01
Occam's Razor
When two explanations fit the evidence equally well, prefer the one with fewer assumptions.
example
Your phone won't charge. Is it the cable, the port, the battery, or the charger?
$ ls -la ~/thinking
Thinking
Razors, paradoxes, biases, and laws I keep coming back to.
Razors
[6]Rules of thumb for reasoning about explanations and changes.
02
Hanlon's Razor
Don't assume malice when neglect, ignorance, or misunderstanding explains it just as well.
example
A friend doesn't reply to your message. Did they decide to ignore you, or just get busy?
03
Hitchens's Razor
What can be asserted without evidence can be dismissed without evidence.
example
A supplement is advertised as curing everything, with no studies behind it.
04
Hickam's Dictum
A person can have as many problems as they have symptoms. Sometimes there really are several causes.
example
A patient has a fever, a rash, and joint pain. Is it one rare disease, or three ordinary ones?
05
Chesterton's Fence
Don't tear down a rule or structure until you know why it was put there.
example
You find a strange rule in the codebase and want to delete it. Do you know why it was added?
06
Sagan's Standard
Extraordinary claims require extraordinary evidence.
example
A friend says they had lunch. Another says they had lunch with a ghost. Do both claims need the same evidence?
Paradoxes
[17]Puzzles where sound-looking reasoning leads to a contradiction or an absurdity.
01
The Ship of Theseus
If every plank of a ship is replaced over time, is it still the same ship? A puzzle about identity and continuity.
example
You replace a bike's parts one by one until none is original. Is it still your bike?
02
Achilles and the Tortoise
Achilles gives a tortoise a head start. Each time he reaches where the tortoise was, it has crept a little further ahead. Can he ever overtake it?
example
A fast runner gives a slow friend a 100 m head start. Each time the runner reaches where the friend was, the friend has moved on. Can the runner ever catch up?
03
The Dichotomy Paradox
To reach any destination, you must first cover half the distance, then half of what remains, and so on forever. If that never ends, how does movement ever begin?
example
Walking to the door, you cross half the room, then half of what's left, and so on. How do you ever arrive?
04
Russell's Paradox
Does the set of all sets that don't contain themselves contain itself? Either answer contradicts itself, and it broke naive set theory.
example
A librarian makes a catalogue of every catalogue that doesn't list itself. Should it list itself?
05
Gabriel's Horn
A horn-shaped solid with finite volume but infinite surface area. A finite amount of paint can fill it, yet no finite amount can paint its surface.
06
The Liar Paradox
"This statement is false." If it's true, it must be false; if it's false, it must be true.
07
The Interesting Number Paradox
Every number is interesting: if one weren't, being the smallest uninteresting number would make it interesting.
08
The Barber Paradox
A barber shaves exactly those townspeople who don't shave themselves. Does he shave himself?
09
The Potato Paradox
A 100g potato is 99% water. After drying, it is 98% water. How can it now weigh only 50g?
10
The Paradox of Inquiry
If you don't know what you're looking for, how can you search for it? And if you stumble on it, how would you recognize it?
example
You forget a song's name but remember the tune. You can't search by name, yet you'll recognize it the moment you hear it.
11
The Paradox of the Stone
Can an all-powerful being create a stone too heavy for it to lift? Whichever way you answer, there is something it can't do.
example
Can a superhero who can lift anything build a barbell they can't lift?
12
The Twin Paradox
One twin flies off at near light speed and returns younger than the twin who stayed home. But motion is relative, so why isn't each twin the younger one?
example
Two twins. One stays on Earth while the other flies to a nearby star at near light speed and returns. Which twin is older when they meet again?
13
Zeno's Arrow Paradox
At any single instant, an arrow in flight occupies a fixed position and isn't moving. If it never moves at any instant, how does it move at all?
example
A photo of an arrow in flight shows it frozen in one spot. How can it be moving?
14
The Lottery Paradox
In a large lottery, it's rational to believe any given ticket will lose. Yet it's also rational to believe some ticket will win. Those beliefs can't all be true together.
example
One million tickets, each with a one-in-a-million chance. Can you believe of every ticket that it will lose, and still believe one will win?
