There’s a lot of nail-biting currently about the potential impact of the next wave of technology, particularly artificial intelligence.
In her book, Hello, World, mathematician Hannah Fry described one aspect—the trusting side—of our often paradoxical relationship with technology: “It’s like the saying among airline pilots that the best flying team has three components: a pilot, a computer and a dog. The computer is there to fly the plane, the pilot is there to feed the dog. And the dog is there to bite the human if it tries to touch the computer.”
Indeed, “we have a tendency to over-trust anything we don’t understand,” according to Fry, [but] “as soon as we know an algorithm can make mistakes, we also have a rather annoying habit of over-reacting and dismissing it completely, reverting instead to our own flawed judgment.”
“This tendency of ours to view things in black and white—seeing algorithms as either omnipotent masters or a useless pile of junk—presents quite a problem in our high-tech age.”
There is ever-accumulating evidence that using algorithms gives better results when making decisions, predictions, diagnoses, and judgments—both trivial and consequential. But there will always be many areas where it’s best for humans to be augmented—not replaced—by machines.
Algorithms can be, to borrow an analogy from Neal Stephenson, “like the genie of the ancient fairy tales, who carries out his master’s instructions literally and precisely and with unlimited power, often with disastrous, unforeseen consequences.” But as Stephenson also said, “The danger lies not in the machine itself but in the user’s failure to envision the full consequences of the instructions he gives to it.” When things go awry the blame lies with us, not the algorithm.
Fry advised, “Whenever we use an algorithm—especially a free one—we need to ask ourselves about the hidden incentives. Why is this app giving me all this stuff for free? What is this algorithm really doing? Is this a trade I’m comfortable with? Would I be better off without it?”
And most importantly, “apply a healthy dose of common sense when it comes to using these algorithms” because the truth lies in the wide area between the omnipotence we desire for our machines and the uselessness we sometimes accuse them of.