any number of manipulations or forms.
Coping and Plasticity
The terms coping and adaptation are sometimes used interchangeably leading to confusion. Here I think there is some opportunity to disentangle the two. A compilation of brainstorming sessions by groups of development practitioners in Ghana, Niger and Nepal described some differences which were then documented in the Climate Vulnerability and Capacity Analysis Handbook. The results of the group’s sessions were pointing to what I think was a difference between 1) consistent and conscious actions to reduce vulnerability (adaptation) versus 2) ad hoc solutions (coping).
It’s worthwhile to differentiate coping and adaptation as within and between generation processes, respectively. Biologists use plasticity to describe the ability of an organism or group to adjust within its lifetime via behavioral or developmental responses to the environment. This may indeed include manipulation of the environment to decrease vulnerability. Phenotypic plasticity is a description that could easily encompass artifacts, behaviors, institutions, and aggregations of resources as extensions of an organism’s phenotype. It invokes important concepts from evolutionary biology including the role of cooperation in building and maintaining extended phenotypes (such as aggregations of useful materials like insurance, band-aids, and water) or how phenotypic reaction norms can change in response to different environments–shedding light on why a strategy in one environment may not be as successful in another. There is further correspondence here with plasticity and the concept of developmental canalization (that organismal systems can get locked in to specific trajectories) and with the concept of path dependence in the development of economic and institutional systems.
So a better definition of plasticity might re-appropriate the IPCC’s definition of adaptation and rework it as:
An adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects, which moderates harm or exploits beneficial opportunities. Plasticity operates through cognitive (sensing), social (interactional), physiological, and other mechanisms that can adjust to a wide range of variability. Plasticity is the ability to respond to variability and a range of realized and possible futures continuously and in a sustained approach. Plasticity or coping strategies attenuate the use of resources to local needs and involve planning that hybridizes old and new knowledge and strategies in an exploratory process.
Here I think this definition makes it much easier to bridge what may be happening at a physiological level (cellular temperature variation, sweating) with responses at an artifact level (clothing, ventilation) and an institutional (e.g. policies towards what it means to be cool).
This is because the term plasticity explicitly invokes a connotation of variability, while adaptation feels more like a description of how well two things (in this case organism or population and environment) fit together. Clearly, if the environment is highly variable we need variability in our systems, not assumptions and values of how well we already fit and work within it.
Coping, on the other hand, seems pretty straightforward. Survive. It makes sense to leave a lot of variability open for this one, because when it comes time for coping strategies, any and all tactics may be appropriate. But then again, there can be ways to cope that are more responsive than others. But I think this starts to dig into a definition of resilience or robustness, where the system properties begin to matter more than than how they manifest themselves in practice. What I mean by this is that as people, organisms, and ecosystems attempt to cope with change, their ability to draw on networks or strategies for coping is itself embedded in the system. Some systems, as a function of their structure, cope better than others. Consequently the adapt better than other too.
Resilience
The Climate Vulnerability and Capacity Analysis Handbook adapts its definition from UNISDR (2009) defining resilience as “the ability of a system to resist, absorb, and recover from the effects of hazards in a timely and efficient manner, preserving or restoring its essential basic structures, functions, and identity.”
The IPCC defines resilience as “the ability of a social or ecological system to absorb disturbances while retaining the same basic structure and ways of functioning, the capacity for self-organisation, and the capacity to adapt to stress and change.”
While Walker et al (2004) define resilience as “the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks.”
In these cases resilience emphasizes a system’s ability to maintain or return to specific structural or functional features–i.e. to maintain its identity, its durability, its persistence. But as noted by Erica Jen in her article “Stable or Robust? What’s the Difference?” (2005), the choices of features or structural elements that we attend to are important for assessing both the capacity and quality of that responsiveness to change.
So what is the function, what is functional, and for whom? Definitions matter.
One way to think about resilience is to imagine a couple of different water balloons. One balloon is filled halfway full. Another is filled so that the latex rubber that composes its surface and membrane is stretched tightly to hold the water in. Now you can throw both balloons back and forth between each other, and neither may pop. But what do you think will happen when the balloons are stretched, twisted, or allowed to drop on the ground where a twig might be a hazard to the already tense surface of the overfilled balloon? It will probably pop and spill the water out.
A system’s resilience is a lot like a water balloon, and the degree of resilience is determined by how much water is forced into the balloon, the size of the balloon, and how much it is pushed to its limits. We might think of the balloons shape, its ‘throwability’ or the thickness of its membrane as examples of functional or structural elements. In most cases, we are looking at how well the balloon is able to maintain it shape and its continuity despite being stressed – i.e. it is functionally a ‘water balloon’, it has a round shape, and responds to the exterior and interior pressures of air and water.
