The book delineates cognitive biases associated with each type of thinking, starting with Kahneman's own research on loss aversion. From framing choices to people's tendency to substitute an easy-to-answer question for one that is harder, the book highlights several decades of academic research to suggest that people place too much confidence in human judgment.
Why talk about this book on this blog? Because it can explain, through the lens of Kahneman's research, biases in our thinking and understanding of extreme weather, flooding and climate change.
Kahneman's research helps explain to how the media, the public, and groups without scientific resources substitute an easy to answer question on meteorology for the harder ones on urban hydrology, infrastructure hydraulics, multi-objective decision making, extreme value statistics and risk assessment. Here are some examples of the biases in thinking:
For example, after the July 8, 2013 storm in Toronto, where 126.0 mm of rainfall was recorded at Pearson Airport, the National Post reported "Before Monday, the highest rainfall ever experienced in Toronto for July 8 was 29.2 mm set in 2008 — a record that was more than tripled". Tripling records sounds extreme when referred to a particular calendar day and anchors perception of rarity - but calendar days statistics are irrelevant given that summer convective storms are uncommon and 2/3 of July days are dry - furthermore daily totals of a similar magnitude were recorded twice before in 1980 and 1954 (119.9 mm and 137.4 mm respectively), and the previous July 8 record was exceeded by 200% in 7 other years between 1950 and 2013. Headlines or course try to emphasize the rarity of events, not the commonplace.
The availability heuristic is a mental shortcut that occurs when people make judgments about the probability of events by how easy it is to think of examples. In the context of extreme rainfall, 24-hour weather broadcasting, and 24-hour new channels give the public many example of flooding events that skew the perceived probability of occurrence. Hurricane Katrina and Hurricane Sandy are examples of extreme flooding that the public can recall in the context of flooding, but that have little relevance to urban flooding caused by convective thunderstorms. Likewise for Tsunamis. Other types of flood events caused in large part by operational issues and inherent vulnerabilities are recalled and mistakenly associated with extreme rainfall as the sole cause (Union Station flooding June 1, 2012 was due to construction pump bypass capacity specifications, GO Train flooding July 8, 2013 due to rail line vulnerability (being below known moderate frequency flood levels)).
|Go Train Flood - Don River Floodplain - July 8, 2013|
|Stranded GO Train in 1981 in same location as the|
stranded GO Train in 2013 in the Don River valley.
|System 2 thinking about flooding must consider rain, runoff, flow and|
flooding processes - a slow, effortful. complex and reliable approach.
As rain first causes runoff, which then creates flow, which then causes flooding, it is easy to mistakenly correlate increased flooding to increased rainfall. The alternative is analyzing the complex problems of urban hydrology changes that influence runoff, the stormwater management mitigation measures that can lessen some impacts of some development at some scales, hydraulic interaction in the flow systems including riverine systems (Lisgar District Basement Water Infiltration Assessment is a wonderful example in Mississauga, or Basement Flooding Areas 4 and 5 in Toronto (see page 4 in the Executive Summary on Black Creek interaction)) with the overland, underground separated, combined and partially separated sewers, hydraulic impacts of operational constraints (bypass pumping during construction, inadequate dredging), hydraulic impacts of environmental protection measures (provincial F-5-5 compliance, federal Fisheries Act compliance, etc.), and hydraulic impacts of development intensification on overland flow routes and interactions with underground systems and private systems. It is much easier to focus only on rainfall. And, conveniently, everyone has an opinion about the weather.
Media support attribute substitution by ignoring even the most fundamental physical facts. For example, the GO Train flood on July 8, 2013 was cited as a 2013 Top Weather Story by CBC News as they associated the record at Pearson Airport with the flooding (record rain somewhere = flooding somewhere else). They ignored the fact that Pearson is in the Etobicoke Creek Watershed, three watersheds away from the Don River Watershed where the GO Train flooded - this is basic hydrology: Mississauga rain = runoff in Etobicoke Creek, not in Don River). They ignored that no record rainfall occurred in the Don River Watershed as they were anchored to the Mississauga data 25 km away.
|System 2 Mode of Thought - Data and Analysis - Slow, Methodical.|
Source: Environment Canada Engineering Climate Datasets ver 2.3.
“There will still be times when someone accuses us of having lost our way, of having chosen the wrong priorities, and I know that can be hard to hear. But in moments in great and important choice, when the stakes are high, and the consequences are long-lasting, we have to test our assumptions.” Premier Kathleen Wynne, AGM, June 6, 2015
|System 1 Mode of Thought - Infographics and Heuristics - Fast, Emotional.|
Source: Environmental Commissioner of Ontario,
Connecting the Dots on Climate Data in Ontario.
Please. More Data.
"People are not accustomed to thinking hard, and are often content to trust a plausible judgment that comes to mind."
Daniel Kahneman, American Economic Review 93 (5) December 2003, p. 1450
Robert Muir's presentation on infrastructure adaptation to the WEAO OWWA Joint Climate Change Committee explores in significant detail the trends in Southern Ontario rainfall extremes that affect flood risk and that drive mitigation priorities: