- Current research questions
- July 10th, 2010
The multiple purposes of scenarios: I'm mainly interested in scenarios for the range of things they can accomplish. From a recent abstract: Scenarios are a suitable platform for situation-specific, user-generated annotations of institutional processes. Scenarios achieve this suitability by allowing participants to arbitrate between different value choices in the context of relevant narratives. Scenarios also facilitate change, as they are able to present plausible speculations juxtaposed with the existing narratives, preparing participants for shifts otherwise obscured by past results. As a result of their direct engagement with the situations of participants, scenarios also provide a meta-theoretical criteria for the applicability of various theories of change to the particular context.
Eliciting causal impacts: Right now I'm working on questions of how does even one appropriately elicit scenarios for governing risky situations with multiple stakeholders, when the participants potentially have all kinds of differences in their worldview. (This has stemmed from my research methods projects, and I'm very exited about this, and am writing a paper and software tools now). A related question is how does one represent and visualize the conflicting accounts emerging from the testimony of multiple stakeholders?
Rendering causal impacts, emerging changing behavior: How do you aggregate nearly insignificant small-scale individual choices into long-term, large-scale, high-impact behaviors in a way that's useful for making situational decisions? For example, how to do map a particular purchase as an exemplar of larger-scale trajectories of materials, energy, and waste? As another example, how do you map a given meal choice on to the nutrition and fitness of a region? And how do you render that information in a manner that makes it immediately useful?
Emerging cradle-to-cradle: One interesting special case of this is the emerging cradle-to-cradle problem. What's the minimum amount of information one needs to capture to make emergent cradle-to-cradle behavior feasible? Cradle-to-cradle issues interest me quite a bit, because of the temporal effect on values: no matter the social values a given society might determine is appropriate, using up a resource thermodynamically will affect future societies with different social arrangement. This leads to some frighteningly easy decision-theoretic planning perspective: non-discounted marginal loss spikes to
Making causal information "portable": Even beyond representing causal information in the first place, I think there are some challenges in making it "portable". Everyone knows there are active volcanos in Iceland, yet nobody can be practically expected to use that information to assist their business travel planning. How to do you pull in what you already "know"? Also, how does one assemble this common knowledge? Can it be mined from text?
Design from the perspective of statistical processes: How do you know when your understanding of potential causal forces is complete enough? I think that design and ethnography teach us to look further than we otherwise might, and there could be interesting discoveries in how design works from a statistical perspective (similar to recent work in cognitive developmental psychology and the psychology of science). In particular, it may have some interesting things to say about the validation of foresight work.
Making design and diagrams "portable": I think of design as being very project-driven: you try a bunch of things, you finish one of them to completion, and then you take whatever you learn, but the models that you often build end up in the trash. In machine learning, there's a problem called "transfer learning", where you ask given that you know one kind of statistics, what can you infer about a different relationship. There's possibly a design analog, where after you've illustrated one set of relationships, how do you (or somebody else) recover those connections for a different project?