Rarely do we think that a water balloon might reconfigure itself, rearranging the organization of its functions, structural elements, or features to be able to accomplish the same task differently. What would happen if the water and the balloon separated or if the water balloon system was able to draw on other systems (e.g. refrigeration) to change the relationships between its functional elements? What if we no longer simply considered only the water inside of the balloon as the system responding to the task of throwing? What if the throwing and catching movements were also included? Would we still think of a resilient system, or would we start to walk a path of robustness–of being able to adjust the definitions and constraints of the systems themselves in pursuit of coevolutionary relationships between them?
Robustness
Robustness is a different beast altogether – literally. While resilience is focused on maintaining a system, we can describe robustness as the ability of a system to change and in doing so to respond to environment and to develop entirely new functions as a result.
Some argue that robustness describes the ability of a system to withstand mutations and maintain its phenotype or “shape” as a result (Wagner, 2005). Instead I think there is a greater correspondence of robustness with transformation as used by Walker et al (2004). Transformability is “the capacity to create a fundamentally new system when ecological, economic, or social (including political) conditions make the existing system untenable.” I’m less sure about the “untenable” part of Walker et al’s definition.
Robustness is the ability of a system to evolve system functions, not simply maintain those that already exist. In this way, an analogy can be drawn between adaptation/robustness and plasticity/resilience. Similarly, I think robustness has a quality of being parametric. Parametric architecture has the quality of being built from common construction principles, but by varying the parameter values of those rules of construction, endless forms become possible.
References
Walker, B., C. S. Holling, S. R. Carpenter, and A. Kinzig. 2004. Resilience, adaptability and transformability in social–ecological systems. Ecology and Society 9(2): 5. [online] URL: http://www.ecologyandsociety.org/vol9/iss2/art5
UNISDR, 2009. Terminology: Basic terms of disaster risk reduction and IISD et al, 2007. Community-based Risk Screening – Adaptation and Livelihoods (CRiSTAL) User’s Manual, Version 3.0.
Climate Vulnerability and Capacity Analysis Handbook
IPCC, 2007: Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Annex I., M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden and C.E. Hanson, Eds., Cambridge University Press, Cambridge, UK, 976pp.
Stephen Jay Gould and Richard C. Lewontin. “The Spandrels of San Marco and the Panglossian Paradigm: A Critique of the Adaptationist Programme” Proc. Roy. Soc. London B 205 (1979) pp. 581-598
Wagner, Andreas. 2005. Robustness and Evolvability in Living Systems (Princeton Studies in Complexity). Princeton University Press.
Nisbett, R. E. (2004). The Geography of Thought: How Asians and Westerners Think Differently…and Why. Simon and Schuster.
Love this talk by the designer of evoke: the ten-week crash course in changing the world. Besides her breakdown of what gamers are good at, she nails a critical point: games can give you lots of characters who are willing to TRUST you and match challenges to your level–providing collaboration, feedback, and an engaging story–something we all need more of. She ends with a a better tactic around futurecasting: imagine the best scenario possible—then empower people to achieve it.
It’s not often that unfunded proposals make their way into disinfecting daylight. Sometimes you try again, and sometimes you just let them waste away among the dusty electrons of your hard drive.
I don’t know which category this one falls into, but I do feel it’s worth sharing and making public. Perhaps someone will even comment with improvements. I can only hope.
In any case, this proposal was dependent on a constellation of partnerships (and funding) to make the project move forward–at least from my perspective. Sometime a little cash can help develop needed projects and spur collaboration. This was a submission to the Knight News Challenge which is supposed to announce its winners sometime in mid-June. Since I know I’m already out of the running, there isn’t really a compelling reason not to share—but please tell me if there is!!!
envirocasting logo
Anyhow, here is most of it—-minus some names to protect the innocent—–except one: this logo was created by Zack Denfeld, and we’ve used it on a variety of projects. For more, you should visit his launchpad.
Describe your project:
Envirocasting adapts global weather information to the cultural and operational needs of local [international disaster preparedness organization] branch offices and communities, supporting their risk assessment and preparedness needs. A wealth of information exists to support disaster preparedness, but a gap exists between the design of information services and their local use-contexts, limiting widespread use and effectiveness. The benefits of these information services are clear to local decision makers, and they are anxious to put the tools and news sources into practice.
