Big Ideas Little Pictures

Sketchplanations in a book! I think you'll love Big Ideas Little Pictures

Sketchplanations podcast photo of Rob Bell, Tom Pellereau and Jono Hey

Prefer to listen?
Try the podcast

Like Sketchplanations?
Support me on Patreon

Fungible - non-fungible

Fungible goods and non-fungible goods: Examples of fungible goods on the left: money, fuel, and commodities and Non-fungible goods on the right: houses, art, people, used cars

Fungible goods are mutually interchangeable in that, in principle, you could swap in any unit for any other unit of the same type or kind and it would be equivalent. Money is a classic fungible good. A $10 bill is equivalent to any other $10 bill, so if you were to borrow $10 from someone they wouldn't care or expect to get the same $10 bill back.

Non-fungible goods are unique and not mutually interchangeable. Each house, even cookie-cutter houses, is in a unique location, with different neighbours, quirks, and history. Having a print of the Mona Lisa on your wall is not the same as having the original from the Louvre. And swapping people between teams at work, even people with similar experience, will still result in different outcomes.

A nice thought experiment to distinguish fungible and non-fungible goods is to ask if you were to borrow one, would it make a difference if you returned a different one? So if you were to borrow my car, you could return it to me with a different tank of fuel (a fungible good) and it wouldn't make any difference to me. But if you were to return a different used car (a non-fungible good) that would be rather odd.

In case you've heard of NFTs (Non-Fungible Tokens) and would like to understand their flaws and promise better I recommend the NFT Freakonomics episode of the 3-part series What can Blockchain do for you?

Also see, rival and non-rival goods

Published 28 Aug 2022

A weekly sketch by email

Learn something new in a sketch each Sunday

Sketchplanations in a book! I think you'll love Big Ideas Little Pictures

Prefer to listen?
Try the podcast

Like Sketchplanations?
Support me on Patreon

Keep exploring

Survivorship Bias illustration: two analysts observe bullet damage, depicted by red dots, on a fighter plane returning from battle. They propose that heavier armour is added to all aircraft in the most hit areas of the plane. A third onlooker wonders whether this surviving plane tells a different story in that it returned because the most vulnerable areas weren't hit. Maybe heavier armour should be added to those areas?

Survivorship bias

The Law of Diminishing Returns illustration: a chart of broth quality increasing from a lone chef stirring a large pot to eventually decreasing once again as a crowd of chefs get in each other's way and goof off. Standard.

Law of diminishing returns

An unexpected surprise seeing a personal friend in a museum with exact replicas and free gifts

The Rashomon Effect illustration: a smashed bottle and its contents lie strewn on the ground. Each individual present recounts how this happened and their stories are not the same.

The Rashomon effect

Kayak v Canoe illustration: on the left we see a kayak with one person sat with legs stretched out inside the hull with a double-bladed paddle. On the right, 2 people sit in the open canoe, each with a single-bladed paddle.

The two primary temperature scales of Celsius and Fahrenheit side-by-side calling out water freezing, body temperature and water boiling

Fahrenheit and Celsius

So the story goes, as told by Stephen Sigler, Nature May 1989: "The US military studied fighter planes returning from missions to try to improve their survival rate and were considering adding heavy armour to those parts of the plane that tended to show the greatest concentration of hits from enemy fire, until statisticians pointed out the fallacy of that argument. The more vulnerable parts of the plane were those with the fewest hits; planes hit there tended not to return at all. The single most vulnerable part, the pilot’s head, was without serious scar in the sample of planes that returned." It’s easy to draw correlations from what we see in front of us. But what we see usually represents just a small part of what has happened. Focusing on the evidence we can easily see at the expense of that we can’t leads to survivorship bias. To say it another way, when Bill Gates drops out of college and starts Microsoft it might seem like dropping out is a path to success for others too, but that ignores all the dropouts who didn’t create Microsofts and consequently you didn’t hear about. Silent evidence — the evidence that we don’t or can’t easily choose to consider — is a term from Nicholas Nassim Talleb. When trying to discover the veracity of the planes story I enjoyed Bill Casselman’s American Mathematical Society article on The Legend of Abraham Wald. The postscript points to some of the source behind the story including a mention of Stephen Sigler’s letter in Nature quoted above. I covered survivorship bias before, but I like this story so much I thought it was worth doing again.…So the story goes, as told by Stephen Sigler, Nature May 1989: "The US military studied fighter planes returning from missions to try to improve their survival rate and were considering adding heavy armour to those parts of the plane that tended to show the greatest concentration of hits from enemy fire, until statisticians pointed out the fallacy of that argument. The more vulnerable parts of the plane were those with the fewest hits; planes hit there tended not to return at all. The single most vulnerable part, the pilot’s head, was without serious scar in the sample of planes that returned." It’s easy to draw correlations from what we see in front of us. But what we see usually represents just a small part of what has happened. Focusing on the evidence we can easily see at the expense of that we can’t leads to survivorship bias. To say it another way, when Bill Gates drops out of college and starts Microsoft it might seem like dropping out is a path to success for others too, but that ignores all the dropouts who didn’t create Microsofts and consequently you didn’t hear about. Silent evidence — the evidence that we don’t or can’t easily choose to consider — is a term from Nicholas Nassim Talleb. When trying to discover the veracity of the planes story I enjoyed Bill Casselman’s American Mathematical Society article on The Legend of Abraham Wald. The postscript points to some of the source behind the story including a mention of Stephen Sigler’s letter in Nature quoted above. I covered survivorship bias before, but I like this story so much I thought it was worth doing again.

More on these topics

…

…

…

…

…

…

…

…

…

…

…

Buy Me A Coffee