15
Jevons Paradox
When a resource is used more efficiently, total consumption often rises, because the lower cost makes new uses affordable.
example
A city replaces its streetlights with LEDs, which use far less power per lamp. Does total electricity use fall by the same amount?
16
The Monty Hall Problem
You pick one of three doors; one hides a car. The host, who knows where it is, opens another door to show a goat and offers you a switch. Should you?
example
You pick door 1. The host, who knows where the car is, opens door 3 to show a goat. Do you stay with door 1 or switch to door 2?
17
Simpson's Paradox
A trend shows up in every group of data, but reverses when the groups are combined.
example
Treatment A beats B for small kidney stones, and it also beats B for large ones. But when both groups are combined, B has the better overall success rate. How can that be?
Biases
[9]Systematic errors in how we judge, remember, and decide.
01
Sunk Cost Fallacy
Continuing something because of what you've already put in, rather than because of what it will return from here.
example
Sitting through a bad movie because you already paid for the ticket.
02
Dunning-Kruger Effect
People with limited skill may overestimate their ability because they can't judge their own performance well. How big the effect is remains debated.
example
After a week of lessons, a new chess player is sure they could beat a grandmaster.
03
Confirmation Bias
Favoring evidence that supports what you already believe and discounting what doesn't.
example
You believe a diet works, so you remember every success and ignore the failures.
04
Survivorship Bias
Drawing conclusions from the visible successes while ignoring the failures that never made it into the data.
example
'Famous dropouts became billionaires.' What about the dropouts who didn't?
05
Anchoring
Letting the first number you see pull every later estimate toward it.
example
A jacket marked down from 200 to 120 feels like a bargain, even if it's only worth 80.
06
Availability Heuristic
Judging how likely something is by how easily examples come to mind.
example
After seeing news about a plane crash, flying feels riskier than driving, though driving is the riskier of the two.
07
Hindsight Bias
Feeling that an outcome was obvious all along once you know how it turned out.
example
After a team loses, everyone says they saw it coming.
08
Fundamental Attribution Error
Explaining other people's behavior by their character, but your own by your circumstances.
example
When someone cuts you off, they're a bad driver. When you cut someone off, you were running late.
09
Base Rate Fallacy
Ignoring how common something is overall and focusing on the specific details, like treating a positive test as proof of a very rare condition.
example
A test for a rare disease is 99% accurate, and yours comes back positive. What are the odds you actually have it?
Laws
[11]Observations about how people, projects, and systems tend to behave.
01
Cunningham's Law
The fastest way to get the right answer on the internet is to post the wrong one.
example
Ask a question online and get silence. Post a wrong answer and get ten corrections.
02
Hofstadter's Law
Everything takes longer than you expect, even when you account for Hofstadter's Law.
example
You plan a project for 2 hours, add a buffer and say 4, and it still takes 6.
03
Gall's Law
A complex system that works has evolved from a simple system that worked. One designed complex from scratch rarely does.
example
Big apps usually start as a small tool that worked, then grow one feature at a time.
04
Parkinson's Law
Work expands to fill the time available for it.
example
A task given a week takes a week. The same task given a day gets done in a day.
05
Conway's Law
Systems tend to mirror the communication structure of the organization that builds them.
example
A company with four separate teams ends up with an app made of four separate parts.
06
Goodhart's Law
When a measure becomes a target, it stops being a good measure.
example
If a call center is judged on call length, agents start rushing customers off the phone.
07
Brooks's Law
Adding people to a late software project often makes it later, because onboarding and coordination add work.
example
A project is late, so you add three developers. The existing team spends weeks getting them up to speed.
08
Sturgeon's Law
Ninety percent of everything is junk, which is exactly why the remaining ten percent is worth looking for.
example
Most apps in a store are forgettable, but the few great ones are worth the digging.
09
Murphy's Law
Anything that can go wrong will go wrong.
example
The one day you skip the umbrella is the day it rains.
10
Peter Principle
In a hierarchy, people tend to be promoted until they reach a role they're not good at.
example
A great salesperson is promoted to manager and turns out to be a poor manager.
11
Pareto Principle
Roughly 80% of effects come from 20% of causes. The numbers are a rule of thumb, not exact.
example
A shop finds that 20% of its products bring in most of its sales.