Behavioral/Consumer Psychology and Transcending Paradigms 9/28/2010
In our workshop today, we discussed strategies for changing practices of consumption in a region like the Chesapeake Bay. Looking to Meadows’ “leverage points” as guidance, we thought of several “solutions” that would reduce consumption. Mainly, our solutions relied on methods of peer-pressuring those who overconsume: making water and electricity meters public knowledge and incentivizing the lightest consumers. We also considered several top-down methods like reintroducing home-economics into elementary and high-school education to teach students about healthy living, consuming, and eating. Finally, we looked to prototypes like Habitat for Humanity’s ReStore, which sells left-over materials from construction sites (perceived by contractors as waste) to consumers.
Ultimately, transcending paradigms boils down to changing people’s habits—or behavioral economics.
I had the pleasure of attending several of Dan Ariely’s lectures at Duke. Ariely is a professor of behavioral /consumer economics who studies how simple changes in how information is represented can effect an enormous—often irrational—change in a consumer’s behavior. He also writes an incredible blog on behavioral psychology (see below). In his blog, Ariely describes how our convention of measuring fuel consumption in Miles per Gallon does not directly reflect the cost differences of fuel-efficient cars versus gas-guzzlers. He uses the following example: (I’ve pasted a portion of his blog post below)
You have two cars, one is a very inefficient van (giving you on average 5 MPG) and one is a relatively efficient sedan (giving you on average 20 MPG). Due to your work and obligations you have to drive each of them the same distance every month.
You need both types of cars and for now you can replace only one of them. What should you replace?
Option 1: Replace the 5 MPG van with a 10 MPG van
Option 2 Replace the 20 MPG sedan with a 50 MPG sedanWhat would you select?
Does this sound odd? Lets look at it more carefully: Lets assume that people drive 100 miles a month. This means that the 5 MPG van uses 20 gallons a month while the 20 MPG sedan uses 5 gallons a month. Now what if we change them? If we change the van we would change from using 20 gallons a month to using 10 gallons a month (saving 10 gallons a month). If we change the sedan we would change from using 5 gallons a month to using 2 gallons a month (saving 3 gallons a month). Now it is clear that changing the van is a much better move.
Why is this not obvious to people from the MPG information? It is because comparing MPG don’t directly reflect the cost differences. In Europe they present efficiency measures I liters per 100 kilometers, and this seems to be a much more intuitive measure.
One advice is clear – if you think about changing a car, change first the least efficient car.
Ariely’s study reinforces one of Meadows’ leverage points: that the freedom and accessibility of information can lead to transcending paradigms. However, Ariely’s findings goes one step further: that the way that information is represented has a direct effect on people’s behavior regardless of the information’s accessibility. As Ariely observed, consumers often make irrational choices, even when confronted with all of the information.
Obviously, Ariely’s cause (that we must be attentive to how information is represented) is perfect fodder for designers.
There are also two amazing TED talks by Dan Ariely on consumer psychology:
Sun Dial Challenge 9/28/2010
Incredible that the person who wrote “never” drew the exact shape that the light cast on the wall!
Appraising our Global Ecosystem 9/19/2010
The Ecosystems Exchange:
In The Value of the World’s Ecosystem Services and Natural Capital, Costanza addresses the concerns of environmental policy-makers and lobbyists: how to appraise the global ecosystem and natural capital in a world dominated by global economy and monetary capital.
Costanza appraises “natural services” through the lens of an economist. By perceiving the global ecosystem as a quantifiable “stock” (inextricably connected to the global economic system), Costanza estimates a current market value ($33 trillion) and GDP ($18 trillion). Costanza’s evaluation of the world’s ecosystems implies that humanity should seriously “invest” in “natural capital” to support our ecosystems’ growth.
Nevertheless, by deploying an economical approach, Costanza ultimately confronts the age-old problem of “exchange”: a commodity’s value is produced in the exchange. If ecosystems are meant for exchange, then where, when, how, and with whom do we exchange them? Since nobody explicitly buys or sells natural services (not at the scale of Costanza’s numbers), then its value—in economical terms—remains negligible. Of course, government could impose regulations on the buying/selling of natural services, but government is not the most accountable/consistent spokesperson for the environment either. With nobody ensuring the economic success of the environment then a “Tragedy of the Commons” scenario develops, where people exhaust natural capital without understanding its stock.
