Erik's newsletter: Tiny habits, climate change, context, and framing the coronavirus.
Hello from Keystone, Colorado! Here are this week’s insights from 9,000 ft elevation.
Small actions lead to big change, whether getting in shape or fighting climate change
An effective tactic for achieving big goals over the long term is starting with “tiny habits:” small steps toward a goal that are easy to accomplish and build momentum for the long term. Here’s an example from BJ Fogg, who pioneered the approach:
For instance, an IT expert named Sukumar had been trying yearly since the age of 26, with no success, to lose the paunch that he was growing while sitting behind his desk. At age 43, he needed a different way to get started. So, at first, every time he brushed his teeth, he would do two push-ups, then hold a “plank’’ position for just five seconds. Rather than minimize these relatively incremental accomplishments, he celebrated them, which made him happier. Once his habit took root, it grew naturally. Now 51, he does 50 push-ups and a five-minute plank each day. He has lost the paunch, changed his self-image and enjoys his strenuous workouts.
Tiny habits are effective because they eliminate the barriers to getting started on behavioral change, make it easy for the action to become a habit, and, most importantly, create an identity around the behaviors that lead to the goal. Per habits author James Clear:
The ultimate form of intrinsic motivation is when a habit becomes part of your identity. It’s one thing to say I’m the type of person who wants this. It’s something very different to say I’m the type of person who is this.
For example, an external goal may be to run a marathon, but intrinsically that means you need to become a runner.
This method is an effective way to drive individual behavioral change, but its concepts may also be relevant for driving broader improvements in society.
In this Washington Post piece, economist Robert Frank argues that smaller individual actions can combine for bigger impacts on climate change than many experts think.
Many economists and climate activists consider individual actions like buying hybrid cars, sustainable diets, or installing solar panels relatively meaningless to the broader cause, as they don’t add up to the level of impact that larger collective action like government policies could. That skepticism disregards psychology, though.
For one, small actions by one person can easily lead to more from others due to “behavioral contagion.” According to the author, behavioral contagion is “social scientists’ term for how ideas and behaviors can spread through populations like infectious diseases.” In simpler terms, it’s basically how trends spread through populations.
Traditional economic thinking looks at the issue as a case of the “free rider problem:”
For instance, if someone buys a Toyota Prius hybrid — which costs several thousand dollars more than a comparable vehicle with an internal-combustion engine — and no one else does, there’s no discernible effect on overall emissions. She has spent the extra money for no reason. Alternatively, if everyone else buys a Prius but she doesn’t, she reaps the environmental benefits for free. Many solutions to environmental problems follow this logic and would therefore seem to require that we make decisions collectively, not individually.
Behavioral contagion, though, tells us that the effects don’t stop at the one individual’s action. That action likely drives similar behaviors through their social circles.
It’s when we consider the effects of our behavior on our peers, and vice versa, that the consequences of individual decisions to reduce carbon use start to grow in importance. We know, for example, that decisions about car purchases are influenced by the actions of neighbors. In a 2008 study, economists from UCLA and Helsinki examined Finnish records of more than 210,000 vehicle purchases (new and used) from 1999 through 2001. They found that people were 12 percent more likely to purchase a car on a given day if one of their 10 nearest neighbors had purchased one during the preceding 10 days.
Just like a tiny habit of two push-ups doesn’t feel like it will make a significant impact to health goals, one person buying a hybrid vehicle doesn’t feel like it will save the world from climate change. When someone in that person’s social circle subsequently buys one, and then someone in theirs does, and so on and so on, it starts adding up.
That effect is compounded by the fact that those small actions create an identity of sustainability in each person that is important for broader change:
Over time, taking small steps to lower your carbon footprint forges the general habit of behaving in a climate-friendly way. And the development of that perspective is a crucial step toward greater political engagement on the issue. Conscious consumption is neither “irrelevant” nor merely a way to advertise our virtue. It creates cascading changes in social behavior, as well as deeper changes in how we view the world. Conscious consumption serves ultimately as a way to build citizens who favor strong climate legislation, who write checks to politicians willing to take up the cause and who knock on doors to help those politicians get elected.
Larger collective action is much easier to accomplish when the people making up that collective have already built an identity of relevant activism through their own behaviors and habits.
We naturally gravitate toward big actions and gloss over the smaller steps needed to get there. Start small to go big.
Behavior is highly contextual. Knowing that context is crucial to impact.
