One of the core tools we need to use when we try to understand public policy issues is what underlies them — what are people truly concerned about when they are concerned about a specific issue? One way of approaching such issues is to try to really decompose them into component concerns.
Let’s take an example: why are we concerned about privacy? If we decompose general privacy concerns into their subcomponent parts we might get something like the below causal structure. As we do this exercise we essentially are constructing a hypothesis that can then be refined and tested in different ways.
The reason something like this is helpful is that it serves as a reference class of concerns for any focus grouping or interviews. If you start interviewing and examining without something like this you are likely to end up with just testing a part of the causal tree, and you may not be able to weight concerns in design and product development responses.
You may, let’s say, over-index on confidentiality and miss autonomy and attention entirely.
A few caveats: the reality is that beliefs or concerns are not as clearly structured as this — in most of use these are all related: we are worried about what people know about us because we worry about it being used to distract and manipulate us in ways that weaken our rights. That is not a reason not to examine the causal tree here — because unless we have a hypothesis about the belief structure we are addressing we are likely to end up in what we can call the “propositional fallacy” – the erroneous model in which beliefs are isolated, atomic propositions.
In this model public opinion is modeled as a set of propositions (p1…pN) that are individually unrelated, rather than a network of beliefs that are all related in different ways. Exposing trees like this is a way to start examining belief networks rather than individual propositions. And building these trees allows one to compare both quantitative and qualitative data against a hypothesis.
A tree like this is easy to design in a group exercise, but best prepared by everyone making their own tree without group think before the workshop. The workshop is then additive – everyone’s trees are added and built out with new ideas into as rich a causal structure as possible. That structure should then be translated into questions.
The patterns of public opinion are complex.
Thanks Nicklas, good and valuable approach. I think it is also important to keep the tree ”open”, i.e. to let your inquiry keep developing the taxonomy. Some classes may prove less important once you test them on empirical data. New ones may crop up as you go along. I would, for instance, suggest one other class of attention concerns: that societal attention and effort becomes misdirected into non-productive and wasteful uses.
I agree — these are evolving classes and they are related in different ways — the tree is most helpful to avoid single cause analysis, where a formulaic explanation of a complex phenomenon replaces more nuanced understanding.