Unlike Costanza, I do not believe that our problem lies in our inability to quantify the world’s natural capital, but in our tendency to appraise our natural environment with economical terms. Ultimately, we are forcing monetary value on a system that consistently rejects appraisal. For instance, when an economical market dissolves, opportunity arises for new markets to emerge. Yet, when a natural stock is exhausted, it simply dies and is gone forever. In this way, ecosystems are much more fragile than economies.
So why subordinate ecosystems to the language of economics? Instead, why not approach economy through the lens of the environmentalist? Perhaps this is the legacy of Meadows’ Thinking in Systems: to describe mundane, economical processes with the same rigor and complexity (“flows”) of natural processes. Nevertheless, by commoditizing our global ecosystems—and assuming that they can be appraised—we will continue to subordinate our ecosystems to our global economy.
Talking about economies through environmental terms: a great example of this approach is McDonough’s TED talk on Cradle to Cradle design. The last couple minutes, when McDonough is describing an urban design for a Chinese city, exemplifies this notion to describe economic processes in terms of natural processes.
Maps:
Compare Costanza’s global map ecosystem services to NASA’s map of the Earth at night (showing human settlement), and you will find an intriguing set of interrelations.
There seems to be a strong inverse correlation between areas of human settlement and regions of high natural services. Natural services seldom occur near high-density settlements. In fact, high natural value occurs in coastal regions away from human settlement. I am left wondering if natural value has been destroyed in regions of human development or if areas of high natural development (coral reefs, rainforests, etc.) are simply inhospitable to human settlement.
It is interesting to note, though, the belt of high-valued natural ecosystems that circles the globe at the meridian. Additionally, I wonder why the map of global ecosystems does not include the vital natural services that occur underwater…
Sun Dial Challenge 9/10/2010
By my calculations, the sun will align the red pane and the “never” spot twice during the year (on each side of the equinox): on March 15th at 4:52pm and on September 28th at 4:35pm.
Below, I have posted my geometrical calculations for the optimal altitude (27.65degrees) and azimuth (243.119degrees) that align the red pane and “never” spot. I based these calculations on measurements of the stairwell by tape-measure.
Below, I have included screenshots of my three methods of calculation. I used a simple Rhino model (with sun position calculator), an orthographic sun position diagram, and NOAA’s “sun calculator.” Interestingly, my results varied across the three applications (even though I input the same longitude, latitude, date, and time). I have noted their error from my optimal values. Since there is a slight variation between each sun position calculation, the programs must be using different algorithms… It’s strange to think that there isn’t a standardized equation for calculating sun position. Perhaps the slight eccentricities and wobbles of the Earth as it orbits around the sun has resulted in several different algorithms for sun position.
Bay Game Pre-Assessment 9/6/2010
Name: Charles Lee Sparkman III
UVA Email: cs3cj@virginia.edu
Course Instructor: Bill Sherman
I have not played the UVA Bay Game before.
1. List the variables and concepts that you think are part of the Chesapeake Bay watershed system (You can list as many as you would like. Use additional space if needed).
Local Scale Linear Variables:
a.) Pollution, b.) Erosion/runoff, c.) Fishing/trawling (but balanced by growth/life cycle), d.) Density (and type) of coastal developments
Global Scale Linear Variables:
a.) Increasing intensity of extreme weather conditions, b.) Rising ocean level, c.) Rising CO2 emissions
Variables that Seem Nonlinear:
a.) All economy-related nonsense from federal and state funding to private investments, b.) Jobs associated with advocating/protecting/cleaning the bay, c.) Public awareness/sympathy (exhibits a bizarre nonlinear relationship with funding)
Known Cyclical Variables:
a.) Hydraulic cycle, b.) Growth/life cycle of plants and animals (strangely, death is a reinforcing loop — marine snow), c.) Daily patterns of tides, temperature, etc, d.) Seasonal patterns, e.) Extreme weather conditions
2. Describe the relationship and interaction between these variables. Be specific. For example, if you state that A influences B, indicate the direction and nature of the influence (i.e., A transforms B in this way, A increases/decreases B, etc.).
