A new study shows why we are polarized about climate change

Summary: Slowly scientists’ investigations produce insights about the psychological and social dynamics that create our dysfunctional politics. Here is a new study about one of drivers of political polarization, that which keeps us divided (despite our common interests), ignorant (despite the internet), and easily ruled. The specific subject is one of the central political issues of our time, and among the most contentious: climate change.

The essential accessory for the modern politically-active fashionista…

Here is a provocative new study (not peer-reviewed) by blue-chip authors. It’s well worth reading, and reveals much about the polarization that is a defining characteristic of modern politics.

“How People Update Beliefs about Climate Change: Good News and Bad News“

By Cass R. Sunstein, Sebastian Bobadilla-Suarez, Stephanie C. Lazzaro, Tali Sharot.
Excerpt from the preliminary draft posted at the Social Science Research Network.

“People are exposed to a great deal of variable information with respect to climate change. {The footnote cites an example: “Developing a Social Cost of Carbon” (ungated copy) — whose complex and assumption-laden calculations are certainly “variable information”.} …We aim here to investigate two simple questions:

How do people update their beliefs when they receive new information about likely warming?
How do people’s prior attitudes affect their response to such information?

“…We find that people who are doubtful that man‐made climate change is occurring, and unenthusiastic about an international agreement, show a form of asymmetrical updating: They change their beliefs far more in response to unexpected good news, suggesting that average temperature rises likely to be (even) smaller than previously thought, than in response to unexpected badness, suggesting that average temperature rises likely to be larger than previously thought. In fact, we do not find a statistically significant change in their views in response to bad news at all.

“By contrast, people who strongly believe that man-‐made climate change is occurring, and who strongly favor an international agreement to reduce greenhouse gas emissions, show the opposite asymmetry: They change their beliefs far more in response to unexpected bad news, suggesting that average temperature rises likely to be even greater than previously thought, than in response to unexpected good news, suggesting that average temperature rises likely to be smaller than previously thought. People with moderate beliefs about climate change show no asymmetry.

“…The findings have implications for how people will update their beliefs about climate change in particular, and also for beliefs about science, politics, and law more generally. If people receive new information about climate change (as is inevitable), and if it is highly variable (as is predictable), we should expect to see greater polarization. Those most concerned about climate change will be more likely to revise their estimates upwards upon receiving bad news than those who are least concerned. Those who are least concerned about climate change will be more likely to revise their estimates downwards upon receiving good news than those who are most concerned.

“This asymmetry undoubtedly contributes to polarization with respect to climate change, as both alarming and less alarming news comes to people’s attention.”

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The New York Times explains why we don’t understand this

Two of the study’s four authors ran an op-ed in the NYT with this provocative title: “Why Facts Don’t Unify Us” (titles are often written by the NYT staff, not the authors). Here’s an insight about the title by Emanuael Derman (Ph.D. in theoretical physics and a prof of industrial engineering at Columbia; Wikipedia bio)…

“{The} new “information” about climate change is prediction, not fact.”

As Professor Derman said, what the NYT headline calls new “facts” in the study are in fact expert opinions (or model outputs) — accurately described by the authors as “news” or “information”. These are expressions of theory, not “facts” in the usual sense of the word.

The NYT staff is not alone in this confusion of fact with theory; it has become quite common in the peer-reviewed literature — with models’ output often treated as empirical evidence. It’s a category error that can lead even the best research to absurd conclusions.

Essential reading to understand use of quantitative models

For more about our misuse of quantitative models see Emanuel Derman’s Models Behaving Badly: Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life. He’s leading the counter-revolution, fighting the misuse of these powerful tools. After years of model output being regarded as reality, Derman points out that they are metaphors or abstractions; expressions of theory not observations of reality.

Derman explains what models are, debunks the exaggerations claimed for them, and what they can and cannot do. He contrasts models in the physical and social sciences; many of his insights apply to both — and especially so for public policy.

“Models try to squeeze the blooming, buzzing, confusion into a miniature Joseph Cornell box, and then, if it more or less fits, assume that the box is the world itself. In a nutshell, theories tell you what something is; models tell you merely what something is like.“

For More Information

Please like us on Facebook and follow us on Twitter. For more information see The keys to understanding climate change, My posts about climate change, and especially these…

Another perspective on “theory” from an earlier time

The last of the West’s scientist-artists reminds us that there are different routes to knowledge — different epistemologies — other than the reductionism of our scientific method.

“The highest is to understand that all fact is really theory. The blue of the sky reveals to us the basic law of color. Search nothing beyond the phenomena. They themselves are the theory.”

— By Johann Wolfgang von Goethe in his “Theory of Colours” (1810), his rebuttal to Newton’s theory of color.