However, exposure to digital news platforms is low, and the capacity to use them in decision making contexts is minimal as a result of this disconnect between design and use.
Envirocasting takes a design anthropology approach to inform the design, distribution, and acquisition of digital weather information services to local decision makers. Design anthropology seeks to understand the role of design artifacts and processes in defining what it means to be human. Using this approach, local patterns of information consumption and culture related to futures, information design, and technological metaphors can be identified, allowing for the design of appropriate services. Design principles as well as specific, local use-applications will aid in the distribution and assessment of weather forecast efficacy. Thus, weather news for risk assessment can flow more precipitously to decision makers, allowing them to coordinate the disaster preparedness efforts more quickly and strategically.
Simulation games for local communities will support learning and the application of information services in context. This provides use-case memories of the future and practice in managing uncertainty with minimal risk.
How will your project improve the way news and information are delivered to geographic communities?
Envirocasting aims to localize climate information by making it simple, non-technical, clear, easy to use, and as meaningful as possible. Maps are relevant when their colors, numbers, icons, and scales are relevant and supported by culture and context. Information that connects with specific actions can be used confidently in planning and decision making. Specific use-cases communicated by local communities will drive the development process and will help weave the digital media fabric with aesthetics, narratives, and metaphors. Games support critical thinking and social play to help decision makers and communities explore the dynamics of news and information-based decisions for climate-related disaster preparedness.
How is your idea innovative? (new or different from what already exists)
Envirocasting innovates by translating connections between design and use. When local conditions refract the design and dissemination of information from distant or multiple sources, innovation is an inherent byproduct. Envirocasting is designed with the mind in mind, understanding cultural legacies that influence the recognition of uncertainty and metaphors. It bridges experience, play, and interactions, creating memories of the future. The project identifies appropriate implementations of open-source digital information services and defines a set of prescriptive resources for innovating across disaster risk contexts and cultural processes based on abstractions and lessons from six local communities in three countries.
What unmet need does your proposal answer?
A fact-finding mission conducted surveys, interviews, meetings and workshops over two-month periods in 2008 and 2009.
Explicit unmet needs include:
An Increase in the Accessibility and User-Friendliness of Climate Information Products
New Products to Fill Information Gaps for Needs–Starting with Improved Flood Forecasting Tools
Training in the Use of Climate Tools and How Climate Information Could Trigger Action Such as:
Learning to access and interpret climate information tools.
Learning how to monitor seasonal forecasts in conjunction with medium and short-term forecasts.
Understanding how to take gradated actions.
Channels of communication and decision-making to receive and take action based on time-sensitive climate information.
And don’t take my word for it:
What will you have changed by the end of your project?
More-Measurable outcomes:
Prototypes that adapt weather information services to local use-contexts.
Documents that communicate design processes for cross-cultural communication.
Heuristics or ‘rules-of-thumb’ for the design of climate information services for risk assessment.
Country and local use-context reports that document specific patterns of information acquisition and behavior.
Relevance of climate information for local decision-makers.
Ability to align information with decision and action.
A folktaxonomy of climate information and categories for creating a cultural consensus model (CCM) to realize translations in cognition and practice among cultural contexts.
An index of context-specific actions and the values associated with them.
Less-measurable outcomes:
Perception of the design process and innovation pathways for news and information about climate-driven risks.
The relationship between information providers, researchers, designers, policy makers, and implementing offices providing the opportunity for continued support, training and dialogue necessary to realize the potential benefits of using climate information.
Channels of communication between information providers and decision makers and between decision makers and community constituents (incl. digital information services).
The scope of the implementing organizations to conduct cross-cultural research and information adaptation projects.
How will you measure progress and ultimately success?
The uses of weather and hazard preparedness information can be measured using surveys, interviews, meetings and workshops and compared to current estimates of use and use cases, but those data are useful differently for different people including the decision-makers, their constituents, their supporting agencies, and funders of this project. Thus, we intend to cast progress in varied terms for the different stakeholders and partners.
Some of these guiding questions include:
What are the iterations, changes, and improvements to existing systems?
What does the trajectory of individual decision-maker’s tasks or questioning look like?
How do other elements of the media ecology change and what stakeholders are invoked or leveraged in the process?
Success, on the other hand, is more elusive. Disasters are sporadic and may not always afford a direct link between information effectiveness and risk reduction. However, existing case studies show that these types of information, when combined with specific actions, can lead to significant reductions in both the vulnerability and negative effects of a disaster such as flooding. The key to assessment it to engage in a continual processes where we value choices and transitions in practice. The design of this project take into account the high-stakes involved in the decision-making and information uses by providing opportunities for both high stakes (post-hazard) and low stakes (simulation-games) assessment.
