Social Science and Climate Change: Positive Thoughts.

There are even short articles, maybe a post and a half, that make a bunnies ears twitch and his nose wiggle back and forth while muttering yeah yeah.  In this case a discussion of risk management and decision science by Paul Stern, John Perkins, Richard Sparks and Robert Knox. 

In The Challenge of Climate Change Neoskepticism, sadly not open, the authors define today's neoskepticism as

accepting the existence of anthropogenic  climate change (ACC) but advocates against urgent mitigation efforts on various grounds such as that climate models run "too hot", or are too uncertain to justify anything other than "no regrets" policies as having net benefits.  Mainstream scientists are well aware of uncertainty in climate projections.  But neoskeptics citing it to justify climate inaction marks a shift in focus in climate debates from the existence of ACC to its import and to response options

While the questions may be legitimate the inferences that the neoskeptics draw from them are unjustified.  In particular, they are assuming that risk remains static, but as Stern, et al, point out the nature of climate change is that risk is increasing, and thus the relative risk of catastrophic consequences is growing scarily fast.  Although only implied in the article, it is the nature of things that when risk increases, the central measure will only grow linearly but extreme risks in the wings will increase to a much greater extent.

When applied to climate change risk this means (and here Eli interpolates) that it will first reveal itself through qualitative and quantitative increases in catastrophic events, but that also means that attribution will be more difficult since it is the nature of wing events that statistical treatment of them is hard while on the other hand, shifts in average risks will be both slower and masked by natural variability.

As the article says, people use simple mental models to deal with uncertainty.  The challenge is to provide the public with models that

(i) are factual and not misleading (ii) use a familiar domain to explain the unfamiliar (iii) capture interest and (iv) allow for extrapolation consistent with current science.

Uncertainly has to be acknowledges together with the choices and costs growing from it if action is taken or not.  Stern et al, as Eli, consider procrastination penalties as punishing. 

They offer hypertension as an example.  It can be dealt with through changes in life style or medication or both, but it is a risk the extent of which is not known for any particular person.  While the risk is progressive, there can be catastrophic failures leading to death or disability and the condition is only slowly reversible.

The authors suggest that decision  sciences offer a way of dealing with such risks by

(i) adopting policies that  will perform robustly across various plausible futures (ii) pursuing a variety of policy strategies to increase the likelihood that some will yield good results and (iii) organizing decision making processes for flexibility and responsivenss.

Eli notes that such a response implies that not everything tried will work, and thus chooses better and faster at the cost of cheaper.