> In a class I taught at Berkeley, I did an experiment where I wrote a simple little program that would let people type either “f” or “d” and would predict which key they were going to push next. It’s actually very easy to write a program that will make the right prediction about 70% of the time. Most people don’t really know how to type randomly. They’ll have too many alternations and so on. There will be all sorts of patterns, so you just have to build some sort of probabilistic model. Even a very crude one will do well. I couldn’t even beat my own program, knowing exactly how it worked. I challenged people to try this and the program was getting between 70% and 80% prediction rates. Then, we found one student that the program predicted exactly 50% of the time. We asked him what his secret was and he responded that he “just used his free will.”
There's another version where a stats professor divides people into two groups. One group flips a coin 50 times and writes on a whiteboard the results. The other comes up with 50 results.
They leave the room and when they come back immediately know which is which. Specifically because of the over-alternation that yours mentioned. A string of HHHHHH is exactly as likely as HTHTHT, but people don't intuit that.
I have managed to get 38-48% the times I tried. I believe I might have been influenced by the article I just read.
It would be interesting to see if by giving people advice on statics it would produce, on average, a measurably different outcome.
This isn't very interesting, but it scratched an itch I had to see what would happen.
The house's record
The house called 18 of your 190 scored numbers: 9%.
Blind guessing would average about 21.1 of them (11%).
Only 1 of the 206 people in a psychology study was more random than you. The house found you extremely hard to read.
I really want to know who was more random than a RNG
It might not be that someone is more random than an RNG, but that the distribution of numbers in your 190 vs. theirs appears more "random". It's a limited sample size.
If yours happened to contain consecutive digits or common ones (ending in zero, significant numbers like 911 or 42 or 69), that would imply less randomness even if it's actually the result of "real" RNG.
Many years ago, as a side project to help me apply to tech companies, I made this little site [0] where the premise is trying to pick the number that you think other people won't pick very often. I still think it's pretty neat.
Also, in part because of this project, I got to go from being unemployed in my hometown in the South to working in SF on some pretty neat projects. It's a good memory.
Nice~ The website made me recall an old mentalist force trick we learned as kids where you ask somebody to "quickly think of a two-digit odd number between 1 and 50 where each digit is a different number".
Most people will say: 100101 (binary to avoid spoilers)
The house called 9 of your 117 scored numbers: 8%.
Blind guessing would average about 13.0 of them (11%).
None of the 206 people in a psychology study were more random than you. The house found you extremely hard to read.
What about the following strategy? You first think of a random integer n1 from 1 to 9, then you think of another one n2, perhaps one that you have not used very often, and finally say (n1+n2) mod 9 + 1. I think this strategy could make your selection more random . Perhaps someone could try it and report the results.
This is pretty interesting. I've found it's fun to throw off the algorithm. Use your warmup to repeatedly guess the same number, and then don't use it for a while.
> The house called 1 of your 32 scored numbers: 3%. Blind guessing would average about 3.6 of them (11%). Only 1 of the 206 people in a psychology study was more random than you. The house found you extremely hard to read.
I found it interesting when I felt my focus shift from the number-generating task to noticing (and responding to) the house’s guesses.
As soon as I noticed it repeating its guess, I had a good long run of adversarially avoiding that number… it’s kind of fun being on the machine side of the slot-machine-type racket!
The first time I did badly. But the second time I got really far by deciding on a number instinctively and then picking something next to it. Maybe we instinctively pick similar numbers, but if we fight our instincts we end up with something truly random.
Alternating and advancing from both ends seems to work, it calls n-1, and n+1 correctly if the previous guess was n, but got no calls in a sequence like - 1, 8, 3, 7, 4, 7, 1, 7, 3, 8, etc
OP here - I went with Vosk because it's pretty trivial to lock input down to a set vocabulary (in this case numbers) and from my testing works relatively well on most browsers. (webkit, firefox, etc)
Yup! Most of the way I put the system together was by having it build several n-gram Markov models of your numerical sequences on the fly.
But we also have a couple of predictors that aren’t markov chains and are based on simpler heuristics. Without seeing your record, I'm guessing that the "numerical avoider" predictor got overweighted and just kept trying to guess the same number.
