Tests of natural language processing models show that the bigger they are, the bigger liars they are. Should we be worried?
We are, as the critic George Steiner observed, “language animals”. Perhaps that’s why we are fascinated by other creatures that appear to have language – dolphins, whales, apes, birds and so on. In her fascinating book, Atlas of AI, Kate Crawford relates how, at the end of the 19th century, Europe was captivated by a horse called Hans that apparently could solve maths problems, tell the time, identify days on a calendar, differentiate musical tones and spell out words and sentences by tapping his hooves. Even the staid New York Times was captivated, calling him “Berlin’s wonderful horse; he can do almost everything but talk”.
It was, of course, baloney: the horse was trained to pick up subtle signs of what his owner wanted him to do. But, as Crawford says, the story is compelling: “the relationship between desire, illusion and action; the business of spectacles, how we anthropomorphise the non-human, how biases emerge and the politics of intelligence”. When, in 1964, the computer scientist Joseph Weizenbaum created Eliza, a computer program that could perform the speech acts of a Rogerian psychotherapist – ie someone who specialised in parroting back to patients what they had just said – lots of people fell for her/it. (And if you want to see why, there’s a neat implementation of her by Michael Wallace and George Dunlop on the web.)
