{"text":[[{"start":4.84,"text":"In the genius’s playground that was Bell Labs in the 1950s, Claude Shannon, the father of information theory, built an outguessing machine. The machine’s task was simple: a human would choose one of two levers, left or right, and the machine would guess which lever the human would choose. Shannon was inspired by a colleague, whose outguessing machine had a slim but definite success rate of 53 per cent. Shannon’s own version was simpler and even better, guessing correctly 65 per cent of the time."}],[{"start":34.26,"text":"The legend related in William Poundstone’s book How to Predict the Unpredictable (2014) is that nobody ever beat the machine over an extended run, with one exception: Shannon himself. As the machine’s algorithm was simple and elegant, he was able to mentally emulate it and play the opposite of whatever he knew the machine would predict."}],[{"start":55.1,"text":"How did the machines work? The logic was simple: both took notes of how their opponent behaved. For example, if you’d won a couple of times in a row, did you usually ride your luck by sticking with the same choice or did you tend to switch? The presumption was that no human plays randomly. We all have certain habits or instincts. No supercomputing was required: Shannon’s machine had just 16 bits of memory. We humans are not hard to read."}],[{"start":80.62,"text":"An even simpler exploit is the double-tailed coin. Any scoundrel with such a coin can decide any disagreement by offering to toss it, then calling “tails”. But even if he offers his mark the opportunity to call the toss, he will probably win, because people will call “heads” more often than not."}],[{"start":97.22,"text":"One of the first academics to figure this out was Louis Goodfellow, who in the late 1930s recruited volunteers to write down a series that reflected an imagined set of coin tosses. Seventy-eight per cent of his participants began their sequence with “heads”."}],[{"start":111.04,"text":"In a larger dataset — originally gathered in an effort to study telepathy (a story for another day) — Goodfellow found that more than 20 per cent of participants either chose the sequence HHTHT or HHTTH. Other random-seeming sequences beginning with heads were also popular, such as HTTHH and HTHHT. Few people favoured anything beginning with tails, and the least popular sequence was TTTTT, chosen by about one person in 600. Any mathematician can tell you, however, that there are 32 possible outcomes of tossing a coin five times, and each of the 32 is equally likely."}],[{"start":151.64,"text":"Fifteen years later, Alphonse Chapanis, a pioneer of ergonomics, asked volunteers to take an hour or so to fill a large grid with thousands of random digits. Analysing the results produced some striking observations. The 10 least popular adjacent combinations of digits, in order, were: 66 99 00 11 33 44 88 22 77 55. And the 10 most popular? 32 43 21 76 65 10 31 87 86 54 — something about the human brain likes descending couplets, it seems. In a truly random sequence, 66 is just as likely to appear as 32, but what seems random as we scribble it down is anything but. Such regularities can be exploited by an outguessing machine, a conman, even a password guesser."}],[{"start":205.72,"text":"They can also be exploited by lazy students. Author William Poundstone offers a few tips to brute-force your way through multiple-choice tests. If you have no idea what the answer is on a true-false question, guess “true”. And if you know what the answer to the previous question was, guess that this time it will change. Offered four options, go for “B”. Always choose “all of the above” or “none of the above”, if available — they are disproportionately likely to be the correct answer. None of these methods guarantees success, but they do improve your odds because most setters of multiple-choice questions are more predictable than they realise."}],[{"start":239.58,"text":"If you really need a random sequence, then don’t ask a human. One alternative is to ask a machine to generate the randomness — but be careful. In 1980, the Pennsylvania “Pick 3” lottery was rigged by staff at the TV studio where the draw was televised. Every number except the 4 and 6 balls was weighted with a judicious addition of latex paint, meaning that when the fan was switched on to blow the lightweight balls around, all the 4 and 6 balls floated to the top. Alas for the conspirators, the heavy bets on 4-6 combinations coupled with the portentous winning number 666 were enough to raise suspicions."}],[{"start":279.72,"text":"Almost the same story played out in the digital realm more recently, when an IT expert at the Multi-State Lottery Association admitted introducing a backdoor to the software that generated lottery numbers: while it was usually random, on certain dates it would produce random-seeming numbers that he could predict."}],[{"start":297.8,"text":"Computer cryptography relies on having a large number that cannot be guessed, and the best way to have an unguessable number is to make it random. Unfortunately, this is harder to do than one might imagine, and several computer systems — most notoriously Sony’s PlayStation 3 — have been hacked because the attackers figured out how the “random” number was being produced."}],[{"start":319.88,"text":"If lottery machines — physical or digital — can be rigged, and humans are incapable of inventing truly random sequences of numbers, it is tempting to resort to the good old-fashioned coin toss. Not so fast. Persi Diaconis, celebrated both as a mathematician and magician, has found that a coin toss is, in general, a 51/49 proposition in favour of finishing the same way up that it started. To illustrate the idea further, Diaconis built a coin-tossing machine. Insert a coin heads-up and the machine will flip it nicely in the air — to land heads-up every time."}],[{"start":355.26,"text":"This is no mere theoretical problem. At the International Congress of Mathematicians this summer, maths author and YouTuber Matt Parker and friends ran a stall in which maths-curious members of the public could try tossing a coin. Parker promised to give $1,000 to anyone who managed to toss 10 heads in a row — a fun challenge to prompt people to explore what an unlikely outcome really felt like."}],[{"start":378.08,"text":"Alas, it wasn’t as unlikely as he had imagined: having been forced to hand over the $1,000 prize twice on the first day, Parker looked at the accumulating data and realised that the entire distribution of coin flips was unexpectedly biased towards strings of tails or strings of heads. The effect was stronger than Diaconis had predicted, perhaps because many of Parker’s coin tossers were rather young and unable to reliably flip coins high enough to rotate much. Parker’s solution: on the second day of the conference, he switched to dice. The pattern of results reverted to something much closer to pure randomness . . . whatever that is."}],[{"start":418.04,"text":"Find out about our latest stories first — follow FT Weekend Magazine on X and FT Weekend on Instagram"}],[{"start":425.24,"text":""}]],"url":"https://audio.ftcn.net.cn/album/a_1787924747_3682.mp3"}