What does artificial intelligence have in common with the price of eggs?
Say youâre trying to decide between 9 or 10 different varieties of eggs at the store. One catches your eye: âAll natural.â Well, thatâs nice, natural is good and theyâre only 30 cents more â you buy those. Now, those chickens and the eggs they produce may or may not be more natural than the others â because thereâs no official or even generally agreed-upon definition of natural. Itâs a common ploy to make you pay 30 cents for nothing. That same exact thing is becoming a problem in tech â but with AI.
There is no official or generally agreed-upon definition of artificial intelligence â if youâre curious about why that is, I wrote a very woolly post called WTF is AI that you might enjoy. But this lack of consensus hasnât stopped companies great and small from including AI as a revolutionary new feature in their smart TVs, smart plugs, smart headphones and other smart macguffins. (Smart, of course, only in the loosest sense: like most computers, theyâre fundamentally dumb as rocks.)
Now, there are two problems here.
Itâs probably not AI
The first problem is this: Because AI is so poorly defined, itâs really easy to say your device or service has it and back that up with some plausible-sounding mumbo jumbo about feeding a neural network a ton of data on TV shows or water use patterns.
âThe term is complete bullshit,â said the CEO of a major robotics company that shall remain nameless, but certainly employs in its robots what most would agree could be called AI. Itâs a marketing term used to create the perception of competence, because most people canât conceive of an incompetent AI. Evil, perhaps (âIâm sorry, Dave, I canât do thatâ), but not incompetent.
This recent flowering of AI into a buzzword fit to be crammed onto every bulleted list of features has to do at least partly with the conflation of neural networks with artificial intelligence. Without getting too into the weeds, the two arenât interchangeable, but marketers treat them as if they are.
The neural networks we hear so much about these days are a novel way of processing large sets of data by teasing out patterns in that data through repeated, structured mathematical analysis. The method is inspired by the way the brain processes data, so in a way the term artificial intelligence is apropos â but in another, more important way, itâs very misleading.
AI is a phrase with its own meaning and connotations, and they donât really match with what neural networks actually do. We may not have defined AI well, but we do have a few ideas. And itâs safe to say that while these pieces of software are interesting, versatile and use human thought processes as inspiration in their creation, theyâre not intelligent.
Yet any piece of software that, at any point in its development, employs a convolutional neural network, deep learning system or what have you, is being billed as âpowered by AIâ or some variation thereof.
Now, if even experts canât say what AI is, what hope is there for consumers? Itâs just another item on a list of features and likely as opaque as the rest to the person reading it. But they know AI is high-tech and being worked on by all the big companies, so the product with AI in it must be better. Just like the person choosing ânaturalâ eggs over another brand â one that could just as easily have put that label on their own box, with as little justification.
And even if it wereâ¦
The second problem is that even if there were some standard for saying what AI is and isnât, and we were to grant that these systems met it, these arenât the kinds of problems that AI is good at solving.
One company, for instance, touted an AI-powered engine for recommending TV shows. Think about that. What insight could emerge from unleashing a deep learning system on such a limited set of data around such a subjective topic? Itâs not a difficult problem to determine a recommendation for someone who likes CSI: Miami. Theyâll like Person of Interest or something. These arenât subtle, hidden patterns that only emerge after close scrutiny, or require hours of supercomputer time to figure out.
And in fact, as Jaron Lanier explained well in The Myth of AI, because the data originates from people â e.g. people who watch this also watch that â the artificial intelligence is completely dependent on human intelligence for all the decisions it makes. People already did the hard part â the development of taste, the selection of what shows they like and donât like, judging the quality of the episodes, of the acting and direction â and all the computer is doing is searching through human intelligence and returning relevant results.
Similar claims are made on behalf of IoT devices like thermostats and now shower heads that monitor your use and recommend things or save energy when they know youâre not there. An AI for your home! It tells you when youâre low on milk! It identifies whoâs at the door! These are similarly spurious: the data sets are sparse and simple, the outputs binary or highly limited. And just because a device isnât quite as dumb as the one youâve been using for 30 years, that doesnât make it smart. On the contrary, these claims of intelligence areâ¦ artificial.
Itâs a fiction cultivated by tech companies that AI meaningfully improves many of these things â in addition to the fiction that itâs AI in the first place. Itâs even possible that relying on machine learning is detrimental to their purpose, since the methods by which these models arrive at their conclusions are often obscure.
This is a bit like another marketing trick often found on egg cartons. Ever seen one that promises that the chickens are raised on an all vegetarian diet? So thoughtful! Problem: chickens arenât vegetarians, they eat worms and bugs â have done for millions of years. And really, itâs more than likely that taking them off their native diet will negatively affect their livelihood and the quality of the eggs. (Incidentally, what you want is âpasture-raised.â)
Maybe youâre thinking, okay Mr. Big AI Expert, if none of this counts as AI, what does? And why is it you arenât so choosy about the term AI when it comes to writing clickbait headlines?
Well, this is all just my opinion, but when weâre talking about AI as a concept being researched or developed by big companies and universities, itâs okay to stretch the definition a bit. Because what weâre talking about is really a nascent class of software and thereâs no sense being pedantic when the ideas fall under the umbrella most people would understand as AI. But when companies use that fundamental vagueness as a deceptive sales pitch, I feel I have to object. And so I have.
Misleading, exaggerated or outright fabricated feature lists are a hallowed tradition in tech, so this practice is nothing new. But itâs good to point out when a new weasel word enters the lexicon of trend-hunting marketers. Perhaps there will be a day when AI is actually something youâll look for in a refrigerator, but that day is not today.
Featured Image: Bryce Durbin / TechCrunch