In September 1969, as I began ninth grade, a rumour circulated that the Beatles' Paul McCartney was dead, killed in a 1966 automobile accident and replaced by a look-alike. The clues were there in the albums, if you knew where to look. Sgt. Pepper's Lonely Hearts Club Band's 'A Day in the Life', for one, recounts the accident: 'He blew his mind out in a car/He didn't notice that the lights had changed/A crowd of people stood and stared/They'd seen his face before/Nobody was really sure if he was from the House of Lords'. The cover of the Abbey Road album shows the Fab Four walking across a street in what looks like a funeral procession, with John in white as the preacher, Ringo in black as the pallbearer, a barefoot and out-of-step Paul as the corpse, and George in work clothes as the gravedigger. In the background is a Volkswagen Beetle (!) whose license plate reads '28IF' ' Paul's supposed age IF he had not died.
Spookiest of all were the clues embedded in songs played backward. On a cheap turntable, I moved the speed switch midway between 331/3 and 45 to disengage the motor drive, then manually turned the record backward and listened in wide-eared wonder. The eeriest is 'Revolution #9' from the White Album, in which an ominously deep voice endlessly repeats: 'number nine ... number nine ... number nine....' Played backward you hear: 'turn me on, dead man ... turn me on, dead man ... turn me on, dead man....'
In time, thousands of clues emerged as the rumour mill cranked up (type 'Paul is dead' into Google for examples), despite John Lennon's 1970 statement to Rolling Stone that 'the whole thing was made up'. But made up by whom? Not the Beatles. Instead this was a fine example of the brain as a pattern-recognition machine that all too often finds nonexistent signals in the background noise of life.
What we have here is a signal-to-noise problem. Humans evolved brains that are pattern-recognition machines, adept at detecting signals that enhance or threaten survival amid a very noisy world. This capability is association learning ' associating the causal connections between A and B ' as when our ancestors associated the seasons with the migration of game animals. We are skilled enough at it to have survived and passed on the genes for the capacity of association learning.
Unfortunately, the system has flaws. Superstitions are false associations ' A appears to be connected to B, but it is not (the baseball player who doesn't shave and hits a home run). Las Vegas was built on false association learning.
Consider a few cases of false pattern recognition: the face of the Virgin Mary on a grilled cheese sandwich; the face of Jesus on an oyster shell (resembles Charles Manson, I think); the hit NBC television series Medium, in which Patricia Arquette plays psychic Allison Dubois, whose occasional thoughts and dreams seem connected to real-world crimes; the film White Noise, in which Michael Keaton's character believes he is receiving messages from his dead wife through tape recorders and other electronic devices in what is called EVP, or Electronic Voice Phenomenon. EVP is another version of what I call TMODMP, the Turn Me On, Dead Man Phenomenon ' if you scan enough noise, you will eventually find a signal, whether it is there or not.
Anecdotes fuel pattern-seeking thought. Aunt Mildred's cancer went into remission after she imbibed extract of seaweed ' maybe it works. But there is only one surefire method of proper pattern recognition, and that is science. Only when a group of cancer patients taking seaweed extract is compared with a control group can we draw a valid conclusion.
We evolved as a social primate species whose language ability facilitated the exchange of such association anecdotes. The problem is that although true pattern recognition helps us survive, false pattern recognition does not necessarily get us killed, and so the overall phenomenon has endured the winnowing process of natural selection. The Darwin Awards (honouring those who remove themselves from the gene pool) will never want for examples. Anecdotal thinking comes naturally; science requires training.
Michael Shermer's new book is Science Fiction: Where the known meets the unknown (Times Books). This article was first published in Scientific American
