The Institute for the Future’s (IFTF) 2010 Map of the Decade is part of their annual Ten-Year Forecast which uses foresight and scenario planning to help organizations navigate change. Entitled “The Future is a High-Resolution Game”, the research materials demonstrate the re-emergence of games as a systematic process for positive change.
Map of the Future
IFTF uses a variety of strategies to help groups understand and interpret macro-level trends across several functional areas including carbon, water, power, cities, and identity. The long term goal is to use these sensemaking activities to meet diverse economic, technological, social, political, and ecological challenges. For organizations it is often the case that the interpretation and implementation can be difficult to connect. As foresight and sensemaking tactics become better honed to organizations of different sizes, structures, and cultures, so will the tools that help dedicated individuals in organizations recognize emerging landscapes AND translate those insights into priorities.
One key in making these translations is the ability to connect macro level processes to micro level behaviors – and everything in between. IFTF took a different tactic towards games as a tool for their 2010 map of the decade, and I think it helps move us in that direction of positive change.
IFTF has been at the forefront of what some call gamification – the systematic use of game mechanics for the development of positive psychology, practice, action, and cooperative dynamics. As IFTF’s Director of Game Development describes, games are put together with a goal, rules, a feedback system and voluntary participation. So it’s pretty easy to see how game mechanics can connect with operational challenges such as problem solving, productivity, and personal growth within organizations.
Critics argue that in most organizations and real-world situations things are pretty fuzzy, conflicted, and confusing. Agreeing on goals, rules, feedback systems, and participation can be difficult obstacles to begin with. But I think that is why games are tools that help us move in positive directions. We don’t often want to spend too much of our time arguing over goals; we’d rather just get on with it, play/work hard, and feel good about what we accomplish.
Th polling organization Gallup conducts surveys among employees every year across thousands of organizations worldwide asking hundreds of questions. THREE of those questions where employees responded positively turn out to be the largest human factors for organizations that are successful.
I have a commitment to quality.
I know what my job and/or role is, and
I trust my leadership.
Organizations are set up to accomplish a wide array of highly-complex tasks. No one person can keep track of everything. So in order to get things done, people have to simplify their overall cognitive load. They have to eliminate many conflicts and sources of confusion to deal with what they know and how it relates to new challenges. Game mechanics (goals, rules, feedback, participation) can be vectors for the above three factors, and more importantly they systematize them within organizational processes – something good human resource departments struggle to do everyday.
Think about it. I trust my leadership so I don’t always need to reevaluate the goals. Check. I know what my role is so the rules are clear. Check. I have a commitment to quality which means that I show up to participate and when I get feedback I self-correct to improve what I’m doing. Check.
I think the differences there have a lot to do with focus – of setting priorities and knowing what to spend one’s time on – especially when things go awry. We often get distracted, but even when we don’t human, social, and technological systems are always out of sync. Sometimes they connect and we may even experience periods of intense connectivity, creativity, and productivity. Albert-Laszlo Barabasi calls these bursts. So I suppose one of the benefits of the scenario platform IFTF uses is its ability to concentrate social interactions to achieve these bursts. We always need some latent time to process, connect, and search further. Maybe that’s why IFTF does the Map just once a year
One element of IFTF’s Map of the Decade is “The Happiness Kit”. It’s a platform for helping people ruminate on the kinds of transitions that could lead to more happiness in the world. There are a few standard tools of the foresight practice included like writing headlines from the future to identifying events that might shape or be shaped by the trends. There are also points where participants can identify new services, communities, and practices.
