12 Laws and Effects Named After People: Where Each Comes From and What the Studies Found

Start herePlenty of ideas travel under a person's name. Here are 12, from online remarks to lab findings, with the first wording we could open and what later work found.

Some ideas get a person’s name attached, and the name sticks. A few began as jokes or quick remarks, two of them online. Others are rules of thumb about how organisations behave, and a few came out of experiments.

Below are 12 of them, grouped by kind. Each card says who the name belongs to, what was first written, what it means in plain words, and what later work found. A “How sure” line says how firm each one is.

01Sayings that began as observations or jokes

Four of these started as quick remarks, not as experiments.

1. Godwin’s law

Godwin’s law says that the longer an online argument runs, the likelier someone brings up Hitler or the Nazis.

Mike Godwin described the law in Wired magazine on 1 October 1994. He wrote that he set out in 1990 to build a “counter-meme”, perhaps to curtail glib Nazi comparisons. He then “seeded” the law in any newsgroup or topic where he saw a gratuitous Nazi reference. His wording: “As an online discussion grows longer, the probability of a comparison involving Nazis or Hitler approaches one.”

A study of 199 million Reddit posts found that, after a certain point, the words “Nazi” and “Hitler” became less likely as threads grew longer. The same study found that threads tended to grow longer once those words appeared, so the comparisons did not end the conversation.

So the comparisons do come up, but in that study they did not keep rising with length. For example, when a debate reaches for a Nazi comparison, you can ask what exact point the comparison is making.

How sure: Limited one large study on one platform, counting selected words rather than reading meaning.

2. Betteridge’s law of headlines

Betteridge’s law says a headline that ends in a question mark can usually be answered “no”.

Ian Betteridge wrote it on his technology blog, Technovia, in February 2009. He called it “my maxim that any headline which ends in a question mark can be answered by the word ‘no’”. His reason was that journalists use the form when they lack the sources and facts to back a story but still want to run it. The idea is older than his 2009 post: for research-paper titles it was called Hinchliffe’s Rule by 1988, and a 1991 Murphy’s Law collection lists it as “Davis’ law”.

A 2016 study of 7,845 titles in academic journals found that questions in titles were rare. Most of those questions were not yes-or-no questions, and the few that were more often had “yes” as the answer.

So the rule was about news headlines, and the one test we found looked at academic titles instead. For example, when a headline asks “Is this the end of cash?”, you can look in the article for the evidence behind the question.

How sure: Limited it is one writer’s maxim, and the study we read covered journal titles, not news headlines.

3. Sturgeon’s law

Sturgeon’s law says most work in any field is poor, so a field should not be judged by its worst examples.

The science fiction writer Theodore Sturgeon wrote “ninety-percent of everything is crud” in his Venture Science Fiction column in September 1957, and repeated it in March 1958 as “Sturgeon’s Revelation”. In its best-known form it reads “Ninety percent of everything is crud.” He was answering critics who, as he put it, used “the worst examples of the field for ammunition”.

Sturgeon’s point was a defence of his own field: the same share of poor work turns up everywhere. For example, before writing off a kind of music or film, you might judge it by its best ten examples.

How sure: Limited it is a writer’s quip, and we found no study that measures the ninety percent.

4. Hofstadter’s law

Hofstadter’s law is a joke that things take longer than you expect, even when you allow for that.

Douglas Hofstadter stated it in his 1979 book Gödel, Escher, Bach: “It always takes longer than you expect, even when you take into account Hofstadter’s Law.” The joke is that the law includes itself, so no extra time ever feels like enough.

Psychologists call a related pattern the planning fallacy: the tendency to underestimate the time a future task will take. In studies published in 1994, people’s predictions of their own finishing times were too optimistic for a variety of academic and nonacademic tasks. In one of those studies, the bias went away when people were told to connect relevant past experiences with their predictions.

The planning fallacy is the serious cousin of Hofstadter’s joke. For example, before guessing how long a report will take, look at how long the last few took. Start from your past times, not from your plan.

