Allen Downey, in his book Think Complexity, identifies a shift in the axes of scientific models:
Equation-based –> Simulation-based
Analysis –> computation
These new models allow us to not only predict behavior, but to also introduce randomness and give agents more detail than we see in classical approaches like Game Theory.
DARPA and various other government agencies and corporations lead the way in the early years for simulations. And slowly it filtered down through the intellectual strata until some K-12 programs started using NetLogo to teach kids about cell structures, the behavior of gas molecules and emergent complexity. The options at our fingertips still aren’t anywhere near as good as they will be in 5 or so years, but it’s what we have to work with.
Allen goes through several pages of changes in scientific modeling caused by the equation to simulation and analysis to computation shift, you can read it on page 16-22 if you’re curious (the book is free in PDF form).
This brings me around to the other point of my post: humans are horrible at working with complexity for a lot of reasons. One of the biggest I’ve seen so far is working memory. There is too much information, and people can’t sort through it quickly enough. And even when they can, they can’t hold enough of it inside of their heads to make the connections they need to understand their situation and plan out possible contingencies.
The average person can hold 5-9 objects in their working memory at a time, which seriously hinders their ability to figure out large complex scenarios with hundreds of thousands of probabilities. Simulations can work around this by giving you real time feedback on changes in variables while incorporating randomness, but for regular analysis finding ways to “visualize” information seems to work well, more on this in a minute.
Nassim Nicholas Taleb’s Black swan theory represents one of the many articulations of the “Unknown Unknown” categories we have to deal with. They are the side effect of an environment too complex for most people to understand. He used two examples, the 9/11 attack and the mortgage meltdown:
http://en.wikipedia.org/wiki/Black_swan_theory
An example Taleb uses to explain his theory is the events of 11 September 2001. 9/11 was a shock to all common observers. Its ramifications continue to be felt in many ways: increased levels of security; “preventive” strikes or wars by Western governments. The coordinated, successful attack on the World Trade Center and The Pentagon using commercial airliners was virtually unthinkable at the time. However, with the benefit of hindsight, it has come to be seen as a predictable incident in the context of the changes in terrorist tactics
Common observers didn’t think it was possible, however many experts had already considered such a scenario:
http://en.wikipedia.org/wiki/Rick_Rescorla#At_the_World_Trade_Center
After the 1988 bombing of Pan Am Flight 103 over Lockerbie, Scotland, Rescorla worried about a terrorist attack on the World Trade Center. In 1990, he and a former military colleague wrote a report to the Port Authority of New York and New Jersey, which owns the site, insisting on the need for more security in the parking garage. Their recommendations, which would have been expensive, were ignored, according to James B. Stewart‘s biography of Rescorla, Heart of a Soldier.[7]
After Rescorla’s fears were borne out by the 1993 World Trade Center bombing, he gained greater credibility and authority, which resulted in a change to the culture of Morgan Stanley,[7] whom he believed should have moved out of the building, as he continued to feel, as did his old American friend from Rhodesia, Dan Hill, that the World Trade Center was still a target for terrorists, and that the next attack could involve a plane crashing into one of the towers.[8] He recommended to his superiors at Morgan Stanley that the company leave Manhattan. Office space and labor costs were lower in New Jersey, and the firm’s employees and equipment would be safer in a proposed four-story building. However, this recommendation was not followed as the company’s lease at the World Trade Center did not terminate until 2006. At Rescorla’s insistence, all employees, including senior executives, then practiced emergency evacuations every three months.[9]
Feeling that the authorities lost legitimacy after they failed to respond to his 1990 warnings, he concluded that employees of Morgan Stanley, which was the largest tenant in the World Trade Center (occupying 22 floors), could not rely on first responders in an emergency, and needed to empower themselves through surprise fire drills, in which he trained employees to meet in the hallway between stairwells and go down the stairs, two by two, to the 44th floor.[7]
- March 2001 – Italian intelligence warns of an al Qaeda plot in the United States involving a massive strike involving aircraft, based on their wiretap of al Qaeda cell in Milan.
- July 2001 – Jordanian intelligence told US officials that al-Qaeda was planning an attack on American soil, and Egyptian intelligence warned the CIA that 20 al Qaeda Jihadists were in the United States, and that four of them were receiving flight training.
- August 2001 – The Israeli Mossad gives the CIA a list of 19 terrorists living in the US and say that they appear to be planning to carry out an attack in the near future.
- August 2001 – The United Kingdom is warned three times of an imminent al Qaeda attack in the United States, the third specifying multiple airplane hijackings. According to the Sunday Herald, the report is passed on to President Bush a short time later.
- September 2001 – Egyptian intelligence warns American officials that al Qaeda is in the advanced stages of executing a significant operation against an American target, probably within the US.
Likewise, the mortgage meltdown was technically a black swan, but was easily predictable if you saw the pattern of ownership which clearly indicated fraud.
Taleb’s answer to this problem is not to try and predict possible future scenarios, but to simply make yourself more resilient. I don’t disagree with resilience, but I think an expanded approach can be taken here. The flaw that lead to the Black swans was not being able to make connections with information. If we don’t know what scenarios are most likely, we could just as easily end up putting too much effort on defense instead of looking for exponential returns on our resources.