In science and technology sociologist Bruno Latour’s book Reassembling the Social, he looks specifically at groups, actions, objects, and facts as sources of uncertainty in the emergence of new technologies or innovation paradigms. These highly social elements tend to reveal themselves when controversies emerge. They help shape our future when, for example, a nuclear plant melts down and new groups, objects or facts insert themselves into society. Most recently at the Fukushima nuclear plant, it was formerly an established fact that the leaked radiation was 10% of Chernobyl disaster. Now as a society we are learning much more about nuclear radiation leakage models and their diversity when it is revealed that two different groups used two different models. The fact has been revised to 20%. We also know much more now about the safety mechanisms at nuclear facilities, especially the roles of strange monsters like emergency generators, vents, and containment vessels. Groups we never really paid attention to, methods of establishing facts, and objects with strange names all the sudden appear as important factors for how we think about the future. Kits like the IFTF Happiness Kit help us by working through some of them before they emerge from other events.
The kit also works to identify the actors involved in these transitions – as well as the distribution of those that are happy and those that are not. Understanding the distribution and abundance of elements in a system is important when we consider that rare things may become more prevalent and ubiquitous things sometimes disappear. William Gibson is famously quoted, “The future is already here — it’s just not very evenly distributed.” As we consider technological diffusion, development, and knowledge-networking, one of the questions we have to ask is how the future can be more evenly distributed. I’m not sure I know the answer, but I think that getting more explicit about the social-technological-ecological networks that individuals live in can help. This graph of system elements in a rural farmer’s immediate grasp might be one step towards understanding, for example, the diffusion of organic farming methods and how they interlink with new sources of income and time for alternative activities.
Overall the thing I like the best about the map of the decade is its ability to use foresight methods while leaving open space for individual interpretations. Some scenario techniques can lead to overarching narratives which create sources of bias. In IFTF’s platform, it appears that participants are encouraged to apply the trends to their immediate organizations and processes (although I cannot be sure since I’m reading the product and not the use-context). My sense is that it’s more of a constructionist approach than the methods used by Royal Dutch Shell or the Global Business Network (for a critique see: Wright 2004; pdf) which define opposing axes and use those for story generation. The way IFTF does it is to throw out a variety of results, new ideas, patterns, and processes – allowing users to pick and choose where to apply them. It’s a more humble approach (if I may say so) that stems from the simple proposition that we can’t really predict what is going to happen and neither can we take everything into account. The point is attenuate our mental models towards things that we think will matter – so that when they become relevant – we notice them.
Still I think there are opportunities to bring greater resolution and hence greater relevance to the process. While the Map of the Future helps deal with actors and events, I think it gets less explicit in areas that matter a lot. More important than who or what is why. The goals that actors have lays out different sets of procedures for attaining those goals. So it’s important to demonstrate how goals and the ways that actors achieve those goals converge on other elements. For example, resources and boundaries are areas that can undergo rapid restructuring or remain relatively stable over time. Helping people make explicit predictions about the direction and magnitude of these changes is helpful for understand the complex dynamics of interacting systems.
Similarly, rules, conflicts, and the outcomes of conflicts are specific pivot points for change. What helps us navigate change well is being able to understand the implications on all side of those transformations. Whiles rules, conflicts, and outcomes are somewhat embedded in the IFTF process, how can we support thinking about how they would change and what changes they would bring in turn to the procedures or boundaries shared by different actors?
I think these additional elements can be added to these types of foresight exercises with little additional cost. And they yield a huge benefit of allowing the results and products of foresight exercises – namely the knowledge generated – to be transferred to the engineers that develop computational simulations. Actors, Goals, Procedures, Boundaries, Rules, Resources, Conflicts and Outcomes are all the basics of putting together agent-based simulation models that allow us to look at the interactions and assumptions of our exercises and turn it into sustained practice.
After all, wouldn’t it be really cool if the Future WAS a High Resolution Game?
The CDC’s done a really smart thing. They lied. They created an entirely “unscientific” risk to respond to a completely “scientific” human bias. The CDC provided an emergency management and disaster preparedness plan in case of a Zombie Apocalypse. This says two things to me: 1) the CDC is serious enough in its priorities to ignore the boundary work that usually goes on in science organizations that tries to keep culture and science separate, and 2) they understand that human bias often impedes our ability to prepare for more “rational” risks.