How sure: Moderate the 1994 studies found the bias across many tasks, but the fix was tested in one of them.

02Rules about organisations and measures

Three of these describe what happens when people work inside systems and targets.

Two older workplace rules, Parkinson’s law and the Peter principle, have their own cards in Business and self-help rules: where 10 famous rules come from. The line “work expands so as to fill the time available” opens Parkinson’s essay in The Economist of 19 November 1955, but he called it “a commonplace observation”; his law was about the number of officials. The Peter principle comes from a 1969 book by Laurence J. Peter and Raymond Hull.

5. Goodhart’s law

When a measure becomes a target, it stops being a good measure.

The famous sentence, “When a measure becomes a target, it ceases to be a good measure”, is the anthropologist Marilyn Strathern’s, from a 1997 paper on university audit. In that paper she notes that another scholar called the idea “Goodhart’s law”, after Goodhart’s observation on instruments for monetary control. Goodhart’s own 1975 wording, as quoted by Takeda and Ueda, was narrower: “any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes”. We could not open Goodhart’s original.

So the idea started in monetary policy and was later applied to numbers people are rewarded for, such as the university audits Strathern wrote about. For example, a call centre judged only on call length might see shorter calls while problems stay unsolved. It helps to watch what people do to hit the number.

How sure: Limited it began as an observation, and this card does not weigh studies that test it.

6. Campbell’s law

The more a number is used to make social decisions, the more pressure there is to bend it.

The social psychologist Donald Campbell set it out in a 1976 report, Assessing the Impact of Planned Social Change. In his words, as quoted in a 2016 Routledge chapter, the more any quantitative social indicator is used for social decision-making, “the more subject it will be to corruption pressures”. He added that it becomes “the more apt it will be to distort and corrupt the social processes it is intended to monitor”.

So Campbell’s version adds a second worry: the measure can change the activity itself, not only the number. For example, if a team is rewarded only for cases closed, it might pick the easy cases first. A good habit is to ask what the number leaves out.

How sure: Limited it is a widely cited warning from research on evaluating social programmes, not a measured effect.

7. Conway’s law

Teams tend to build systems that copy the way the teams talk to each other.

Melvin Conway made the point in an article called “How Do Committees Invent?”, published in Datamation in April 1968. His thesis was that organisations which design systems “are constrained to produce designs which are copies of the communication structures of these organizations”.

In a 2016 review of 142 studies, the industry and firm studies showed this “mirroring” to be a prevalent pattern, but not universal. Studies of open collaborative projects, most of them on software, did not support it.

So it often holds inside firms, and less so in open projects. For example, if two parts of a product never fit well together, you can check whether the two teams behind them ever talk.

How sure: Moderate a review of many studies found the pattern common, with real exceptions.

03Effects that were measured

These four came from measurements, and later work has tested each one.

8. The Zeigarnik effect

Unfinished tasks were said to stick in memory better; later work points more to a pull to go back to them.

The Zeigarnik effect is the older idea that unfinished tasks are remembered better. The American Psychological Association’s dictionary says it was described in 1927 by Bluma Zeigarnik.

A 2025 meta-analysis found no memory advantage for unfinished tasks, though it did find a general tendency to go back to them. Its authors write that the memory advantage “has proven particularly difficult to replicate”.

The urge to return to an unfinished task has its own name, the Ovsiankina effect. For example, a half-written email may keep drawing you back until you send it. In that pooled review, the pull to finish held up better than the memory boost. More in Pomodoro vs time blocking vs to-do lists.

How sure: Moderate one 2025 meta-analysis pooled the studies, and its authors say the memory effect lacks universal validity.

9. Hick’s law

The more options you choose between, the longer you take, but the time grows slowly.

Hick reported in 1952 on experiments with up to ten alternatives, and found that people took in information at a roughly steady rate. Later researchers describe the law as relating reaction time to the logarithm of the number of alternatives. It is also known as the Hick–Hyman law, after Hick and Hyman’s work on choice reaction time. In everyday words, in the law’s simple form, doubling the options adds roughly a fixed step of time; it does not double the time.

