Question #1: In the past 20 years, the proportion of the world population living in extreme poverty has (A) almost doubled; (B) Remained more or less the same; (C) almost halved.
Question #2: Worldwide, 30-year-old men have spent 10 years in school. How many years have women of the same age spent in school? (A) 9 years; (B) 6 years; (C) 3 years.
The correct answers are C and A. If you got them wrong, you have a lot of company. Across a wide variety of groups worldwide, faced with these and many more questions with factual answers, people do far worse than they would by choosing responses at random.
Which brings us to the next addition to your KJR bookshelf: Factfulness: Ten Reasons We’re Wrong About the World — and Why Things are Better Than You Think (Hans Rosling with Ola Rosling and Anna Rosling Rönnlund, Flatiron Books 2018). Unlike books that rely on cognitive science to explain why we’re all so illogical so often, Rosling focuses on the how of it. Factfulness is about the mistakes we make when data are available to guide us but, for one reason or another, we don’t consult it to form our opinions. Viewed through this lens, it appears we’re all prone to these ten bad mental habits:
- Gaps: We expect to find chasms separating one group from another. Most of the time the data show a continuum. Our category boundaries are arbitrary.
- Negativity: We expect news, and especially trends, to be bad.
- Extrapolation: We expect trend lines to be straight. Most real-world trends are S-shaped, asymptotic, or exponential.
- Fear: What we’re afraid of and what the most important risks actually are often don’t line up.
- Size: We often fall for numbers that seem alarmingly big or small, but for which we’re given no scale. Especially, we fall for quantities that are better expressed as ratios.
- Generalization: We often use categories to inappropriately lump unlike things together and fail to lump like things together. Likewise we use them to imagine an anecdote or individual is representative of a category we more or less arbitrarily assign them to when it’s just as reasonable to consider them to be members of an entirely different group.
- Destiny: It’s easy to think people are in the circumstances they’re in because it’s inevitable. In KJR-land we’ve called this the Assumption of the Present.
- Single Perspective: Beware the hammer and nail error, although right-thinking KJR members know the correct formulation is “If all you have are thumbs, every hammer looks like a problem.” Roslund’s advice: Make sure you have a toolbox, not just one tool.
- Blame: For most people, most of the time, assigning it is our favorite form of root-cause analysis.
- Urgency: The sales rep’s favorite. In most situations we have time to think, if we’d only have the presence of mind to use it. While analysis paralysis can certainly be deadly, mistaking reasonable due diligence for analysis paralysis is at least as problematic.
The book certainly isn’t perfect. There were times that, adopting my Mr. Yeahbut persona, I wanted to strangle the author, or at least have the opportunity for a heated argument. Example:
Question #3: In 1996, tigers, giant pandas, and black rhinos were all listed as endangered. How many of these three species are more critically endangered today? (A) Two of them; (B) One of them; (C) None of them.
The answer is C — none are more critically endangered, which might lead an unwary reader to conclude we’re making progress on mass species extinction. It made me wonder why Roslund chose these three species and not, say, Hawksbill sea turtles, Sumatran orangutans, and African elephants, all of which are more endangered than they were twenty years ago.
Yeahbut, this seems like a deliberate generalization error to me, especially as, in contrast to the book’s many data-supported trends, it provides no species loss trend analysis.
But enough griping. Factfulness is worth reading just because it’s interesting, and surprisingly engaging given how hard it is to write about statistical trends without a soporific result.
It’s also illustrates well why big data, analytics, and business intelligence matter, providing cautionary tales of the mistakes we make when we don’t rely on data to inform our opinions.
I’ll finish with a Factfulness suggestion that would substantially improve our world, if only everyone would adopt it: In the absence of data it’s downright relaxing to not form, let alone express, strongly held opinions.
Not having to listen to them? Even more relaxing.