The 17 cognitive biases that screw up your decision-making process
Knowing these cognitive biases won't save us, but not knowing them is surely worse.
The scientific study of cognitive biases has roots stretching back decades, most famously to the Nobel Prize-winning work of psychologists Daniel Kahneman and Amos Tversky in the 1970s and 80s.
Their research, later wildly popularized in Kahneman's book “Thinking, Fast and Slow”, established that human reasoning is systematically and predictably flawed.
These biases have been observed in courts, hospitals, investment firms, companies, teams, hiring panels, and family dinner tables.
They affect experts more than novices in some cases, because experts are more convinced that they are immune to them.
Cognitive biases run the show and they make you think you’re in charge.
Here are the 17 you need to know.
Anchoring bias
The first number you hear becomes the reference point for everything that follows, even when it’s arbitrary.
Whoever speaks first in a negotiation sets the invisible ceiling and floor for everyone else.
Availability heuristic
We overestimate how likely something is based on how easily we can recall an example. Plane crashes feel more dangerous than cars because they make the news.
The math says otherwise.
Bandwagon effect
Beliefs spread like contagion. The more people hold an opinion, the more likely we are to adopt it, regardless of evidence.
Blind-spot bias
We are excellent at spotting biases in others, but terrible at seeing them in ourselves. In fact, the more cognitively sophisticated we are, the better we become at rationalizing our own flawed thinking.
Choice-supportive bias
Once we’ve chosen something, we start remembering it as better than it was. This is why we defend bad purchases, or mediocre restaurants we picked, and people we've hired.
Clustering illusion
We see patterns in random data. Gamblers call it a “hot streak”, investors call it a “trend”. Basketball players think they’re “hot”. But scientists call it noise: our brains were built to find patterns for survival, even where no pattern exists.
Confirmation bias
We seek out, notice, and remember information that confirms what we already believe, and dismiss everything that doesn't.
Conservatism bias
We update our beliefs more slowly than the evidence warrants. New information exists, but we just don’t care.
People took decades to accept that the Earth was round, despite the proof being right there.
If you’re more of a hidden principles and laws person, here’s Part 1 of my most read series:
Information bias
More data feels like better decisions. We gather information even when we know it won't change the outcome, because gathering more data feels productive.
However, sometimes the most useful move is to (quickly) decide with what we have, and then adjust if it’s not going how we thought.
Ostrich effect
We tend to bury our heads in the sand, avoiding information that could cause us discomfort, as if not looking makes the problem less real.
Outcome bias
We judge decisions by their results, not by the quality of the reasoning behind them.
Overconfidence bias
Most of us rate ourselves as above-average drivers. Most investors believe they’ll beat the market.
A classic example of a miscalibration of subjective probabilities.
Placebo effect
Simply believing something works, makes it work. Some patients given fake pills experience real physiological changes.
Recency bias
Whatever just happened feels most important. The most recent data point drowns out the entire historical record.
This is how people buy high and sell low.
Selective perception
Our expectations filter what we see.
Selective perception is the tendency to not notice and more quickly forget stimuli that cause emotional discomfort and contradict prior beliefs
Survivorship bias
We study successful entrepreneurs and draw lessons without accounting for the thousands who tried the exact same things and failed.
The cemetery of failed startups doesn’t give interviews.
Zero-risk bias
We love certainty so much we’ll pay a disproportionate premium for it. Zero risk bias relates to our preference for absolute certainty. We tend to opt for situations where we can completely eliminate risk, seeking solace in the figure of 0%, over alternatives that may actually offer greater risk reduction (and maybe even greater return).
See you on Sundays 🗓️
Thanks,
Giacomo