Do you see any risk in the development of your project?
The biggest risk at present is that the organizations listed do not have a history of working together (this is indicated by the generic names rather than their proper ones), but this is also where the opportunity exists. The leadership (particularly of the larger orgs) is wary of their participation in the project without first-hand knowledge of all partners and/or certain funding. This conversation is ongoing at the time of this application and continues to develop. If the proposal moves through to the next round, we should at that point be able to name each of the partners in more specific terms.
Supply-side risks (design-mediated)
Inability to generate meaning either through lack of empathy or translation of needs to designers
Research products are not absorbed and implemented during the design processes because they are non-normative, unclear for direct application, left uncommunicated, or other
Partner coalition denatures from lack of shared goals or mental models
Emphasis on technological development or information diversification over use-context and user needs
Existing insights, stakeholders, and methods are unknown or unengaged
Irrelevance, inability, or non-linkage of digital mediums and meaningful information services
Cultural heterogenetiy too great for scaling of appropriate information services
Ability and capacity of project managers to recognize and adapt to other sources of risk
Expertise of project partners is missing or unleveraged
Translation of local use-contexts into primary research is distorted or biased
Demand-side risks (user-mediated)
Low frequency acquisition of technology platforms, information services, and/or symbolic systems
Scripting of use and application to local decision making is unclear
Appropriation for local use-cases is nonexistent
Assembly does not fit into the local context of everyday life
Cannot be integrated into normal practices, culture, and concerns
Practice with information and platform is sparse
What is your marketing plan? How will people learn about what you are doing?
The conduits for marketing are, in many respects, already in place. The organizational structure and extent of [intl. disaster preparedness agency] branch offices will facilitate branding and distribution using existing networks of community organization, tactical planning, and response offices. Though the value of the services should be self-evident in the design and cognitive acquisition of the services, the goal is to help users to practice using and applying these information services. We also recognize that aesthetic values can elevate the recognition of value and the maintenance of that value through everyday use. Thus, arriving at these values will be a principle objective for all participants.
In order to increase domain knowledge, the outcomes can be shared among the participants, their centers, and via professional and interest networks including the design research community which actively engages with similar project goals. Because some of the project partners include university centers, schools and research organizations, the outcomes will be shared with emerging professionals including graduate students and visiting fellows.
Tactically, the marketing plan for simulation game-based training is slightly more difficult because it requires additional preparation, training, and presentation. Nonetheless, with a bit of effort, these games will reinforce the marketing strategy for the primary goal of adapting weather information using the same local community branch office network structure. We also expect to develop videos that demonstrate our process as well as the use and value of the informations service under construction. But ultimately, the best marketing will be the effectiveness of the adaptation process.
Is this a one-time experiment or do you think it will continue after the grant? If it is to be self-sustainable, what’s the plan for making that happen?
Envirocasting is the application of a process to translate meaning across cultural contexts with relevance for local concerns. We do not view it as an experimental process so much and an underutilized one. Luckily, there are many resources, case studies, and additional expertise to draw from in the process. Our goal is to assemble them and to draw the pieces together into relevant platforms and prototypes for weather information services.
The project will accomplish this goal as a one-time research project that will publicly document its methods and outcomes as guides so that they can be applied in new use-contexts and for wider information arrays. We fully expect that the different project partners will continue to apply the work and experience in varied ways after the initial project, although they may carry it out to their own ends.
Our method for fostering rhizomatic-like dissemination of the results (and thus, sustainability) is to link with additional strategic partners whose networks span varied social groups, languages, use-contexts, and concerns. Furthermore, the acquisition and integration of the research (as well as the information services it supports) can be broadly advocated from a policy perspective because successes arise from its application and benefit in specific, local communities. The overall plan for sustainability is to demonstrate that these information service platforms reduce risk by enabling decisive action before pending hazards become disasters. If this is demonstrated, sustainability will ensue, even if not in the form described in this proposal.
The article details the proposition that our adaptive capacity–to respond to environmental feedback–to learn–is structured by the double bind, a concept coined by Gregory Bateson. A double bind is when an individual receives conflicting messages (intransitivity of preferences?) that disallows action on their part because responding to either message means being in conflict with the other. Wikipedia has a more detailed description here, but Bateson’s articulation of the concept can be found in Steps to an Ecology of Mind (2000, University of Chicago Press).
