The growing sophistication of the scientific community is a cause for continued hope — if they can accelerate their learning curve, and follow the right path. They no longer mistakenly assume that the facts can “speak for themselves,” and they’ve gotten much better at developing ways to communicate lucidly about complex challenges and uncertainty. But the entrenched denialist, do-nothing opposition is still winning when it comes to writing the checks. If that’s to change, Australian psychologist Stephan Lewandowsky will almost certainty be part of the reason why. Reframing Uncertainty One reason global warming opponents still have the upper hand is basic confusion over the nature and significance of uncertainty. “There are numerous instances in which politicians and opinion makers stated that ‘there is still so much uncertainty, we shouldn’t invest money to solve the climate problem,’” Lewandowsky explained to Salon. Now he has just co-authored two related articles on scientific uncertainty and climate change — “Part I. Uncertainty and unabated emissions” and “Part II. Uncertainty and mitigation” — which show this thinking is completely backwards. “This is shown to be wrong by our analysis, because uncertainty can never be too great for action. On the contrary, uncertainty implies that the problem is more likely to be worse than expected in the absence of that uncertainty.” It’s a simple fact that your typical scientist already knows intuitively: Uncertainty grows with risk, exposure and potential loss, especially with complex nonlinear systems, like the global climate system. In fact, it’s not even possible to calculate how much damage could come from worst-case climate scenarios, as Working Group III lead co-author Christopher Field pointed out at the press conference for their report. The relationship between greater uncertainty and risk is both obvious to those in the know and invisible to those who aren’t. So it’s never been properly talked about — or even rigorously analyzed — until now. “Basically, we tried a new mathematical approach that is called ‘ordinal,’” Lewandowsky said. “An ordinal method allows us to address questions such as: ‘What would the consequences be if uncertainty is even greater than we think it is?’ That is, ordinal questions refer to the order of things, such as ‘greater than’ or ‘lesser than,’ but don’t address absolute questions such as ‘how much.’” So it doesn’t tell you how much worse things will get — which would certainly be nice to know — but it does tell you that they will get worse the more uncertain things are. In short, it gets you oriented in the right direction — 180 degrees away from where so-called “common sense” would take you. It puts you on the right path, asking the right kinds of questions, taking the right kinds of first steps, and avoiding getting lost in the confusion, mistakenly thinking that uncertainty means less to worry about. It’s hard to imagine a more basic finding. “Using that approach we showed that as uncertainty in the temperature increase expected with a doubling of CO2 from pre-industrial levels rises, so do the economic damages of increased climate change,” Lewandowsky continued. “Greater uncertainty also increases the likelihood of exceeding ‘safe’ temperature limits and the probability of failing to reach mitigation targets. Likewise, in the context of sea level rise, larger uncertainty requires greater precautionary action to manage flood risk.” As for the impact on policy, Lewandowsky said, “We show that the adverse effects of uncertainty are ‘leveraged’ and hence amplified by more emissions. It follows that to reduce the adverse effects of uncertainty, we should curtail emissions. This is a pretty strong imperative, but our papers don’t prescribe an exact target for emissions. As I noted above, we cannot answer ‘how much’ questions, we can only say ‘less (pollution) is better.’” Acceptance and Rejection of Science But these two recent papers are only side of the story of what Lewandowsky has been up to. He’s also written a series of papers dealing with how people process information, either rejecting or accepting science. When I asked about the relationship, Lewandowsky replied,”The underlying ‘theme’ — if there is one — is how people respond to uncertainty or ambiguity. What the uncertainty papers analyze is how people should respond to uncertainty if they were mathematically-optimal. What my rejection-and-acceptance work shows is how people actually respond to things they perceive to be uncertain. So the two streams of research are opposing sides of the coin — what reality actually means and how people interpret it.
Posted on: Sun, 20 Apr 2014 20:15:50 +0000
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