Joachim Andersen

Accelerated Learning

Hanlon’s Razor: Don’t Assume Malice When a Mistake Explains It

A vintage straight razor with a dark horn handle on a walnut desk at night beside a tipped over crystal inkwell spilling black ink across a handwritten letter, with a fountain pen, tortoiseshell glasses and a brass desk lamp
Spilled ink is usually an accident, not an attack.


Hanlon’s razor is a rule of thumb for judging other people’s behavior: “Never attribute to malice that which is adequately explained by stupidity.” I read “stupidity” generously. It covers carelessness, ignorance, fatigue, bad tools and broken processes, the ordinary ways in which well-meaning people and systems get things wrong.

The essence of Hanlon’s razor is to ask: “Before I decide someone did this to me on purpose, is there a simpler explanation in a mistake?”


Origin: A Joke Book Entry That Stuck

The adage got its name in Arthur Bloch’s Murphy’s Law Book Two: More Reasons Why Things Go Wrong! (1980), a collection of jokes in the spirit of Murphy’s Law. It was credited to Robert J. Hanlon, a reader who submitted it, and the name was a nod to Occam’s Razor. It spread widely after it was added to the Jargon File, a glossary of programmer slang, in 1990.

The idea is much older than the name. In Robert A. Heinlein’s 1941 novella Logic of Empire, a character warns against the “devil theory” and says: “You have attributed conditions to villainy that simply result from stupidity.” Some even suspect “Hanlon’s” razor is a corruption of “Heinlein’s”. In 1943, Winston Churchill wrote to King George VI that Charles de Gaulle’s insolence “may be founded on stupidity rather than malice”. I have also included it in my short overview of philosophical razors, but it deserves a closer look.


Key Concepts

  • A Razor, Not a Law
    Like other razors, it shaves away unlikely explanations. It does not prove that nobody acted in bad faith. It tells me which explanation to check first.

  • Base Rates Favor Error
    Mistakes are far more common than plots. Most people are busy, distracted and working with imperfect information, and a deliberate scheme takes more effort and coordination than an accident.

  • Systems Fail Without Villains
    Many of the worst outcomes come from processes, interfaces and old defaults that nobody designed to do harm. Blaming a person often hides the real cause.

  • Charity as a Starting Point
    The razor is close to the principle of charity: interpret others in the most reasonable way first, then update if the evidence points elsewhere.

  • The Mirror of a Known Bias
    It’s a practical antidote to the Fundamental Attribution Error, our habit of explaining other people’s behavior by their character instead of their situation.


Some Examples

  • Thirty-Eight Minutes of Terror
    On January 13, 2018, phones across Hawaii received an alert: “BALLISTIC MISSILE THREAT INBOUND TO HAWAII. SEEK IMMEDIATE SHELTER. THIS IS NOT A DRILL.” It took 38 min before a correction went out. There was no missile and no hacker. During a shift-change drill, a supervisor deviated from the script and said “this is not a drill”, an employee believed the threat was real, and the interface let him choose “missile alert” instead of “test missile alert”.

  • A Command That Unplugged Facebook
    On October 4, 2021, Facebook, Instagram and WhatsApp disappeared from the internet for six to seven hours, and speculation about an attack spread quickly. The company’s own explanation was mundane: during routine maintenance, a command meant to assess backbone capacity accidentally took down every connection in its backbone network. As the engineers put it, the outage was caused “not by malicious activity, but an error of our own making”.

  • The Security Update That Crashed the World
    On July 19, 2024, a faulty configuration update to CrowdStrike’s Falcon security software crashed roughly 8.5 million Windows computers, grounding flights and disrupting hospitals and banks. With so much down at once, a cyberattack seemed likely to many, but CrowdStrike stated that it was a logic error in its own update and “not the result of or related to a cyberattack”.

  • The Missing Covid Cases
    In October 2020, nearly 16,000 positive Covid-19 cases in England went unreported, which delayed contact tracing. It looked like the kind of thing someone might hide. The BBC found the cause was far more ordinary: Public Health England had used the old XLS spreadsheet format, which holds only about 65,000 rows, so new results were simply cut off.

  • Genes Renamed to Please a Spreadsheet
    A 2016 study of genetic data shared with 3,597 published papers found that roughly one in five lists had been corrupted by Excel automatically turning gene symbols such as SEPT1 and MARCH1 into dates. There was no fraud, only default settings. In 2020, the HUGO Gene Nomenclature Committee renamed 27 human genes, so that SEPT1 became SEPTIN1 and MARCH1 became MARCHF1.


Applying Hanlon’s razor

When I feel that someone has wronged me on purpose, this is the simple process I follow:

  1. Pause Before the Verdict
    I notice the jump to “they did this on purpose” and try to give myself time before I reply, especially in writing.

  2. List the Boring Explanations
    I write down a few innocent causes: they did not see the message, misunderstood it, were overloaded, or used a tool that behaves in an unexpected way.

  3. Ask, Don’t Accuse
    I ask a neutral, curious question, such as “I noticed this, can you help me understand what happened?” It usually costs me nothing and saves the relationship.

  4. Fix the System, Not Just the Person
    If the mistake could happen again, I look at the process, the defaults and the interface, the way Hawaii changed its procedures after the false alarm to require two people to send any alert.

  5. Update on Evidence
    If the same harm keeps happening, always in someone’s favor, I let go of the charitable explanation and look at the incentives instead.


Pitfalls and Limitations

  • Malice does exist. Fraud, phishing and sabotage are real, and attackers often rely on people assuming an innocent mistake. In security, finance and safety-critical work, I verify before I trust.

  • Repeated incompetence still causes harm. A popular twist known as Grey’s law says that “any sufficiently advanced incompetence is indistinguishable from malice”. Not assuming malice does not mean accepting the damage.

  • It can be exploited. Some people deliberately do a poor job so that others take over the work. Being charitable once is wise, but patterns matter.

  • The word “stupidity” can sound harsh. The point is not to look down on people, but to remember that smart people make mistakes too, including me. I try to apply the razor to my own errors with the same generosity.


Related Mental Models

Hanlon’s razor reminds me that most of the frustration I meet in daily life comes from mistakes, not enemies. By checking for error before assuming intent, I keep my relationships intact, fix the real causes faster, and save my suspicion for the rare cases that truly deserve it.



To learn more about mental models and philosophy,
check out: Wise: How to Attain a Deep Understanding of the World, History, Our Place in It, and How to Live Well



📚 Sources and References