Since I have acknowledged several nonlinear and cyclical variables, a written description of their interaction will be confusing.
By distinguishing types of variables (linear, nonlinear, cyclical), I can better generalize their interactions. In short, nonlinear variables have a direct—often negative—effect on linear variables. Cyclical variables function as the resilience of the system, keep the Chesapeake Bay watershed in a fragile homeostasis.
3. On a separate piece of paper, diagram (either free-hand or with a software program) the variables you described above demonstrating the relationships and interactions that influence the watershed.
Complex Data Visualization in Virtual Space 9/3/2010
Several students have commented on the shortcomings of Meadows’ systems diagrams. Her two-dimensional approach results in muddled diagrams, tangled flows, and obscured interconnections. Likewise, when I emulate Meadows’ way of diagramming, I become bewildered with multi-stock and multi-loop systems whose diagrams approach incoherence.
In my last post, I wrote about the possibility of modeling systems in Grasshopper (Grasshopper already exhibits the structure and syntax systems-thinking). However, Grasshopper’s visual output remains static, as users have to render (or bake) their models to present them. Perhaps a three-dimensional and immersive—even interactive— way of representing systems will result in coherent and dynamic systems diagrams.
At Duke, I completed several research projects on virtual reality environments (the engineering department has a six-sided CAVE system able to project immersive virtual environments).
I worked with a research group exploring methods of visualizing complex data trees in virtual space. For one of our projects, we projected 500+ interconnected data nodes representing technology patents registered in Silicon Valley (see pictures). The blue squares represent patents filed, the green squares represent people, and the red squares represent companies. The lines in between squares represent a company or a person’s involvement in the development of a particular patent.
When a user moved his hand towards a data node, an entire screen of paratext would appear and describe the patent. Additionally, users could manipulate data nodes by “pulling” them out of the tangled web, thus making their interconnections more clear.
Ultimately, by allowing users to explore and interact with a complex, three-dimensional data tree, they were able to gain understanding and insights of the data as well as the connectivity between the nodes within the data structure.
The users who manipulated the data tree in virtual space were able to retain the information and describe—even draw—the tree’s interconnections after a short exposure to the virtual environment. Participants who read the same patent data from a book (much like Meadows’ presentation of data) never exhibited the same knowledge of the system.
In short, a three-dimensional, virtual, immersive mode of representation might benefit the coherence of systems-analysis.
Systems-thinking, Emergence, and Grasshopper 8/31/2010
Meadows’ method of organizing systems into stocks, flows, and interconnections translates directly to Grasshopper’s mode of processing data flows as nodes, inputs, and outputs. Additionally, Grasshopper’s user interface shares an uncanny likeness to many Meadows’ diagrams of complex systems in the Systems Zoo. However, while Meadows’ representation of systems-thinking (through diagrams) is often overwhelming and abstract, Grasshopper’s interface with Rhino lends systems-thinking visual/spatial feedback and a way to visualize fluctuating stocks.
Over the summer, I was faced with the challenge of modeling some 200+ Haussmann-style apartment buildings for a project I am developing on Paris. Instead of modeling the buildings individually, I decided to use Grasshopper. Systems-thinking in Grasshopper allowed me to define the “rules of Haussmannization” (5+ stories, street frontage, interior courtyards, etc.).
The final result—which Meadows might diagram as a stock or cloud—is the virtual representation of a Haussmann structure defined by my parameters.
Just as Meadows suggests that systems-thinking can generate complex systems of emergence from simple rules, my approach to defining the fundamental rules of Haussmannization allows boundless iterations of the Haussmann style.