The author’s argument is that sustainability, or human-environment interactions that respond dynamically to each other, is constrained because beliefs about oneself and the community are increasingly biased towards individual level sustainability for two reasons. First, individual safety is increasingly linked to individual performance. Second, alienation from environmental feedback loops means that an amplification of uncertainty is taking place resulting many more belief ‘nodes’ about systems level relationships. This amplification results in greater propensity for conflict to develop between an individual’s assessment of the environment/system and their own well-being.
The task they outline is manifold–having many forms and elements. It means developing a shared cognitive base from which to develop mental models for collective action. The goal of a shared cognitive base is to help connect system level safety ideals to individual level belief nodes They argue that to do this requires “simple messages with the potential to shape individual belief systems”. Excessive information is to be avoided, while everyone should have access to the building blocks of conceptual blends that synthesize complex information.
The authors, Antal and Hukkinen, argue that more direct and influential injunctions should be exchanged to help reframe the context towards systems-individual linkages–not just individual. Thus an injunction, “Become a vegetarian” becomes the positive injunctive norm, “Become a vegetarian to maintain the status quo” and then makes more sense in terms of promoting sustainable behavior when coupled with a positive injunctive future norm, “Become a vegetarian so our civilization can survive.” This tactic seems similar to one described in the book Nudge (Thaler and Sunstein, Penguin Books, 2009) where they describe some forms of social nudges based on experiments in judgment and decision making.
Thaler and Sunstein describe how some forms of social nudges unfold. These include:
Increasing compliance when one is informed that others are complying–i.e. drawing public attention to what others are doing.
Emphasize the positive injunctive norm encourages behavior that helps maintain the commons. (e.g. “Please don’t do this in order to keep it this way.”)
Show what the norm actually is, as opposed the the perceived norm.
Small encouragements or discouragements can maintain or induce new norms.
The example of the positive injunctive norm seems to be what Antal and Hukkinen are advocating, but with a touch more bite.
Their case lies in creating cognitively accessible links between systems status and individual experience. An example of this might be an electricity brownout linked to CO2 accumulation or perhaps a full blackout each time species diversity is degraded.
Their conclusion that ICT services are needed to help these links form is predictable. Systems like smart grids, early warning systems, and other membership and signaling tools are appropriate, but the burning question is how to implement them in society where the tools themselves do not reflect the normative values.
One scenario I had after reading this is a case where an electrical power generation company that is responsible for supplying the city creates more direct informational links with its consumers. Neighborhoods in the city already experience frequent and irregular cuts in supply. Engineers, particularly in energy, tend to focus on maintaining supply based on certain assumptions. Sometimes we don’t always know what those assumptions are. Smart grids have been identified as a solution bridging consumption and supply (albeit from a supply perspective), but what if there was a more jugaad solution?
I am hereby coining the term Ener-geets™ to describe a form of information transfer between energy consumers and energy suppliers. Let’s say consumption is pretty high. It’s hot. Everyone has fans running, AND the big cricket match is on. Power suppliers have decisions to make in order to maintain a consistent supply, but what if they could provide realtime feedback to their customers that threshold levels were being reached and if their behavior didn’t change, they might loose the ability to follow the cricket match to its conclusion.
Cut the normal means of feedback out for the time being (an energy bill or brownout) and allow the power operator to send a message, perhaps in the form a tweet (from Twitter), to everyone following those tweets. Potential overshoots to the grid capacity could be avoided. But then, this would go against established channels of information flow and place a great deal of responsibility in the power operator’s hands–er..mobile phone.
To connect the feedback loop, individual consumers could also be sending messages, informing of power cuts, potential spikes in use (a festival perhaps), or other changes or observations about consumption at the individual level.
You start to get the picture. Now, how do w do it?
Ref: Miklos Antal, Janne I. Hukkinen, The art of the cognitive war to save the planet, Ecological Economics, In Press, Corrected Proof, Available online 3 February 2010, ISSN 0921-8009, DOI: 10.1016/j.ecolecon.2010.01.002.
(http://www.sciencedirect.com/science/article/B6VDY-4Y9HP0Y-2/2/8effb7b70d90787bc2250323ffeef134)
Keywords: Human-environment interaction; Belief systems; Environmental strategy; Climate change communication; Cognitive studies
I recently scanned this report that leveraged domain understanding in psychology to the problem of climate change. While the problem of climate changed could just as easily be reframed as a problem of recognizing variability and relevance, the research and patterns that the report draws upon can be used in the design process as levers to recognize opportunities and constraints for sustainability and adaptation.
