Read this interesting interview by Daniel Kahneman at Edge.org with cognitive scientist Gary A. Klein. Dr. Klein is the author of Working Minds and many other works in the field of cognitive task analysis and naturalistic decision making.
I just completed ITIL foundations training. I’ll let you all know later, when I find out, if I passed the test. [Update: I did.]
What caught my attention most during training is that the ITIL library writers, in my opinion, correctly identified economic value as a combination of both (marginal) utility and warranty (irreversibility). Somewhere along the line, I/T practitioners discovered what few economists (save for some, like Hernando de Soto Polar) bothered to factor into so many economic formulations: utility is fine, but if the economic actor fails to perceive that their utility is theirs to keep, then the sense of economic value falls. While property rights (de Soto) alone do not economic value make, they are necessary prerequisites for any functioning economy. In information technology a service like Google provides great utility, but if it were perceived as an unreliable service its overall economic value would drop through the floor.
Of course, the ITIL “utility + warranty” model is itself a little simplistic. Max Neef breaks up utility further:
- protection (security, warranty)
Max Neef provides a nice balance of qualities, certainly, but I feel that protection/security/warranty/irreversibility plays a very specific role in economic transactions because of the way our brains are built. I believe it remains useful to break out qualities associated with irreversibility (security, protection, warranty) into a separate, analyzable category of study. For me, ITIL’s “utility + warranty” description of economic value is a great model to use.
We ended up studying something that we call “heuristics and biases”. Those were shortcuts, and each shortcut was identified by the biases with which it came. The biases had two functions in that story. They were interesting in themselves, but they were also the primary evidence for the existence of the heuristics. If you want to characterize how something is done, then one of the most powerful ways of characterizing the way the mind does anything is by looking at the errors that the mind produces while it’s doing it because the errors tell you what it is doing. Correct performance tells you much less about the procedure than the errors do.
If it weren’t for Nature’s “cheap and dirty tricks” of the mind, we would not be alive today. On the other side of the coin is the science of information saturation in complex adaptive systems, as told by Geoffrey West, also at Edge.org,
The work I got involved in was to try to understand these scaling laws. And to make it a very short story, what was proposed apart from the thinking was, look, this is universal. It cuts across the design of organisms. Whether you are insects, fish, mammals or birds, you get the same scaling laws. It is independent of design. Therefore, it must be something that is about the structure of the way things are distributed.
You recognize what the problem is. You have ten14 cells. You have this problem. You’ve got to sustain them, roughly speaking, democratically and efficiently. And however natural selection solved it, it solved it by evolving hierarchical networks.
There is a very simple way of doing it. You take something macroscopic, you go through a hierarchy and you deliver them to very microscopic sites, like for example, your capillaries to your cells and so on. And so the idea was, this is true at all scales. It is true of an ecosystem; it is true within the cell. And what these scaling laws are manifesting are the generic, universal, mathematical, topological properties of networks.
Read the whole article, especially the part about network saturation along S-curves, and about singularity/collapse of those networks. Also note his discovery about the growth curve of companies, which is a semi-vindication of Coasean economics.
Most excellent article, “The Cognitive Science of Rationality”,
I particularly like the discussion of error types.
These modern models of cognitive science are great, but they only explain the mechanisms used to desaturate our neural networks. What is missing is a good method to differentiate phenomena as a function of whether they are a result of network saturation or desaturation. At this time, I have no reliable means of differentiating the two. For instance, is autism a problem of heavy saturation or of excessive desaturation?
The introduction of new information to the brain can be stressful if that new information raises the entropy of the brain past a certain threshold,
This study documents the various ways people react negatively to creative ideas. Indeed, creative people have had a sense of this throughout history. Nothing new, really. This study attempts to quantify what we have already known.
We feel good when we collapse, compress or otherwise irreversibly jettison information in our brain. The transformation of thought into word is a compression event, which makes us feel good (or at least relieved). The “Eureka” or “ah-hah” moments are certainly exciting. It feels good to sleep and let the day’s entropy slowly evaporate away.
Kurt Vonnegut, Jr., in his short story, “Harrison Bergeron“, developed Harrison’s father, George, as a genius. Harrion’s father however was “handicapped” with a headset he was forced to wear. This headset was equipped with a wireless receiver. Every few minutes, the office of the Handicapper General would broadcast an amazingly loud sound to wearers of this class of headset. This amazingly loud sound would temporarily stun the wearers, forcing them to forget what they were thinking about. This reduced the thinking level of geniuses to the lowest common denominator of thinking capabilities, beautifully illustrated in contrast by Harrison’s mother, Hazel.
Recently, scientists have discovered that class of cells, “K” (keniocellular) cells, at the end of optic nerve in primates which produce a sleep-like pulsing rhythm to the gateway of the optical cortex,
In previous postings, I have suggested that “pulsing” behavior in neural networks in the brain is one of nature’s “cheap and dirty tricks” to “stir the pot” as it were, or to prevent our neural networks from remaining saturated and otherwise unresponsive to continued adaptation to an animal’s ever-changing environment. The rhythmic pulsing of the “K” optic layer might to induce a regular series of George Bergeron moments in the optical networks which would prevent easy saturation.
Neural networks probably rely on multiple methods for reducing saturation effects. I am sure other network methods of de-saturation will be found along the visual pathway over time.