So I would call this a media coup – especially if (as I suspect) there was a huge spike in visits to their sitesince the story crashed the server. I’m sure it helped that some people are actually predicting a zombie apocalypse this weekend.
What I like about this is the acknowledgment that people are interested in fiction at least as much as they are in reality. As a scientist or policy maker in disaster management, it’s worth recognizing that people aren’t going to respond or think a certain way just because it makes the most rational sense. Zombies may make more sense because they tap into deeper fears and hopes and long-held narratives that are embedded in our cultural fabric.
post-normal science
Humans have all sorts of biases, and instead of assuming that people are going to just believe elements of science based on their rationality, we ought to start mixing the science with some more compelling narration. This may be a good indicator of its practical value of working with a paradigm of post-normal science. Post-normal science is typically characterized by cases where facts are uncertain or contested and values are in dispute. Because so much of science and its applications relies on us to make rational choices, and yet we often don’t, there’s a case to be made that the transition of new scientific meaning from discovery to practice is post-normal because it is highly influenced by our cognitive biases.
Using zombies to carry the more important message of preparedness – and the specific steps to take – is way more important than the reality of a zombie apocalypse. Then again, better safe than sorry!
Design is a sticky practice. It is looped with contradictions, uncertainties, and material constraints. Bringing something new into the world, be it an artifact or service raises challenges that few individuals can surmount – if at all. Despite the dominant view that geniuses, visionaries, and otherwise crafty individuals are solely responsible for designed creations, organizations play a far greater and often unattributed role. Perhaps it is because of the aesthetic flair worked into the surface of the object or experience, or maybe it’s the personality of the driving individual that points us in the direction of these myths. And they are myths, because even the most brilliant designer owes their success at the end of the day to at least one group – their participants, their users. More likely is “rock-star” designers owe the production of a product or service to many more who inhabit a long chain in the process of design, implementation, and distribution.
Diego Rivera's "Detroit Industry, South Wall"
Somewhere along the chain of causation between creative individuals and their users there exists a group of people, places, ideas, and things that operate synchronistically and synergistically to develop ideas into concepts, concepts into prototypes, prototypes into experiences, experiences into practices, and practices into lessons. These sets of translations encompass different skill sets and relationships, few of which are possible without deep and varied interactions across different environments.
Taking stock of an emerging design practice is something we do often these days. I think it springs from places that have recognized and internalized failures for what they are – opportunities – and from people who embrace reflection as positive forces for learning and adaptive change.
Our environments are changing. And they will continue to do so. Even if we find pathways to design static landscapes that include fixed social interactions, the resources and habitat available to us and other species will remain in flux. Consider that in 2008, we reached the threshold where 50% of the world’s human population resides in urban dwellings (and possibly also 50% of the world’s population of cockroaches, starlings, street dogs, and sewer rats).
It’s also true that the biosphere can no longer be considered ‘natural’ in the same terms that 18th century Romantics did, as something pure, something to be conserved, something separate. The landscapes of our contemporary experience are human enmeshed – neither dominated nor resistant to our desires to interact, to use, and to understand. They show our preferences for stable communities supported by agriculture that reinforce a growing feedback loop between population growth and energy consumption. The Anthropocene, as this epoch is now commonly referred to, places a point on some linear timeline where people demonstrated their best applications of the idea of progress. Perhaps it is only our external concept of the sublime that are disappearing from the human range of experience.
There is much greater landscape diversity than has ever existed, but certainly it is less inhabitable by the majority of the world biological diversity. Landscape diversity is created not only by people and their continued interpretations of “safe” and “prosperous”, but also by animals and plants that push and get pushed into their own new and divergent niches. Patches of materials are being collected and redistributed to form wild hybrids and pure spaces– bacteria-resistant surfaces, show rose gardens, crude oil-slicked sandy beaches, tourist-friendly rainforest, wildlife mobility solutions, skyscraper concrete pillars, semiconductors, and extra-terrestrial orbiting robots – to name just a few.