It’s worth noting that the authors admit that the results are not drawn from a representative sample of the world’s population. Most of the work described comes only from studies done in North America, Europe, and Australia. Even the researchers who put the report together were from only the United States, Canada, Australia, and one member with dual citizenship in the United States and Germany. So while the report doesn’t represent a diversity of perspectives, it does emphasize the fact that there are significant gaps in our knowledge about environmental psychology and what intercultural similarities and differences exist in how we perceive and respond to problems like climate change.
Given that much of the work in the report describes what we could call cognitive or psychological biases, there are probably vary important differences in the processes people will use to adapt to climate variability. Indeed, one finding was that perceptions & reactions to climate risks are mediated by cultural values and beliefs.
Examples of design levers (observation followed by lever):
Small probability events tend to be underestimated when based on personal experience. Thus, designer should gather multiple personal experiences (embodiment? experiential learning?)
Recently occurred small probability events tend to be overestimated. Thus designer should show longer time frames (the historical context?)
Emotions influence perceptions of risk with respect to climate change. Thus, people tend to be conflicted and muted because it is seen as being beyond personal control.
The report also details how psychology looks at the relationship between consumption and behavior, where individual ability + motivation, context, and external motivators shape practice.
There was also a specific focus on the psychosocial impacts of climate change as driven by health an by relationships with common goods.
Adaptation in this context has multiple conduits:
sense making
causal and responsibility attributions for adverse instances
Which can be affected by media representations as both formal and informal social discourse that moderates the social construction, representation, amplification, and attenuation of risk and impacts.
In summary, the report identified psychological barriers to climate change action:
unaware
unsure
lack of trust or believeability
“not in my backyard”
fixed behavior
other people’s problem
belief that actions are unimportant or make no difference
engaged in token or objectively unhelpful actions
not under human control
other competing goals, time, resource, or effort draws
Much of the discussion and research seemed to point to a question of the cognitive architecture of risk. That is, how are categories learned, does information become relevant, risk construed, and behavior adopted? And what does that mean for vulnerability and adaptation?
Detection of climate change means distinguishing between climate and weather, making relevant the need for planning and decision making, and addressing expectations based on categories (e.g. latitude or place) since these beliefs bias the direction of our errors in perception. It also means understanding how information acquisition takes place which leads to differences in perception and action even when it comes from the same source.
associative + affective processes + repeated personal experience = fast and automatic
Daniela Plewe’s discussion brings me back to some thoughts and notes I made about Marcel Duchamp’s Coefficient d’Art. Duchamp described it as:
“An arithmetical relation between the unexpressed but intended and the unintentionally expressed.”
It is intended to describe the difference between what artists intend and what the spectator perceives. For Duchamp, this difference is in the act of communication or transaction, where certain differences and attributions of value are made out of the interaction among individuals. It this coefficient that structures the viewers engagement with artifacts and allows them opportunities to appropriate objects to their own needs and ends.
For Duchamp, the coefficient of art could be good (+), bad (-) or indifferent (=), but the sign of the coefficient had no bearing on the effectiveness of the work itself–only the difference between the agency of the artists to produce a desired effect in the minds of the spectators. The effect itself is up for further negotiation between them.
Mutual information is a similar concept to the coefficient of art, but it comes from information theory and describes the amount of information one thing tells about another thing. In other words, it is the reduction in uncertainty of one thing due to knowledge of another. If we ask how information (and consequently, meaning) is shared between different sources of uncertainty (like an object and a spectator or an object and its artist), we may be able to get a sense of how they are connected and how they might respond to each other.
Mutual information is helpful as a concept because we want to understand how interactions vary with one another–i.e. how interaction values may/may not change as a result of signals, actions, and assumptions.
A component of mutual information is information entropy. Entropy is a measure of uncertainty associated with a variable and quantifies the information contained in a message. It is similar to the coefficient of art; it may describe the uncertainty associated with an artwork as judged by the spectator. Conversely, it could describe the absence of meaning when one does not know the value of the work. Likewise the spectator may themselves exhibit high entropy (high uncertainty) relative to the artist if the artist knows little about the spectator and how they will perceive the artwork….at least that’s how I think it would go.
The coefficient of art is a compelling concept. It suggests that that art has an effect, and if an effect–value in context. Describing that value is very close to the describing what difference the work of art makes, either to the spectator or some chain extending through them.
Borrowing from evolutionary and network theory, one could pull in a set of relationships between interacting agents that describe how networks evolve and persist. Relationships endure over time from the benefits of interaction. In network reciprocity, entities pay a cost, c, while their number of neighbors, k, receive a benefit, b. If b/c > k, where the ratio of benefits to costs is greater than the sum of neighbors, the network persists because its members are gaining as a result of their interactions.
