## Design as a Multi-Scale Network, Risk as Network Structure

Seed idea: Can modeling a design project as a network provide underpinnings to better estimate risk and sequence problem solving? With connections to multi-scale systems, Alexander's idea of an unfolding process, and thin vs. fat-tailed variables.

**Part 1: 00:12**

Network theory, multi-scale networks, example of building a clustering feature on a side project, two scales of design: the feature level and the implementation level

Mentioned:

- Barabasi's work on Network Medicine
- Harry Crane's Probabilistic Foundations of Statistical Network Analysis
- "More is different" is the title of an article by P.W. Anderson

**Part 2: 13:54**

Unfolding as a network dynamic, learning at the fine scale under constraints from the large scale

Mentioned:

- Christopher Alexander describes unfolding processes in Book 2 of the Nature of Order

**Part 3: 20:05**

Risk, thin-tailed vs. fat-tailed variables, how underlying structure gives rise to different shapes of distributions, orthogonality and interdependence

Mentioned:

- Nassim Taleb. See Probability, Risk, and Extremes (PDF) on thin vs fat-tailed variables. Re: the relationship between distributions and underlying structure: "... we cannot rule out that it is not fat tailed
*unless we understand the process*." (emphasis added)

**Part 4: 30:14**

Patchiness of risk in a design problem, observation in science vs. active control in design, targeting unknowns, redesigning at the feature scale based on information from the implementation scale, example of designing for independence

**Part 5: 38:35**

Scopes in Shape Up as tangled network neighborhoods, structure vs. opacity in the network, alternation between identifying structure and removing "the fog"

Mentioned:

- Scopes are explained in the Scope Mapping chapter of Shape Up