The Human Factor (in the Age of Machines)
No matter how far AI evolves in the future, for as long as humans remain as the dominant species on this planet, machines will exist to serve the benefit of human collectives, in some form or another. That is an optimistic view and possibly the best-case scenario.
Now, if we imagine the dark path as kindly illustrated in movies like "Terminator" or the "Matrix" series, AI may one day decide to eliminate humans as we are merely nuisances to them (the worst case scenario), or convert us into living, breathing battery packs to power them with our body heat (the next-worst-case scenario).
Even without such doomsday predictions, it is quite feasible that machines will take jobs away from most of us, starting with menial and repetitive ones and moving on to so-called white-collar positions with thinking involved. Not quite the end-of-the-world case, but definitely the end-of-the-world-as-we-know-it situation, as the cognitive process won’t remain as a uniquely human function.
Not too long ago, it was big news that AI decisively defeated one of the smartest human beings on Earth in the game of Go. It was quite an achievement — not necessarily for the machine, but for the humans who designed it. The machine, less than one year after that achievement, is now up to the level that its older version won’t able to match. The latest is that it doesn’t even play Go anymore, after having played the game by itself millions of times.
Here is my take on that event: First, why is that so surprising? Yes, the game of Go is far more complex than chess, with a virtually unlimited number of outcomes. But everything happens on a game board and the rules are quite simple. Machines and humans can observe and predict events within that set boundary. If machine does nothing but “1” task within the rule set for an unlimited amount of time without being bored or getting tired, of course it will beat humans who easily get distracted or grow tired.
So can we even call such a match fair? At some point in the distant past, a car passed the speed of the fastest human runner or even a man on a horse (with exactly 1 horse-power). But other than the fact that we still continue to humiliate horses by measuring the engine power in terms of “horsepower,” who cares about that? We don’t have runners compete against cars in the Olympic Games, do we?
The second point is that, yes, it is newsworthy that an AI beat one of the best Go players in the world. But so what? The history of computers has been a series of human defeats in terms of speed and accuracy since the very invention of the thinking machine. Computers have been outperforming humans in many ways all along, so why does everyone get so scared them all of a sudden? Is it fear of the unknown or loss of control?
We have learned how to coexist with clunky mainframes in the past, and we will learn how to live — and live well — with AI with or without cute faces. And that's if, and only if, we maintain the “human factor” in the evolution of thinking machines.
So let’s stop thinking about how smart machines have become, and let’s think about what that word “smart” means.
What 'Smart' Means
Does it mean that it remembers things better than us? Undoubtedly. The best use of a computer is to have it remember what we don’t want to remember. Just because I can’t even remember my work number without my “smart” phone, that doesn’t mean that I became dumber. I will use the remaining memory space in my brain to store some other useless information, like the average driving distance of an old golfer or a name of an actor in some obscure movie. Then again, why even bother with all of that when I can just Google them anytime?
Stephen H. Yu is a world-class database marketer. He has a proven track record in comprehensive strategic planning and tactical execution, effectively bridging the gap between the marketing and technology world with a balanced view obtained from more than 30 years of experience in best practices of database marketing. Currently, Yu is principal and chief product officer at BuyerGenomics. Previously, Yu was the head of analytics and insights at eClerx, and VP, Data Strategy & Analytics at Infogroup. Prior to that, he was the founding CTO of I-Behavior Inc., which pioneered the use of SKU-level behavioral data. “As a long-time data player with plenty of battle experiences, I would like to share my thoughts and knowledge that I obtained from being a bridge person between the marketing world and the technology world. In the end, data and analytics are just tools for decision-makers; let’s think about what we should be (or shouldn’t be) doing with them first. And the tools must be wielded properly to meet the goals, so let me share some useful tricks in database design, data refinement process and analytics.” Reach him at firstname.lastname@example.org.