Duchamp’s coefficient of art (hereafter described using the greek letter psi, ϕ; see also: epistasis), approximates the number of neighbors, but as indicated by it separation from the actual effect of the work itself, says nothing about costs and benefits. ϕ approximates k, or rather the reciprocal of k, because as the number of neighbors (or spectators of the work) increases, the likely ability of the artwork to communicate intent, decreases. This is because of variation among the spectators who may either not be well-understood by the artist or who are perceiving differently or because the artist. Interestingly, ϕ always assumes artistic intent. If ϕ is low, it may be the ‘fault’ of the spectator, the inability of the artist to realize that intent, or of some other intervening factor.
But what about art that is created beyond intent such as generative, algorithmic, or emergent artworks?
ϕ may also be a bound on the ability of artifacts to bridge social groups, as in the case of boundary objects that have multiple uses. The intent of the maker of that object is only partially achieved, but may clearly be appropriated to serve other purposes. Here we might similarly invoke a coefficient of use–or a measure of intent in use that transforms the intent of the artist.
Far from achieving certainty, at least the idea of ϕ, of a coefficient of art, starts to unlock more questions about translation and meaning between objects and people–and of the directionality of interactions between people.
Anthropogenic Biomes as a Region for Research in Evolutionary Design Ecology
Many systems of classification for regions ignore the integration of human influence and ecosystem form, process, and diversity. This situation was common when I was in school and we learned about different ecological regions that were described largely by vegetation type and the weather patterns. A definition of region that is based on many interactions between society and nature, including perspectives on global patterns of sustained direct human interaction with ecosystems, may be appropriate for weighing studies of human health, its interactions, and driving factors. Anthropogenic biome describes a recent and perhaps better system of regional classification than have previous definitions (Ellis and Ramankutty, 2008) which have tended towards pure forms of nature or the separation of nature and society.
Anthropogenic Biomes: Definition
Anthropogenic biomes are similar to ecological biomes: they describe patterns of vegetation, climate, and ecosystem processes. However, they also take into account the anthropogenic influences of land use and population density on ecosystem processes. Ellis and Ramankutty characterize anthropogenic biomes as heterogeneous landscape mosaics, combining a variety of different land uses and land covers. Some of this heterogeneity is driven by natural landscape variation, as well as human enhancement of natural landscape (e.g. intensive agriculture) and human created landscape (e.g. construction of settlements and transportation systems).
The Regional Classification System they developed is as Follows (Ellis and Ramankutty, 2008): Dense Settlements: Urban, Dense Settlements
Of Earth’s 6.4 billion human inhabitants:
40% live in dense settlements biomes (82% urban population),
40% live in village biomes (38% urban),
15% live in cropland biomes (7% urban), and
5% live in rangeland biomes (5% urban)
0.6% live in forested biomes.
Asia and Oceania have the most diversity in the distribution of these regions around the world.
Global Anthropogenic Biomes
Further refinement is possible (Alessa and Chapin, 2008) by resolving distributions of social values, dietary patterns, movement patterns, resource use and between local and regional scales, inter alia.
Why Anthropogenic Biomes Matter for Public Health and Other Forms of Research
Anthropogenic biomes are a more accurate description of broad ecological patterns than are systems that exclusively describe vegetation patterns based on variations in climate and geology. Likewise, anthropogenic biomes may be better at representing patterns of human interactions with the environment and describing the driving factors in health outcomes. There are multiple reasons for this that stem from the varied roles that ecosystem, climate, cultural, and social relationships enact in dialogue with each other.
Anthropogenic biomes differ substantially in terms of basic ecosystem processes (eg carbon emissions, reactive nitrogen) and ecosystem biodiversity. These factors in turn affect the relative availability of resources for that region, including and especially ecosystem services like clean air and water and nutrient availability for agriculture. Furthermore, they must necessarily feed back into human ways of knowing and interacting with the environment.
Anthropogenic biomes can be connected to global patterns of ecosystem processes, along with anticipated future increases in human influence on ecosystems and the associated health outcomes due to climate change-driven risk factors.
Genome by environment interactions may be particularly relevant at this scale of interaction. The region definition is appropriate to human movement patterns and thus exposure to sources of chronic and acute risk from disease and consumption patterns.
The land use type itself determines a wide variety of factors including interactions with other humans, livestock, dietary consumption, levels of hydration, energy intensity, and other factors.
