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Self-MasteryJohn List

External Randomizer

Use an outside signal to execute a mixed strategy without human pattern bias

Difficulty
Easy
Time to result
~days to results
Steps
4
Confidence
96%

People are poor random-number generators. Even when asked to produce coin flips, they tend to create too even a split and too few long runs, making their supposedly random behavior predictable. List's solution is to outsource execution to an exogenous signal. Decide the desired frequency first, select an independent signal such as the second hand of a clock, and reserve the corresponding proportion of outcomes for the action. In poker, a player who intends to bluff ten percent of the time can define six seconds on the clock as bluff outcomes and obey the signal when the decision arrives. The mechanism separates strategic frequency selection from biased human execution. It should be used only where a mixed strategy is appropriate, not as a substitute for analysis.

Origin

List explains using a clock's second hand to implement a chosen bluffing frequency in poker.

Core principles

  • 01Humans generate sequences that look random but contain too few runs
  • 02Choosing a frequency is different from executing it accurately
  • 03An exogenous signal is less susceptible to momentary bias
  • 04The action rule must be fixed before reading the signal

How to run it

  1. 1

    Set the frequency

    Determine how often the action should occur based on the strategy. Express it as a proportion before facing the individual decision.

    Pro tip Use a frequency that maps cleanly to the signal.

    Watch out Randomization cannot rescue a bad target frequency.

  2. 2

    Choose an outside signal

    Select a source independent of your preference in the moment, such as a clock's second hand. Ensure it provides enough possible outcomes.

    Pro tip Use a signal that is quick to observe and difficult to manipulate unconsciously.

    Watch out Do not choose a signal you can delay until it gives the result you want.

  3. 3

    Map outcomes in advance

    Assign the correct proportion of signal outcomes to the action and all remaining outcomes to the alternative. Fix the mapping before looking.

    Pro tip For ten percent on a 60-second clock, reserve six specified seconds.

    Watch out Changing the mapping after reading the signal reintroduces bias.

  4. 4

    Obey and audit

    Follow the mapped action each time and periodically compare the realized distribution with the target. Adjust the signal mechanics, not individual outcomes, if execution drifts.

    Pro tip Record enough repetitions to reveal a pattern.

    Watch out Short runs can differ from the target by chance.

In the wild

Randomizing poker bluffs

List says that after deciding to bluff ten percent of hands, he looks at the second hand of a clock. A predetermined part of the clock triggers the bluff; all other positions do not. The clock prevents his own biases from selecting convenient moments.

The player executes the mixed strategy less predictably than by choosing bluff moments intuitively.

Common mistakes

Inventing a random-looking sequence

Human-generated sequences tend to stay too close to an even split and avoid the runs that genuine randomness produces.

Reading before mapping

Seeing the signal before assigning outcomes lets preference influence the rule.

Is it for you?

Best for

Repeated low-stakes decisions where unpredictability matters and a target action frequency can be defined.

Not ideal for

One-off high-stakes decisions or choices that should be made from evidence rather than randomized.

From the transcript

humans are terrible at doing something in a random way

John List · 58:30

i use the seconds hand in a clock to say well if i'm gonna bluff say 10 of the time then i look at the…

John List · 58:30

it's an exogenous machine that is not susceptible to my own biases

John List · 59:00

From the episode

#566: John List — A Master Economist on Strategic Quitting, How to Practice Theory of Mind, Learnings from Uber, Optimizations to Boost Donations, the Primitives of Decision-Making, and How Field Experiments Reveal Hidden Realities

John List