Gartner: Predicting What Technology Will Do Is Much Easier Than Predicting What Humans Will Do With It
Here at Gartner we make a lot of predictions. I jumped in feet first as co-lead author of our Software Adoption predicts and have been closely watching the predictions on AI.
I’ve noticed a single factor that divides these predictions: whether they depend on the human element or not. If the topic is purely technical, like predicting what self-driving cars will be able to do on a test track in ten years, the human element is fairly low. Sure, the brilliance of the engineers, tenacity of the project managers, and ability of the execs to keep the business afloat long enough to see it through all play in. But mostly that’s a prediction about what the technology will be capable of.
Compare that to predicting how many self-driving cars will be on the road in ten years. Now you’ve introduced humans into the equation and certainty goes out the window. Technological feasibility is just the bar of entry to a morass of social, political, and psychological considerations – human issues – that greatly decrease the confidence interval of the prediction.
The easiest way to approach a prediction including humans is to “assume” them out. Assume the human response will be rational, intelligent (or informed), benevolent, and unimpeding of technological progress (RIBU? I’d come up with an acronym for NONLUDDITE, but I don’t have time for that).
Artificial intelligence (or automation, or robots) invite many predictions about what they will be able to do. And that’s a start. But now, if the technology turns out to be powerful, companies may be smart about it or stupid; governments may be smart or stupid. Predicting the effect isn’t just about what the tech will do – it’s a prediction of how humans will behave when thrown a powerful new toy.edict this is going to be interesting.
Read the entire article here, Predicting What Technology Will Do Is Much Easier Than Predicting What Humans Will Do With It
Via the fine folks at Gartner.