Culture, ethnicity, and language are also important in response to land use and domestic patterns of consumption ranging from food use and taboos, communication of lifestyle and health options, provisioning of nutrition, water, and energy, availability, and the use of technology to process and maintain different lifestyle patterns.
In each of these regional definitions, the interactions between landscape and human activity affects affluence, access to health care, and political regulation which suggests that these are are other possible subdivisions since these regions correspond to human social, transport, technological, and social networks–especially in dense settlements versus villages and remote areas.
For these reasons, anthropogenic biomes may provide more of a mosaic-like image from which to base categorizations used by clinical and other studies of health compared to political and continental boundaries which conventionalize migration barriers and tribal relationships. Geographic and political definitions will slowly shift, leaving only historical genetic signatures. Furthermore, anthro biomes are not specific to any particular disease or health outcome. They may encompass suites of infection and disease patterning where behavior, exposure, risk, and land use are correlated. They may also be indicative of linked health outcomes at the physiological level where, for example, musculoskeletal disorders and endocrine system perturbations are bound by human-influenced ecosystem interactions. Or they may suggest psychological correlates, linking cognition and landscape to disease and health risks.
The main point to consider is that ecological relationships, including land use and human infrastructure development, script behavior and consumption in ways that drive health outcomes. Understanding human influenced ecosystem patterns helps us identify areas of positive feedback between health risks, land use, population density, and the construction of everyday life.
References
Alessa, L., & Chapin, F. S. (2008). Anthropogenic biomes: a key contribution to earth-system science. Trends in Ecology & Evolution, 23(10), 529–531.
Ellis, E. C., & Ramankutty, N. (2008). Putting people in the map: anthropogenic biomes of the world. Frontiers in Ecology and the Environment, 6(8), 439–447.
This is one of the best popular articles I have read on the psychological factors affecting individual and group decision making in complex, high-stakes uncertainty. The focus of this article is on climate change, but the implication can be translated to other problems just as easily. This is simply because of the scale and the way that problem itself is generated. The scale is large and usually prohibits people from seeing the impacts of decisions, while it is also caused by many individuals making choices that contribute to the problem.
It amazes me that in all of the discussion documented in the article, there is never a mention of designers, artists, or any other such expertise that actually spends the majority of its effort on communication, messaging, experience design, and the use of sensory mechanisms to motivate behavior. It makes me sad that there is the recognition that, when it comes to communication, it’s always about the researchers doing the communication. This can be improved, yes, and there are also many design-thinking guidelines one can pull out of the article. How many can you spot?
A letter to this week’s Nature describes a study that reveals an interesting model of human movement patterns. The study is the first of its kind for the simple reason that the researchers were able to objectively track people in the natural environment by using mobile phone locations as proxies for their movement.
location tracking phone
Biologists have been performing similar studies on animals for years, using radio tracking devices and similar forms of locations awareness. However, because people tend to be difficult to keep track of, subject to influence from experimental methods, and resistant to monitoring by others, it has been previously difficult to get this kind of accurate data about humans.
Without recapping the study itself (you can read the original abstract and related news stories from the links below), there are many reasons why these data are interesting and useful. The least of which concern us with how people behave and how their behavior translates into public health practice, urban planning, education and communication. For me, the most interesting questions come when we understand what kinds of heterogeneity exist in populations. Understanding what motivates people to behave and respond differently is curious, especially when it relates to their cognitive capacities, their environment, and their learned behaviors. Thus we can begin to ask questions about how systems like architecture or policy, at very different scales, affect systems at other scales–like human reproductive choices for instance.
This study demonstrated that people aren’t really all that interesting in the movements, which is to simply say that we are predictable. We generally stay close to home or work and move in small bursts around these areas most of the time. Occasionally we make wider forays across the landscape.
There are privacy concerns to be negotiated. Many have been critical of the use of this information for the study. To my mind I don’t find the use of the data in the current study problematic for two reasons: 1) there is no identifying information available in the data, and 2) the mobile phones companies have been collecting this data, often out of legal obligation for billing precision, and using it for proprietary purposes with contractual consent from subscribers. I think it is important that some public good be made of the information, even if it means simply bringing to light the fact that these kinds of data are ubiquitously collected under the terms of cell phone contracts. Furthermore, a sample of people in the study explicitly consented to having their movements tracked as part of a value-added service, associated with navigation or weather for example.
Still, the study raises questions and begs for further social questioning and negotiating. I think where it starts to become problematic is when these studies begin to impede personal autonomy. Then again, the negotiations are where all the fun is…