Donella Meadow’s Thinking in Systems 8/26/2010
Rethinking in Systems: Three Exercises/Explorations
Systems-thinking compromises our habitual “mental models” and asks us to unpack processes into systems of elements, functions, purposes, and interconnections.[i] By understanding a system’s inner-workings, we can better anticipate its traps, opportunities, and means of leverage. However, Meadows also demonstrates systems’ ever-expanding complexity,[ii] for systems are boundless, interconnected, interdependent, and often elude rationalization by systems-thinking.
Nevertheless, according to Meadows’ mantra, I have decided to analyze/rethink three of my own mental models with systems-thinking.
1. The Smooth: Ways of Seeing Random Conglomerations
Meadows begins her primer by distinguishing Systems from Random Conglomerations. She states that Systems are comprised of elements, functions, purposes, and interconnections, and function within an ever-expanding web.[iii] Conversely, Conglomerations seem to exhibit indeterminacy and futility. Meadows states, “Is there anything that is not a system? Yes—a conglomeration without any particular interconnections or function.”[iv] She does not mention conglomerations again until the end of the text, when her description of conglomerations becomes useful for comprehending systems’ ever-expanding complexity.[v]
Since Meadows’ text prompts us to see systems in the most unexpected places, her acknowledgement of conglomerations compromises her approach and leaves little room for the discovery of new systems. The task of systems-thinking lies in ways of seeing, and perhaps the most compelling way of seeing is understanding a Random Conglomeration as a System—the very purpose of science/design/representation.[vi]
My favorite example of ways of seeing occurs in Deleuze and Guattari’s illustration of Smooth and Striated space, which I now appreciate as a catalyst for systems-thinking.
In “1440: The Smooth and the Striated,” Deleuze and Guattari contrast our modern way of seeing the ocean to our knowledge of the ocean at the eve of maritime exploration. The ocean was once a great unknown: distant, boundless, unmapped, unstructured, and malevolent (countless sailors died at sea). Deleuze and Guattari name this pre-condition “Smooth.”[vii] After considerable technological developments in ways of seeing we have inscribed our understanding of the ocean with: oceanography, navigation, and oceanic flows. Thus, the ocean has become “Striated“—quite literally by the latitudes and longitudes of a map.[viii] In Meadows’ terms, the ocean, which was once seen as a Conglomeration is now perceived as a highly complex System. However, the ocean itself did not change. As a system, the ocean remained the same. The only thing that changed was our way of seeing the ocean.
Deleuze and Guattari’s Smooth and Striated offer an important lesson to systems-thinking: that it matters how one sees or represents a phenomenon. Depending on the way we see, a phenomenon can look like a System or a Random Conglomeration. Therefore, discovering ways of seeing a conglomeration lies at the heart of systems-thinking.
2. The System of the Production of Space:
My next exercise is concerned with how Henri Lefebvre’s Production of Space, a process that describes the production of social space can be affirmed, amended, and expanded by systems-thinking. After all, production (of space) implies systems-thinking, so I should be able to critique Lefebvre with Meadows’ terms.
In The Production of Space, Henri Lefebvre posits a triad of social space, a set of three parameters: “conceived space” (the symbolic, ideal space of a map or a plan), “perceived space” (optical, physical, architectural space), and “lived space” (haptic space)—a social space must fulfill the triad to endure.[ix]
Lefebvre makes social space’s interconnections clear: a mutual dependency across the triad. However, I had always assumed—erroneously—that Lefebvre’s triad exists independent of all other triads in producing social space. Additionally, Lefebvre puts the parameters of his triad on equal ground (one parameter is no more important than another). However, Meadows presents a new way to understand Lefebvre’s Production of Space through systems-thinking.
First, Meadows reveals that all systems are interdependent. Therefore, when examining social spaces, a systems-thinker could assume that only a few parameters could produce vast—and interdependent—permutations of social spaces.
Second, Meadows introduces the property of resilience (engendered by parameter hierarchy). Due to resilience, Meadows’ systems stay intact when one of its components fails.[x] Lefebvre, however, insists that his spatial triad does not exhibit the same effect: it dissolves when a parameter is removed. However, if a systems-thinker accepts Meadows’ previous revelation, that all systems are interdependent, then certain parameters hold more significance in the web (see diagram), and the entire system maintains resilience if one parameter disappears.
