Remember this date – 12 02 2012 - the day our species lost to AI - but won

This is worried look of Lee Sedol and he was in the match of his life - he lost. But it wasn't Lee who lost, it was us all or is it really a win for us, the certaors of AlphaGo? The Human v machine sparring that has been going on for some time with checkers, Chess and Jeopardy, were featherweight contests. This was the Big Fight and we, as a species, got thumped. There’s a new breed of champion in the ring and it’s not just smart, it’s a superfast learner, even its own teacher. It’s eats up human expertise for breakfast, then the real game begins, as it uses this experience to play itself, as it’s the only opponent worth playing. Having learned from us, it sucks our experts dry, then transcends their abilities to boldly go where no brain has gone before.

Momentous moment

This is a momentous moment. In less than 2.5 years, since Google snapped up Deepmind for a mere half billion dollars, 2500 years of human experience and expertise at GO has been trounced. But this is only the start. Software that learns is exponentially more powerful than software that has to be written by humans. Given the huge processing power of Google Cloud Services, AlphaGo has one of the greatest engines on the planet under its hood. It also has some of the best algorithms and that’s what matters. Machine learning algorithms are like small Gods. Free from the tyranny of time and space, speed is no limit. They can learn faster than any of us. These algorithms are the new DNA of progress. This machine moves beyond teaching and teaches itself. That’s essentially what humans do as they become expert learners, few in the later years reply any longer on teachers, as we’ve learned to learn for ourselves. AI just moves to abandoning the teacher faster.

A bit of history

Throughout our history as a species we have always benefited from the delegation of the mundane. This has largely been achieved through technology. We conquered the planet through technology. First through stone then metal tools, needles for clothing, tools for agriculture and so on. Then we invented machines that to did the manual work and we moved from the fields to factories. Then we mechanised the factories and moved towards mental work. Now we’re delegating the drudgery of some of that mental work to machines or, more accurately – AI, even more accurately to machine learning.

Teaching and learning

Amid all the hubris that surrounds education and teaching, there’s a deeper problem. Parents know it, learners know it, even teachers, lecturers and trainers know it. Performance has plateaued and everyone is getting a little fraught. Politicians, driven on by the poor foundations, and therefore learning tower of PISA results, demand more testing. Parents, the most conservative of lobbyists, demand more schooling. Teachers scream ‘enough already – we’re exhausted’. Well, isn’t it about time we looked for the sort of solutions that gave us the industrial and information revolutions of the past? Can’t machines solve the problem of teaching?

Teaching trumped by learning?

Could teaching be trumped by a learning machine? Are we beginning to glimpse the possibility of machines that teach themselves to teach? They learn what works, what doesn’t and deliver ever better performance. We see the embryonic evidence for this in adaptive learning systems, that are truly algorithmic, and do use machine learning, to improve as they deliver. The more students they teach, the better they get. They even tech themselves. This is not science fiction. This is real AI, in real software, delivering real courses, in real institutions. The future has been here for some time it’s just not distributed.

Teaching free like search?

Imagine what will happen when these super-teachers are commoditised, delivered from super fast cloud-services and let loose on the web? Teaching and learning will be as free and accessible as Google search. You will not only be able to find things with ease, you’ll be able to learn them with ease. We may see dramatic rises in performance among learners, right across the board, as such systems will be far more sensitive to individual needs, even learning difficulties. Who is likely to deliver such as service? Well Amazon are on the march, Gates has been seriously funding this stuff but Google is the front runner.

Future without teachers?

This may see hopelessly utopian. But could we have a future without teachers? Why not? Teaching is essentially being a conduit. It is a means to an end, not an end in itself. Wouldn’t academics really prefer to do pure research and not teach? Wouldn’t most teachers prefer not to have to mark anything and avoid the stress of the classroom? Couldn’t we dispense with teaching and just have learning?

Probable, improbable or impossible?

Agricultural workers were largely mechanised out of the process by machines. factory workers by robots, secretaries by word processors and It looks likely that we will see the obliteration of drivers, cabbies and truck drivers, through driverless cars. No one predicted that! There’s a lot of evidence to suggest that many professions, even white collar, middle-class professions, may be replaced by smart AI. So what’s so special about teaching? If we can teach millions, of not hundreds of millions at cents per learner, isn’t that desirable?

Remember this date

So remember this date – 12 02 2012 – it sounds almost providential. It may go down in history as the day we lost our several million year long reign as Champions of the World, not to the super-smart Frankenstein we created, but to the machine teachers who help us learn to be better humans.