Although sixty years old, artificial intelligence remained mostly a curiosity until half a decade ago, when IBM’s Watson trounced the world’s best Jeopardy! players in a televised match. At the time, you might have thought nothing of that - what does a game show matter in the scheme of things?
It didn’t stop there. IBM sent Watson to train with oncologists and lawyers and financial advisers. Quite suddenly, three very established professions, just the sort of thing you'd tell your kids to pursue as a ticket to prosperity, seemed a lot less certain of their futures in a world where intelligence, like computing before it, becomes pervasive, then commoditised.
These top-of-their-profession projects show that the driver to bring artificial intelligence into any field isn’t the amount of labor, but rather the cost of that labor. A lawyer costs fifty times more per hour than a retail worker and so is that many times more likely to find themselves with an AI competitor.
Automation's erosion of work will proceed from the top-down; although we will certainly see long-haul truck drivers replaced by autonomous vehicles within the next few years, it’s actually the doctors and lawyers and bankers who really need to be afraid.
Just today I read an article about MogIA, software that analyzes millions of inputs from social media and search engines to predict the future. Since MogIA called the result of the recent US Presidential election, it’s being taken quite seriously. It’s reasonable to expect that within a few years I could be competing against an always-on Futurist-as-a-service in my own professional life.
The same will be true for editors and marketers and auditors and … at this point we run out of pavement, because while there are likely to be some professional roles that artificial intelligence will not compete with in the short term, those roles are fewer than we had believed, and we can’t all crowd into those fields.
The middle years of the 21st century will feel a bit like musical chairs to anyone who tries to build a career. Everyone so often the music will stop, and another profession will have been eaten by increasingly-capable AIs.
When that problem was ‘over there’ - with people who had less training, whose lives were more precarious - we gave it less thought than we probably should have. Now we have to wonder if we have enough time to think our way through to a solution.
Our ‘gig economy’ demonstrates both problem and solution: we have no security, but we do have flexibility. Sharks, tracing an endless path toward our next meal, we have to keep moving. But the fish are getting wise to our ways, so we can’t be the same dumb eating machines we were a decade, or even a year ago. We have to get smarter faster than our dinner, or we’ll never find enough to eat.
Education needs to become a constant part of our diet: real education, not not just the firehose of truthy factoids that clutter social media. For a generation, educators have been pointing to an era of ‘lifelong learning’, a cradle-to-grave process of capacity-building. For all that talk, we haven’t seen enough of it; those of us who we graduate from university mostly get to work and seldom make the time for or are offered further professional development.
The massive infrastructure we’ve built out over the last decade - one that brought three billion smartphones to as many hands - offers us a chance to lean into lifelong learning. Case in point: earlier this year I watched a video of a 15 year old, teaching me how to program in virtual reality. For almost any topic in technology, you can use a search engine to find an answer.
That’s not to say Google is the new classroom - because we’ve already outgrown the classroom. We have to reorder our priorities, using our “20% time" to master a new and valuable skill, and we have to do this constantly. There’s no end to this treadmill, because at no point will any of this artificial intelligence stop to take a breath.
We value IT automation as a time- and money-saver, allowing us to do ever more with less. That drive to automation doesn’t stop just because it engulfs our own skills. Our efforts in machine learning, cloud computing, and connectivity have enabled this revolution, and it’s coming for us now, this Rise of the Machines.
The same skills that enabled that rise can help us rise to meet the challenge. We know how to build systems that allow us to share knowledge at scale, learn from one another, and put those new capacities to work. In smartphones we have a global platform to bring these systems to nearly every adult on the planet - just in the nick of time.
This is the future IT owes to everyone else; we took the jobs away, now we have to create the scaffolding to allow everyone keep pace in a world where robots are nipping at our heels. Unless we learn how to learn a lot faster than we do today, we’ll be eaten whole. ®