Less Is More in Decision Theory
Heuristics are mental shortcuts that often outperform complex calculations. Examples from nature and human behavior show how simple approaches can support effective decisions, challenging the assumption that optimal choices require extensive computation.
THE IDEA
Less Is More in Decision Theory
Simplicity and Steve Jobs: "That's been one of my mantras—focus and simplicity. Simple can be harder than complex: You have to work hard to get your thinking clean to make it simple. But it's worth it in the end because once you get there, you can move mountains." BusinessWeek, May 25, 1998.
Heuristics as powerful—and necessary—shortcuts: Gigerenzer and Brighton (2009) bust the following myth, as presented in The Selfish Gene by Richard Dawkins, in which we find the following about how a baseball outfielder catches a ball: "[H]e behaves as if he had solved a set of differential equations in predicting the trajectory of the ball.… At some subconscious level, something functionally equivalent to the mathematical calculations is going on." Not quite, Professor Dawkins. Gerd Gigerenzer et al. counter by saying that none of that is done. They write the following:
Instead, experiments have shown that players rely on several heuristics. The gaze heuristic is the simplest one and works if the ball is already high up in the air: Fix your gaze on the ball, start running, and adjust your running speed so that the angle of gaze remains constant. A player who relies on the gaze heuristic can ignore all causal variables necessary to compute the trajectory of the ball—the initial distance, velocity, angle, air resistance, speed and direction of wind, and spin, among others. By paying attention to only one variable, the player will end up where the ball comes down without computing the exact spot.
The same heuristic is also used by animal species for catching prey and for intercepting potential mates. In pursuit and predation, bats, birds, and dragonflies maintain a constant optical angle between themselves and their prey, as do dogs when catching a Frisbee.
Additional examples:
To choose a mate, a peahen uses a heuristic: Rather than investigating all peacocks posing and displaying in a lek eager to get her attention or weighting and adding all male features to calculate the one with the highest expected utility, she investigates only three or four, and chooses the one with the largest number of eyespots.
Just like humans. Another example:
To measure the area of a nest cavity, a narrow crack in a rock, an ant has no yardstick but a rule of thumb: Run around on an irregular path for a fixed period while laying down a pheromone trail, and then leave. Return, move around on a different irregular path, and estimate the size of the cavity by the frequency of encountering the old trail. This heuristic is remarkably precise.
Other: Czerlinski and Gigerenzer et al. (1999), Goldstein and Gigerenzer (1999), Gigerenzer (2008).
Makridakis, forecasting, and less is more: Makridakis et al. (1982, 1993), Makridakis and Hibon (2000), Makridakis and Taleb (2009).
Heuristic to measure risks: Taleb, Canetti et al. (2012)—with IMF staff.
When to use it
Choosing a restaurant: instead of reading all reviews, go to the one with the most patrons (social proof heuristic).
Investing: use a simple rule like 'invest in index funds' rather than analyzing individual stocks.
Sports: track a ball using the gaze heuristic rather than calculating trajectory.
Mate selection in animals and humans: focus on a few key traits rather than exhaustive evaluation.
FROM THEORY TO EVERYDAY LIFE
In practice
The Gaze Heuristic in Baseball
Outfielders catch a ball by fixing their gaze and adjusting running speed to keep the angle constant, ignoring all other variables such as wind, spin, and distance.
Peahen Mate Selection
A peahen selects a mate by quickly surveying a few peacocks and choosing the one with the most eyespots, rather than evaluating all traits and calculating expected utility.
Ant Nest Cavity Measurement
An ant estimates the size of a nest cavity by running irregular paths and using the frequency of encountering its own pheromone trail, a simple and precise rule of thumb.
A MOMENT TO REFLECT
Put it to work.
How can you simplify a complex decision by focusing on one key variable instead of weighing all options?
Think of a time when adding more information made your decision worse. Could a heuristic have helped?
In what areas of your life do you overcomplicate things when a simple rule would suffice?
Often confused with
References
- Gigerenzer and Brighton (2009) — Gigerenzer, G. & Brighton, H. (2009)
- The Selfish Gene — Dawkins, R. (1976)
- Czerlinski and Gigerenzer et al. (1999) — Czerlinski, J., Gigerenzer, G., et al. (1999)
- Goldstein and Gigerenzer (1999) — Goldstein, D. G. & Gigerenzer, G. (1999)
- Gigerenzer (2008) — Gigerenzer, G. (2008)
- Makridakis et al. (1982) — Makridakis, S., et al. (1982)
- Makridakis et al. (1993) — Makridakis, S., et al. (1993)
- Makridakis and Hibon (2000) — Makridakis, S. & Hibon, M. (2000)
- Makridakis and Taleb (2009) — Makridakis, S. & Taleb, N. (2009)
- Taleb, Canetti et al. (2012) — Taleb, N., Canetti, E., et al. (2012)
CONTINUE THE CONVERSATION
Source texts
- Antifragile (Nassim Nicholas Taleb)