Each time new patches are created, they exemplify the desires and possibilities available for their inhabitants. They provide food, space for living, courses for exercise, obstacles for navigation, challenges and threats between groups that aim to occupy more patches, places to hide, and places to trade. Evolutionary history has demonstrated that cooperation confers a significant strategic advantage to those who choose to communicate, share, and build together. In human terms, one need only look at the migratory patterns of individuals from rural to urban settlements to understand that there is a direct and perceived economic advantage from sharing land, resources, infrastructure, and culture on people’s livelihoods – not to mention social mobility.
Detail from wall illustration at the Golden Temple, Namdroling Monastery, India
Design practices are widening. They are gaining breadth proportional to their influence on economic productivity, their ability to expand social engagement and political empowerment, and perhaps because of the impact that social studies of science and technology has provided to our appreciation of artifacts as catalysts for knowledge. Scientists and technologists are viewed as inventors, individual carries of the modern ideal of progress. We now recognize that images, laboratory spaces, institutions, public media, and mechanical parts play as significant a role in chance events, innovation, and the acquisition of scientific and technological dogma by civil society.
One of the implications of an expanded design practice is the gradual inclusion of organizations as ‘objects’ for design. Organizations were once the purview of managers, business executives, policy makers, and human resources consultants, but they can now be confidently lumped together with paint, plaster, and photo emulsion.
I’m sure this is raising red flags for some who read this, and it should. It’s a scary proposition for some to think that individual behaviors can and should be designed and organized. But it is a fact that individual and group behaviors are already structured by the designed and so-called natural environment along with normalized social interactions and perceptions of social agency. The only thing we gain by ignoring the structures that are already in place (albeit unconsciously) is the freedom from self-awareness, individual and collective agency to solve more challenging and complex problems. The more we ignore these unconscious behaviors (eating habits for example) that already exist, the more they leads us into deep patterns and habits that can be difficult to get out of for reasons of fear, inexperience, ability, or just a lack of awareness.
This is not to say it is all negative. If we had to pay attention to everything we did, we would fall apart from exhaustion while trying to make complicated decisions. Many of our biases may have developed because they habituate us into safe spaces for interaction. Unfortunately, as our societies and environments change, those safe spaces may be retreating, and it’s worth reflecting on our biases and how our individual and group dynamics promote infrastructures for flourishing.
Organizational management has become a major discipline of the 20th century with the adoption of increasingly complicated tasks and industrial processes. It stands to become more integrated into our systems and psyche, but will management theories dominate – or will design envelop management in favor more distributed processes of self-organization consistent with cybernetics and decision theory?
Groups change, and so do their goals. It is a part of life and society, and it always will be. The questions that we ought to be asking is how, where, through whom, and when do they change?
There is ample evidence that organizational behavior is at the root of innovation and robustness across enterprises. The shape and tenor of a group of people, each with different tasks, and working towards a common goal varies widely – not to mention the tasks, people and goals – and that’s assuming those goals are shared among the group members! Without going into the theory and practice of organizational behavior for which there is a massive literature, I simply want to raise the point that organizational design may be a more recent practice and one that plays a role in or strategies for adaptation, sustainability, and inclusive growth.
In part II, I’ll look at some examples where designers are tackling organizational design as project and process.
The image above was the first draft. This is the second. Thanks to Aliya for good, perceptive comments.
attachmentModel_v2
Premises:
Culture as the processes that allow the uptake of processes, procedures, information, beliefs, values and social norms.
Cultural affiliations are attachments.
Attachments and reattachments are limited (quantity) and constrained (quality) by pressures.
Aspiration is a cultural step in creating capability.
Based in part on: Appadurai, A., 2004, ‘The Capacity to Aspire: Culture and the Terms of Recognition’, in Rao, V. and Walton, M., (eds.) Culture and Public Action, Stanford University Press, Palo Alto, California, pp 59-84.
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.
Philip Zimbardo conveys how our individual perspectives of time affect our work, health and well-being. Time influences who we are as a person, how we view relationships and how we act in the world. Via RSA
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.
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