I enjoyed this piece by Natasha Ouslis on “Dollar Store Behavioral Economics” and especially loved this example of both how contextual behavior is and how important basic primary research is.
In one of Robert Cialdini’s most famous studies, he and other researchers tested messaging encouraging hotel guests to reuse their towels rather than have room service bring fresh ones each day, which is a much more sustainable practice. They found that by prompting guests to do so with a social norms message (“Almost 75% of guests who are asked to participate in our new resource savings program do help by using their towels more than once”) instead of an environmental one (“You can show your respect for nature and help save the environment by reusing your towels during your stay”), the rate of reusage increased by 26%.
While this was effective in American hotels, German ones were a different story:
…the classic social proof nudge increased the number of hotel guests in America who reused their towels. When researchers in Germany replicated it, the nudge didn’t work.
Why? Turns out, towel reuse was already 70-80%, so a social norm of “75% of people reusing their towels” wasn’t a surprise to Germans. To Americans, who reuse towels less than 40% of the time, this was a big deal.
I like this example for two reasons.
For one, it shows how contextual behavior is. While studies from the behavioral sciences may identify heuristics and biases that apply to the majority of decisions, there will still be a significant number of situations in which they don’t. People are fickle and their decision-making is constantly altered by any number of personal, environmental, or social factors.
Second, it shows the importance of laying proper groundwork for behavioral interventions. If German hotel guests are already reusing their towels at a high rate, what’s the point in trying to nudge them further? The time would have been better spent tackling other problems. Whether you’re trying to solve problems in business, social issues, government, or even personally, take the time to understand the baselines and context of the issue. A little bit of homework ensures you spend your time on areas with higher potential for impact instead of insignificant improvements on the margins.
Data is only as objective as its framing.
In one of Amos Tversky and Daniel Kahneman's famous studies, participants were given the following scenario:
Imagine that the U.S. is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Two alternative programs to combat the disease have been proposed. Assume that the exact scientific estimation of the consequences of the programs is as follows:
If Program A is adopted, 200 people will be saved.
If Program B is adopted, there is a one-third probability that 600 people will be saved and a two-thirds probability that no people will be saved.
Which of the two programs would you favor?
Consider which option you’d choose. Now, look at two more options:
If Program C is adopted, 400 people will die.
If Program D is adopted, there is a one-third probability that nobody will die and a two-thirds probability that 600 people will die.
Which of the two programs would you favor?
Now, which would you choose?
Well, in case you didn’t notice, all four options have the same expected value: 200 lives saved and 400 lives lost. What’s different is how that outcome is framed. In the first pair of choices - the “positive” frame - 72% of respondents chose option A. In the second pair - the “negative” frame - 78% chose option D.
I thought of this study reading the various statistics describing the coronavirus. The same data can be alarming or comforting depending on its framing. For example, in the New York Times:
The virus had killed about 1,100 worldwide and infected around a dozen in the United States. Alarming, but a much more common illness, influenza, kills about 400,000 people every year, including 34,200 Americans last flu season and 61,099 the year before.
That seems pretty harmless and makes me glad I got my flu shot. However, if I think about it further, it’s probably not a good comparison, as the coronavirus is new and still spreading, while the flu has decades of data quantifying its risk.
So, how much can this virus spread? From The Atlantic:
Lipsitch predicts that, within the coming year, some 40 to 70 percent of people around the world will be infected with the virus that causes COVID-19.
Umm…yikes. That sounds bad! However:
But, he clarifies emphatically, this does not mean that all will have severe illnesses. “It’s likely that many will have mild disease, or may be asymptomatic,” he said. As with influenza, which is often life-threatening to people with chronic health conditions and of older age, most cases pass without medical care.
Okay, that sounds less alarming. The article also states:
The disease (known as COVID-19) seems to have a fatality rate of less than 2 percent—exponentially lower than most outbreaks that make global news.
Again, that sounds reassuring. However, I could easily take those numbers and make them much more alarming.
Taking the lower bound of the estimated infections from above, 40% of the world - roughly 7.8 billion people - at a 2% fatality rate would mean something like 62 million deaths. That sounds pretty terrifying!
With coronavirus spreading, we’re all trying to grasp its potential impact and what we should do to avoid it. As you find data and information on the virus, consider its framing. Is the author trying to alarm or comfort you? What context may be missing? Also, remember that any data we have on it is new and not necessarily reliable. There’s a lot of unknown here, so the best we can do is stay informed, consider the limitations of that information, and take precautions without panicking.
See everyone next week.
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