Pick a Number, Any Number… Did You Guess 27?
Hello everyone, John here! Welcome back to the blog where we make sense of the exciting world of AI. Today, we have a fun and slightly weird story that tells us a lot about how AI actually works. Let’s start with a little game. I want you to pick a number between 1 and 50. Got one? Hold it in your head.
Now, what if I told you that if you asked some of the most powerful AIs in the world to do the same thing, they would probably all pick the exact same number? And that number is 27.
That’s right! Researchers recently did a simple experiment. They asked four of the biggest names in AI to guess a number between 1 and 50. The AIs they asked were:
- OpenAI’s ChatGPT (you’ve probably heard of this one!)
- Anthropic’s Claude
- Google’s Gemini
- Meta’s Llama
And guess what? All four of them, independently, chose the number 27. It’s not a magic trick, and it’s not 42, the famous “answer to the ultimate question” from The Hitchhiker’s Guide to the Galaxy. So, what’s so special about the number 27?
Is 27 the Secret Favorite Number of Our Future Robot Overlords?
It’s easy to jump to spooky conclusions. Is this a secret AI code? Are they communicating with each other? Is 27 the first step in their plan for world domination?
Thankfully, the answer is no! The real reason is far less science-fiction and much more interesting. It all comes down to something called training data.
Lila: Wait, John. You’ve mentioned that term before, but what exactly is “training data”? It sounds like something you’d use at a gym for robots.
John: Haha, great question, Lila! You can think of it like this: Imagine an AI is a student who has never seen the world. To teach it, we give it a gigantic library containing almost every book, article, website, and piece of text ever written by humans. The AI “reads” all of this information to learn about language, facts, and patterns. That entire library of information is its training data.
So, the AI doesn’t “think” or “feel” that 27 is a special number. Instead, it has learned from its training data that the number 27 just shows up a lot. When you ask it to pick a “random” number, it defaults to a number that it has seen frequently in all the human text it has learned from. It’s basically making an educated guess based on popularity.
So, Why Does 27 Appear So Often?
This is the fun part. Why is 27 so common in the text that AIs are trained on? Researchers believe it’s due to a mix of cultural and statistical quirks. The number 27 pops up more than you might think in human culture and writing.
Here are a few possible reasons:
- The 27 Club: This is a famous, if morbid, cultural phenomenon. It refers to a list of popular musicians, artists, or actors who died at age 27, like Jimi Hendrix, Janis Joplin, Kurt Cobain, and Amy Winehouse. This topic is written about a lot online, in books, and in news articles, meaning the number 27 appears frequently in that context.
- Mathematics and Science: The number 27 has some neat mathematical properties. For example, it’s 3 cubed (3 x 3 x 3 = 27). It also appears in various scientific contexts, which would be included in the AI’s training data.
- Simple Randomness (or lack thereof): When humans are asked to pick a random number, we’re actually not very random. For some psychological reason, people tend to gravitate towards certain numbers. When asked to pick a number between 1 and 50, numbers in the 20s and 30s are common choices, and 27 might just be a popular pick that shows up in surveys and examples online.
- Dates and References: The number 27 appears constantly as a day of the month. Every month (except February) has a 27th, so it’s mentioned in countless documents, historical records, and daily articles.
The AI isn’t aware of any of this context. It just sees the pattern: “27 appears a lot.” So when forced to choose, it picks the statistically safe bet.
Why This Funny Quirk Actually Matters: AI Bias
Okay, so the AI has a favorite number. That’s a fun piece of trivia, but does it really matter? Yes, it does! This simple example is a perfect window into a much bigger and more important concept in AI: bias.
Lila: Okay, “bias” is a word I hear on the news, but what does it mean for an AI? Does it mean the AI is prejudiced?
John: That’s a great way to put it, Lila. AI bias is when the AI gives unfair or skewed answers because it learned from biased information. Remember our library analogy? Imagine if the library we gave the AI only had books written about dogs. If you then asked the AI, “What is the best pet?” it would almost certainly say “a dog.” Not because it loves dogs, but because its entire “worldview” is based on information that is overwhelmingly about dogs. It doesn’t know about cats, hamsters, or fish because they weren’t in its training data.
The AI’s “preference” for the number 27 is a harmless example of this. But imagine if this bias applied to more serious topics. What if an AI was helping a company screen résumés for a job? If the training data (past hiring records) showed that the company mostly hired people from a certain background, the AI might learn to favor those résumés and unfairly ignore qualified candidates from different backgrounds. This is a huge challenge that AI developers are working hard to solve.
A Mirror to Ourselves
Ultimately, this “favorite number” story reminds us that AI is not a magical, all-knowing crystal ball. It’s a mirror. It reflects the vast, messy, and sometimes biased collection of information that we humans have created. The patterns it finds, both good and bad, are our patterns.
When an AI tells us 27 is a good guess, it’s really telling us something about our own culture, our history, and even our subconscious preferences. It shows us what we, as a society, have chosen to write down and talk about.
Our Final Thoughts
John’s View: I find this fascinating. It’s a perfect, simple example to show people that AI isn’t “thinking” in a human way. It’s a powerful pattern-matching machine. This little quirk with the number 27 is a healthy reminder to always be curious and a little critical about the answers AI gives us.
Lila’s View: It’s definitely less scary now that I know why it’s happening! It makes me think that we have to be really careful about what we teach these AIs. If we feed them a balanced “diet” of information, maybe they’ll give more balanced answers in the future. For now, if I ever play a guessing game with an AI, I know what number to bet on!
This article is based on the following original source, summarized from the author’s perspective:
AIs have a favorite number, and it’s not 42