I just pretended I'm playing piano to a megamix of tracks which popped into my head and did 'well'. Only 2 people more random. Typing though, think the site said that's "easier to win" on. Cba to speak 200 numbers out loud :/
Haha, that’s great. Yeah, I totally get what you mean about speaking out loud.
You only really need to vocalize about ~40 numbers total, but you can actually get a similar level of RNG by "subvocalizing the numbers" before you press them on the keypad.
The main issue is that using the keypad kind of lends itself to just pressing it randomly without really thinking about the actual numbers themselves.
"You spread your picks more evenly than a random draw would. Your most-used number made up 23% of your picks, where a random draw's busiest number gets about 23%."
I have a little "mad-lib templatized" set of sentences for reporting on various stats, and that one was supposed to be sort of related to the law of small numbers. For example, shorter runs mean there is a larger probability of getting lopsided distributions (different from pure 11%).
It's supposed to demonstrate that even though you used a single number a disproportionate number of times, it's not necessarily statistically significant since shorter RNG runs can produce the same effects.
> In a class I taught at Berkeley, I did an experiment where I wrote a simple little program that would let people type either “f” or “d” and would predict which key they were going to push next. It’s actually very easy to write a program that will make the right prediction about 70% of the time. Most people don’t really know how to type randomly. They’ll have too many alternations and so on. There will be all sorts of patterns, so you just have to build some sort of probabilistic model. Even a very crude one will do well. I couldn’t even beat my own program, knowing exactly how it worked. I challenged people to try this and the program was getting between 70% and 80% prediction rates. Then, we found one student that the program predicted exactly 50% of the time. We asked him what his secret was and he responded that he “just used his free will.”
I actually built this on a whim after watching that episode of TNG where Data locks everyone out of the Enterprise.
https://youtube.com/watch?v=rERApU26PcA
https://youtu.be/bl5TUw7sUBs
They leave the room and when they come back immediately know which is which. Specifically because of the over-alternation that yours mentioned. A string of HHHHHH is exactly as likely as HTHTHT, but people don't intuit that.
this contradicts the comment you're replying to. the premise they are having is that HTHTHT is "less random" than HHHHHH.
https://aaronsonoracle.com/
This is what I also use for rock, paper scissors (mod 3). You can also use second hand of a watch for random samples, e.g splitting 0-30 vs. 31-60.
The secret? I distracted myself with the website text and kept pressing the buttons quickly without thinking about it.
"Over here we have our random number generator."
https://web.archive.org/web/20230305130159im_/https://assets...
If yours happened to contain consecutive digits or common ones (ending in zero, significant numbers like 911 or 42 or 69), that would imply less randomness even if it's actually the result of "real" RNG.
tldr; "im just like totally so random xD"
Also, in part because of this project, I got to go from being unemployed in my hometown in the South to working in SF on some pretty neat projects. It's a good memory.
[0] https://www.humanrandomness.com/
Most people will say: 100101 (binary to avoid spoilers)
(Yes, I saw the "type the numbers" option.)
Nice!
I tried it. Several 9s later, it figured me out.
I started just lagging the guesses of the machine, and it never seemed to catch on.
As soon as I noticed it repeating its guess, I had a good long run of adversarially avoiding that number… it’s kind of fun being on the machine side of the slot-machine-type racket!
Not familiar with the sota if someone can chime in.
https://github.com/alphacep/vosk-api
I always thought I was random, but now it's conclusive!
https://imgur.com/a/0azWegW
Did I break it?
But we also have a couple of predictors that aren’t markov chains and are based on simpler heuristics. Without seeing your record, I'm guessing that the "numerical avoider" predictor got overweighted and just kept trying to guess the same number.
It should be fixed now!
Thanks, btw, actually enjoyed that. :)
You only really need to vocalize about ~40 numbers total, but you can actually get a similar level of RNG by "subvocalizing the numbers" before you press them on the keypad.
The main issue is that using the keypad kind of lends itself to just pressing it randomly without really thinking about the actual numbers themselves.
??? huh?
I have a little "mad-lib templatized" set of sentences for reporting on various stats, and that one was supposed to be sort of related to the law of small numbers. For example, shorter runs mean there is a larger probability of getting lopsided distributions (different from pure 11%).
It's supposed to demonstrate that even though you used a single number a disproportionate number of times, it's not necessarily statistically significant since shorter RNG runs can produce the same effects.