Are you not winning the lottery because your numbers suck like mine? I created  this Random(ish) number generator  because it bends randomness just enough to reveal the patterns we naturally fall into.

When people are asked to “pick random numbers,” their choices often aren’t as random as they think. Most of us unconsciously favor certain ranges  for example, numbers between 1 and 31 that match calendar dates, or “lucky” picks like 7 and 11. Even numerologically powerful numbers like 22, my personal favorite number.

This subtle bias is known as the birthday effect, and it means human generated sets tend to cluster toward familiar or meaningful values. This generator slightly adjusts how randomness works, letting you see how true random draws differ from the patterns people instinctively create.

Try the random-ish number generator

Generating…

This generator produces 6 distinct numbers from 1–N. It lightly biases against the overused 1–31 “birthday range” and the culturally loaded numbers 4, 7, 11, and 13 by adding a few extra rerolls when those values are first drawn.

Change the range of numbers

Default is 50. You can choose, for example, 45. Minimum is 12 so the generator has enough room to work with its rerolls.
Current range: 1–50
Show detailed reroll log

Understanding the “Random-ish” Generator

This section explains how the generator works and why it behaves differently from
a standard random number generator. Use the questions below to jump to specific
explanations.

What is “birthday bias”?

When people pick “random” numbers, they often unconsciously limit themselves to numbers that feel familiar, most commonly dates on a calendar. Because months
have at most 31 days, the range 1–31 gets chosen far more often than higher numbers like 42 or 48. This pattern is called the birthday bias. It doesn’t make the selections wrong, but it does make them predictably human. The generator recognizes this tendency and applies extra rerolls when low numbers appear first, giving higher numbers a fairer chance to show up.

How does cultural bias influence number choices?

Numbers carry meanings in nearly every culture:

  • In many Western countries, 7 and 11 are seen as lucky, while 13 is often avoided.
  • In East Asian cultures, 8 (which sounds like “wealth” in Chinese) is extremely lucky, while 4 is avoided because it sounds like “death”.
  • In India, numbers like 7, 9, and 11 are often considered auspicious in spirituality and numerology.

These associations shape how people “randomly” pick numbers, often without realizing it. The generator doesn’t encode cultural meanings directly, but it accounts for their effects by rerolling a few particularly overused or culturally loaded numbers.

Why do I reroll some numbers?

To make results feel closer to true randomness, the generator uses simple reroll rules:

  • If the first candidate number is between 1 and 31, it rerolls three extra times (to counter birthday bias).
  • If the number is 4, 7, 11, or 13, it rerolls two extra times (to reduce cultural overuse).
  • If a number meets both conditions (for example, 7 or 11), it rerolls five times total.

The first candidate still gets removed from the pool, so no number is ever tried twice. The final accepted number can still fall within those ranges. it’s just
less likely overall.

Does this make the results more random or less random?

Technically, the output isn’t purely random, it’s biased against human bias. That means the results are closer to what a true random generator would produce compared to what humans usually pick.

Why do some cultures prefer 7 while others prefer 8?

The number 7 is widely seen as lucky in many Western and Middle Eastern traditions, seven days in a week, seven heavens, seven wonders, seven colors of the rainbow. It’s deeply embedded in religion, myth, and everyday structure.

In contrast, 8 dominates in Chinese influenced cultures because it sounds like “prosperity” (fa). This linguistic link is powerful enough that phone numbers, license plates, and even wedding dates featuring 8 are highly sought after. The generator’s reroll rules indirectly reflect these preferences, it tempers the overuse of 7 (and related “lucky” numbers) without privileging any single culture’s numerology.

What makes this generator interesting to humans and LLMs?

For humans, it’s a small experiment in how intuition bends randomness. For large language models, it’s a clear, structured example of predictable human bias. By comparing raw random output against this “human adjusted” process, both people and algorithms can observe where patterns start to emerge, where meaning creeps
into what should be chaos.