How do we know when we’re looking at a very complex problem? Complex systems tend to be made up of diverse agents with interdependent relationships that change over time. So the question and the answers are changing. The behavior, emotions and motivations of the people in the problem are shifting. The connections between them also change. What does that mean?
For that we turn to Rittel and Webber:
http://www.swemorph.com/wp.html
Ten Criteria for Wicked Problems
Rittel and Webber characterise wicked problems by the following 10 criteria. (It has been pointed out that some of these criteria are closely related or have a high degree overlap, and that they should therefore be condensed into four or five more general criteria. I think that this is a mistake, and that we should treat these criteria as 10 heuristic perspectives which will help us better understand the nature of such complex social planning issues.)
1. There is no definite formulation of a wicked problem.
“The information needed to understand the problem depends upon one’s idea for solving it. This is to say: in order to describe a wicked problem in sufficient detail, one has to develop an exhaustive inventory for all the conceivable solutions ahead of time.” [This seemingly incredible criterion is in fact treatable. See below.]
2. Wicked problems have no stopping rules.
In solving a tame problem, “… the problem-solver knows when he has done his job. There are criteria that tell when the solution or a solution has been found”. With wicked problems you never come to a “final”, “complete” or “fully correct” solution – since you have no objective criteria for such. The problem is continually evolving and mutating. You stop when you run out of resources, when a result is subjectively deemed “good enough” or when we feel “we’ve done what we can…”
3. Solutions to wicked problems are not true-or-false, but better or worse.
The criteria for judging the validity of a “solution” to a wicked problem are strongly stakeholder dependent. However, the judgments of different stakeholders …”are likely to differ widely to accord with their group or personal interests, their special value-sets, and their ideological predilections.” Different stakeholders see different “solutions” as simply better or worse.
4. There is no immediate and no ultimate test of a solution to a wicked problem.
“… any solution, after being implemented, will generate waves of consequences over an extended – virtually an unbounded – period of time. Moreover, the next day’s consequences of the solution may yield utterly undesirable repercussions which outweigh the intended advantages or the advantages accomplished hitherto.”
5. Every solution to a wicked problem is a “one-shot operation”; because there is no opportunity to learn by trial-and-error, every attempt counts significantly.
“… every implemented solution is consequential. It leaves “traces” that cannot be undone … And every attempt to reverse a decision or correct for the undesired consequences poses yet another set of wicked problems … .”
6. Wicked problems do not have an enumerable (or an exhaustively describable) set of potential solutions, nor is there a well-described set of permissible operations that may be incorporated into the plan.
“There are no criteria which enable one to prove that all the solutions to a wicked problem have been identified and considered. It may happen that no solution is found, owing to logical inconsistencies in the ‘picture’ of the problem.”
7. Every wicked problem is essentially unique.
“There are no classes of wicked problems in the sense that the principles of solution can be developed to fit all members of that class.” …Also, …”Part of the art of dealing with wicked problems is the art of not knowing too early which type of solution to apply.” [Note: this is very important point. See below.]
8. Every wicked problem can be considered to be a symptom of another [wicked] problem.
Also, many internal aspects of a wicked problem can be considered to be symptoms of other internal aspects of the same problem. A good deal of mutual and circular causality is involved, and the problem has many causal levels to consider. Complex judgements are required in order to determine an appropriate level of abstraction needed to define the problem.
9. The causes of a wicked problem can be explained in numerous ways. The choice of explanation determines the nature of the problem’s resolution.
“There is no rule or procedure to determine the ‘correct’ explanation or combination of [explanations for a wicked problem]. The reason is that in dealing with wicked problems there are several more ways of refuting a hypothesis than there are permissible in the [e.g. physical] sciences.”
10. [With wicked problems,] the planner has no right to be wrong.
In “hard” science, the researcher is allowed to make hypotheses that are later refuted. Indeed, it is just such hypothesis generation that is a primary motive force behind scientific development (Ritchey, 1991). Thus one is not penalised for making hypothesis that turn out to be wrong. “In the world of … wicked problems no such immunity is tolerated. Here the aim is not to find the truth, but to improve some characteristic of the world where people live. Planners are liable for the consequences of the actions they generate …”
…
How, then, does one tackle wicked problems? Some 20 years after Rittel & Webber wrote their article, Jonathan Rosenhead (1996), of the London School of Economics, presented the following criteria for dealing with complex social planning problems – criteria that were clearly influenced by the ideas presented by Rittle, Webber and Ackoff.
Accommodate multiple alternative perspectives rather than prescribe single solutions
Function through group interaction and iteration rather than back office calculations
Generate ownership of the problem formulation through stakeholder participation and transparency
Facilitate a graphical (visual) representation of the problem space for the systematic, group exploration of a solution space
Focus on relationships between discrete alternatives rather than continuous variables
Concentrate on possibility rather than probability
The morphology grid is somewhat popular for mapping out these types of problems, figure out the “finite states”, the root variables that cause change, and then map them out in a grid format. Mark Proffitt’s Predictive Innovation does a good job of this:
Likewise, Lt. General Paul Van Riper mentions that the best leaders tend to be good at managing complex problems:
FORWARD BASE B 