AI and the Dilemma of Technology

Here, in two sentences, is the Dilemma of Technology:

Fritz Haber earned the Nobel Prize for Chemistry in 1918 for his invention of the Haber-Bosch process which synthesized ammonia from hydrogen and nitrogen gases. His discovery fed millions through its application to fertilizer, and killed millions more through its application to manufacturing explosives.

Though the final count is, of course, not yet available, no scientifically minded accountant has yet tallied the columns and calculated which side is ahead in the race. My guess is the Lives Saved column outstrips the Lives Taken by a country mile because, even though those milling about in that century did their level best to kill as many people as possible, global population increase over the twentieth century tracked along with increases in food production — and both were enormous.

The Dilemma is easy to state: You get both good and bad with every new invention or innovation, depending on the uses to which the invention is put. The Dilemma speaks of us, not the inventions. The stick is not culpable for crushing an enemy’s skull; its wielder is.

Good and Bad

The late Australian philosopher David Stove opened his essay “Why You Should Be a Conservative” with an anecdote showing that the Dilemma is ever-present:

A primitive society is being devastated by a disease, so you bring modern medicine to bear, and wipe out the disease, only to find that by doing so you have brought on a population explosion. You introduce contraception to control population, and find that you have dismantled a whole culture. At home you legislate to relieve the distress of unmarried mothers, and find you have given a cash incentive to the production of illegitimate children. You guarantee a minimum wage, and find that you have extinguished, not only specific industries, but industry itself as a personal trait. You enable everyone to travel, and one result is, that there is nowhere left worth travelling to. And so on.

Here’s another example: You invent superior methods of surgery to cure awful ills, but you discover it allows people to indulge in the fantasy of “sex change” operations.

Stove shows us the Dilemma applies not just to technology, but to “innovations” and “Change we can believe in” of any kind. The moral is that caution in adopting new things is always to be recommended, but the historical lesson, which all know but all forget, is that it almost never is. Hence the perpetual mad race of one “solution” being proposed to fix all the problems introduced by previous “solutions.”

If the introduction of new technological solutions worries you, you can try making certain lines of research illegal — like gain-of-lethality investigations. (Researchers in that proscribed field prefer the euphemism “gain-of-function.”) Murder is illegal, too, yet murder is still with us. So it shouldn’t be strange that forbidding scientists to monkey with viruses doesn’t stop them from doing so.

The current Dilemma surrounds the fears, and not a little hype, over so-called Artificial Intelligence. Should you fear it?

Who Will Be Obsolete?

Not if you believe computers will come alive, gain sentience, become conscious, take over the world, make us their slaves, and that line of thing. These scenarios are not only unlikely, they are impossible. Computers are mere machines, and AI is nothing but glorified statistical models. They may be good to excellent models, at times, but they are models nonetheless, and all models only say what they are told to say. Which means it’s better to know and have some influence over who writes the models; or, in other words, better to have coders on our shores than off shores.

Don’t worry, then, about these models being omniscient or becoming godlike and having all the answers. They only have the answers supplied to them. What you do have be frightened of are those who think the computers are infallible, or have somehow ascended beyond. Offloading decisions to AI is the same as asking programmers what is best in life. The glamour of computers and the excellence AI will attain at mimicry will cause many to forget this.

Will these models take your job? Maybe. Or even likely, especially if you’re a cubicle dweller cycling emails. Or making cartoons or illustrations. Or answering phones and directing calls. But not if you’re hauling or installing plumbing supplies, knocking studs together, cutting open a chest and installing a stent, or even being a politician.

You might survive if you’re a writer. What passes for “news” can be programmed, and even is already. The real danger is to talking heads, who can be replaced with invented computer personalities. Some “creatives” in these vaguely disreputable jobs will survive. Even if you cheat and pass off AI for your own work, the paycheck for appearances sake will still come to you.

Managing Change

On the other hand, back in the 1980s we were warned that secretaries were soon to be made redundant because word processors would steal their livelihoods. Secretaries don’t take diction as often now as then, and aren’t as responsible for correspondence, but other uses were found for them.

In a speech at the American Dynamism Summit, J.D. Vance recalled the predictions of how bank tellers would no longer be needed once ATMs took root. Didn’t happen.

Assembly line workers took a hit once robots became commonplace, but that was also because of the grand ideas behind free trade, which led to manufacturing largely moving offshore. Ideas about open borders, financially and literally, are changing, though, so perhaps factories will return. Grueling hand-work might no longer be required, with robots assigned to repetitive tasks, guided by software (a.k.a AI). But people will be found to be indispensable for the process, though the old jobs won’t look the same as new ones.

The interactions between man and machine, man and nature, and, even more so, between man and man are so hideously complex that venturing any prediction about the precise shape of our coming (greater) software-controlled economy, about who will lose their job and who will gain a new one, requires more recklessness than I possess.

I can venture that change, like always, is coming, and there’s not much you can do to stop it. The best you can do is learn to live with it.

William M. Briggs is a senior contributor to The Stream, the author of Uncertainty and maintains an active and lively blog at wmbriggs.com. He earned his Ph.D. from Cornell University in statistics and studies the philosophy of science, the use and misuses of uncertainty, the corruption of science and the uselessness of most predictions. He began life as a cryptologist for the Air Force, slipped into weather and climate forecasting, and matured into an epistemologist.