The implications of systems-thinking applied to The Production of Space allows for the overlapping and weaving of social space such that two social spaces might occupy the same physical space or two physical spaces might share the same ideologies, etc.
3. Diagramming the Creative Process as a System:
In her final chapter, Meadows suggests that systems-thinking ultimately reveals the ever-expanding complexity of our world: a tangled web of systems. This notion of expandability promises stunning complexity in the most mundane, everyday things.
I decided to diagram a system that we experience everyday in studio: the creative process. In studio, the creative process occurs at such regular intervals (a series of design projects every semester), that one can observe—and perhaps predict—the rhythms of design production. I will call the stock of this system “creative potential” (though I am not sure how to measure it).
If creative potential is my stock, then what are the elements, functions, purposes, and interconnections that drive the creative process? Do the same traps, opportunities, and leverage points apply to the creative process? Will an analysis of the creative system yield a structure of ever-expanding complexity? Or, is the creative process best expressed by a random conglomeration?
Sitting at my studio desk, I imagined the interconnections that might drive my creative stock… Of course, my system diagram is inadequate and incomplete, but offers some ways to apply Meadows’ later revelations.
The exercise confirms that systems analysis is boundless as I am sure that many more flows, delays, and feedback loops contribute to my creative potential. Meadows might insist that I should narrow the scope of my analysis and ask simpler questions with a measurable stock.[xi] However, the boundlessness of my question typifies many of the realistic, real-world systems that Meadows tackles.
Nevertheless, many of Meadows’ leverage points apply to my system. With two layers of reinforcing loops, the “success to the successful” phenomenon can produce exponential growth in stock, and explains how the creative potential of an artist grows as he builds upon his past experiences.[xii] Meadows’ leverage point of Self-Organization, too, enables a kind of designer who adapts his creative process to a specific purpose or goal.[xiii] Additionally, Meadows’ leverage point of Transcending Paradigms characterizes a designer with no attachments or disposition towards any creative process—a curse and a blessing.[xiv]
If I were to add more flows to my system (flow of emotions, financial resources, etc.), I imagine that my system would soon be indecipherable or incoherent—if it isn’t already. With increased complexity, my system for determining creative potential becomes irrational and nonlinear. At this critical point, it might be described as a Random Conglomeration with no purpose or function, thus revealing the “mobius-spiraling negativity”[xv] between Systems and Random Conglomeration. Or, like Deleuze and Guattari’s ocean, we have not yet found the correct way to see the creative process so that we may formulate an appropriate system.
[i] Donella H. Meadows, Thinking in Systems: A Primer (White River Junction, Vermont: Chelsea Green Publishing Company, 2008), 11.
[ii] Meadows, 181-182.
[iii] Meadows, 181-182.
[iv] Meadows, 12.
[v] Meadows, 167-168.
[vi] In my third exercise, I discover that conglomeration is still an adequate model for the creative process.
[vii] Gilles Deleuze and Felix Guattari, “The Smooth and the Striated,” in A Thousand Plateaus: Capitalism and Schizophrenia, translated by Brian Massumi (Minneapolis: University of Minnesota Press, 1987), 476.
[viii] It is important to acknowledge that the complete complexities of the oceanographic system are still unknown. Smooth and Striated are not binary, they are a gradient. Therefore, a space can never be completely striated and a system never completely understood. Deleuze and Guattari, 476.
[ix] Henri Lefebvre, The Production of Space, translated by Donald Nicholson-Smith (Malden, Massachusetts: Blackwell Publishing, [1974] 1991), 50.
[x] Meadows, 16.
[xi] Meadows, 181-182.
[xii] Meadows, 126.
[xiii] Meadows, 159.
[xiv] Meadows, 164.
[xv] Jean Baudrillard, Simulacra and Simulation, translated by Sheila Faria Glaser (Ann Arbor: University of Michigan Press, [1981] 1994), 16.
Systems, Sites and Building (Sparkman) 