thinkfetti

I just concluded several days of intensive, one-on-one training in problem solving with Tim Mezel, a senior problem solver at Albuquerque’s Intel fab. After the first segment of our work together, Tim said, “now you’re getting very dangerous!”

This is a very different - and very positive - read on what it means to be dangerous. Effecting change. Actually solving problems instead of spinning around and around, wringing hands and living with problems. Dangerous to the status quo.

For many reasons, individuals and groups are usually unwilling or unable to let others help them solve problems. This overarching “metaproblem” isn’t going to be solved once and for all, and it’s probably not worth getting depressed about that.

Helping where possible (by being aware of the “metaproblem” and effective in tackling ordinary problems) and moving along when it’s not possible to help (no real need to blame anyone in this case, and it might work out to come back again later) may be a good way to go.

This past week, D. Eric Smith, a resident researcher at the Santa Fe Institute, spoke at my university about the beginning of life on Earth. His talk was compelling, and although his talk was directed at a scientifically-literate general audience including undergraduates and faculty, his background and work betray extensive breadth and depth of thought.

I had an opportunity to talk with Eric earlier in the day about my potential interest in developing an introductory undergraduate course on complexity theory or self-organization. He suggested Jaynes’ book on probability theory as a good starting point for the course, a way to efficiently clear up some misconceptions about design, causality, reductionist approaches in science, and statistical mechanics. It’s been awhile since I have really done math; my undergraduate physics degree from Harvey Mudd and my graduate physics coursework at UC Berkeley were relatively math-intensive, but since 1993 my work has been primarily in qualitative-study-leaning subjects such as music (the quadrivium notwithstanding). So I knew I was going to be in for a challenge.

I checked out Jaynes’ book from our library, and it remains to be seen how far I will be able to work my way through it, but to this point, the effort required is certainly worth it. (I’ll probably end up buying my own copy, so I can write in it…)

The book explores logic and probability theory and connects them (or will connect them) to how we as people work with plausibility. In other words, this book seems to be a bridge between core aspects of science and several important pieces of philosophy and psychology.

The text also is already helping me refine and expand my thinking in other areas, such as in the course I’m teaching on TRIZ, a problem-solving methodology. For example, in formal logic, if A is a proposition, the consequences of the mutual exclusivity of A and not-A are the starting point for a vast exposition and development of powerful tools. In TRIZ by contrast, one of the methods for catalyzing problem solutions is to formulate a so-called “physical contradiction.” Here is an example of a physical contradiction: an object in a particular design situation must be heavy and it must not be heavy. Or a chemical in a particular context must be soluble and it must not be soluble. In other words, the categorical avoidance of contradiction is a starting point for formal logic, but the focusing of a conflict into a contradiction is a starting point for the problem solving heuristics of TRIZ. In Taoism, the idea of contradiction may also be seen to be generative, this time in still another way.

David Weinberger, in his blog, has just posted about a new patent related to faceted navigation (see my earlier post for my initial wishlist). I’m curious to see if/when this trickles down to a publicly available tool.

Choice complicates the decision-making process (that’s pretty close to tautological on one hand, but it’s not so cut-and-dried as it first seems: some constraints lead to more efficient progress to an “end,” but when there are too many constraints, the “end” might be in the wrong spot), but choice is also empowering (if also effort- and time-consuming). I would imagine the “optimal” amount of choice for efficient - and effective - navigation of solution space is going to turn out to be context-sensitive both locally and globally.

I’m sorry for writing on such an abstract level (fleshing this out in writing with concrete examples will have to wait until I have more time available), but I’ve just finished reading Duncan Watt’s Six Degrees, a primer on network science, and as a result, I’m seeing evidence of networks everywhere.

Via Boing Boing, a “periodic table of visualization,” itself a knowledge map — simply roll your mouse over an element to see that method of vizualizing exemplified.

Add this to Edward Tufte’s Visual Explanations, and we’re coming up with lots of ways to communicate visually. If we had this down well enough to employ the optimal (or at least a very good) visualization method whenever we needed it, I think our ability to communicate in print and other document forms would jump to a whole new level.

In the spring, I’ll be teaching (or at least facilitating) a course called “Creativity and Innovation and Interdisciplinary Problem Solving.” It’s a “pilot” course, meaning an experimental course, but I’ll be drawing on materials I’ve used in several other courses I’ve taught.

I’ve just set up the (first try at a) blog for the course at http://nmtdesign.blogspot.com/ because I read on slashdot that Google has released Blogger from beta testing, and I figured this is as good a place to start as any.

The point of the blog is to see if a bunch of networked students in a class about networking can or will initiate some interesting (to me and to them) communication behavior and get some great work done.

What follows is the gist of the course, excerpted from a document I presented several weeks ago to the chairs of the engineering departments:

Intended target audience:

Advanced undergraduate students currently involved in junior or senior design courses or working on other research projects at NMT.

Texts:

V. Fey and E. Rivin, Innovation on Demand: New Product Development Using TRIZ. Cambridge University Press, 2005. (Required.)

S. Savransky, Engineering of Creativity. CRC Press, 2000.

Description for students:

This course will introduce you to the TRIZ framework, an outstanding tool that will enable you to analyze design problems effectively and develop innovative design solutions. TRIZ (a Russian acronym that stands for Teoriya Resheniya Izobretatelskikh Zadach, the Theory of Inventive Problem Solving) was initially developed in the 1940’s but only began being used outside of the former Soviet Union in the 1980’s.

TRIZ is helpful in avoiding design compromises. For example, if we wanted an object to be stronger without being too heavy, a compromise solution might suggest settling for some added strength and some added weight. A TRIZ-generated solution, by contrast, might allow for substantial improvement in strength with no additional weight.

TRIZ can also help an analyst forecast technological development of a product. Insights into what kinds of qualitative changes a system will undergo as it evolves can help engineers and other leaders make strategic decisions about where R&D efforts will be focussed. The tools TRIZ brings to bear on this problem were developed by studying tens of thousands of patents and distilling trends of technological evolution of systems.

During this course we will also examine the more abstract design problem of how to facilitate effective communication between individuals and groups who have differing specialties and who may model problems completely differently from each other. With the many technologies now coming online for realtime communications, there should in principle be many opportunities for engineers, scientists, and other scholars and entrepreneurs to collaborate in spite of their geographical separation. A current NSF-funded project will begin to explore the possibilities and emergent problems of using the cyberinfrastructure (CI) as a collaborative tool for scientists. As part of the NSF program, a seminar entitled “CI in Science” will be attended remotely by graduate students and scientists at several universities in the Southwest including New Mexico Tech. In this course, we will use the “CI in Science” seminar as a case study to study the technical, organizational, and communication-related problems of a complex system.