A review calls it one of the few widely acknowledged laws in psychology, and lists what complicates it, including practice and very large sets of choices. A 2020 paper for interface designers argues that the law speaks against, not for, the popular principle that “less is better”. The same paper says the lab task behind the law is rarely relevant to interface work, and that looking at search and decision making is more useful.

So the law is real in the lab, and menus are mostly about how fast people can find things. For example, a long menu sorted in an order people expect can be quicker to use than a short, jumbled one. How easy options are to find matters more than how many there are.

How sure: Strong a long-tested result in the lab; how far it carries to screens and menus is less certain.

10. Fitts’s law

Hitting a target is quicker when it is bigger and closer.

The psychologist Paul Fitts published the law in 1954, from work on quick aimed movements toward targets of a certain size over a certain distance. Nielsen Norman Group sums it up: the time to move to a target depends on how big it is and on how far away it is. A handbook chapter on the law says it is widely used in ergonomics, engineering, psychology and human-computer interaction.

Screen edges help mouse users, because the pointer cannot overshoot them. On touchscreens, one study found that targets placed around the edges took longer to hit.

For example, a large button near where your thumb already rests is quicker to tap than a small one in a far corner. Bigger and closer is quicker, and where to put a button depends on the device.

How sure: Strong a long-used model in several fields, though the details change with the device.

11. Benford’s law

In many real lists of numbers, the first digit is 1 far more often than 9.

In data that follow the law, the leading digit is 1 about 30.1% of the time, rather than the 11.1% you would get if all nine digits were equally likely. Simon Newcomb described it in 1881, after noticing that the first pages of books of logarithm tables wore out faster. Benford studied a wide variety of data sets in 1938.

Many real data sets roughly follow the law, but it is not a universal law for numbers. It is used to look for made-up figures, for example in customs declarations. But researchers note that no general theory can tell in advance whether honest data will follow it.

So a mismatch is a reason to look closer, not proof of anything by itself. For example, in a list of town populations, count how many start with 1. In many such lists, a pile of 1s is normal.

How sure: Strong the pattern is well documented, though it does not hold for every kind of data.

04The law about all of these laws

One last law is about the names themselves.

12. Stigler’s law of eponymy

Discoveries are often not named after the person who first made them.

Stephen Stigler put it as: “No scientific discovery is named after its original discoverer.” His paper appeared in 1980, in the Transactions of the New York Academy of Sciences. In a fitting twist, Stigler named the sociologist Robert K. Merton as the discoverer of his own law.

Two later authors note that the law seems to be true more often than it is false. Benford’s law on this page is one example: Newcomb described the pattern decades before Benford’s study.

For example, when you meet a law named after someone, you can ask who described it first. The name on a law is a label, not always a credit.

How sure: Limited Stigler’s wording says “no” discovery, and later authors read it as true more often than not.

05Where to learn more

• Business and self-help rules: where 10 famous rules come from, with Parkinson’s law and the Peter principle.
• Mental models checked: 15 thinking tools, with more on Goodhart’s law.
• AI benchmarks explained, where Goodhart’s law meets test scores.
• Pomodoro vs time blocking vs to-do lists, with the Zeigarnik effect and the planning fallacy.
• Melvin Conway’s own page for “How Do Committees Invent?”.
• Nielsen Norman Group, “Fitts’s Law and Its Applications in UX”.

06Quick answers

07Use this

08Quick quiz

How we checked this · Last checked November 2026

• Each law is traced to the earliest wording we could open, such as Godwin's 1994 Wired article, Betteridge's 2009 blog post, book passages found through library search, and the original papers or their abstracts.
• Goodhart's law and the Zeigarnik effect use the same sources and wording as our mental models and pomodoro pages.
• Parkinson's law and the Peter principle have their own cards on our business rules page, so they get one line here.
• Poe's law and Brandolini's law were left out, because we could not open a stable first source for either.

How we check every article →