Futurology, future-gazing, horizon-scanning – it’s all the same. And (whilst I would say this) it’s helpful, even crucial. Inherent in these very words though is a hidden but unhelpful limitation, for it compares tomorrow’s world to today.
Obsessing over comparisons, whilst it does of course give us a frame of reference, does not help us freely imagine what things could, or even should be like. We find ourselves thinking about a starter position that is already weighed down by legacy assumptions.
My current musing on this is spurred by both the fest of predictions and webinars (unrepentantly guilty as charged) and the existential worries that attend the “robots are better than humans (and vice versa)” debate surrounding automation and AI.
Currently, we compare automation software and AI to humans, partly as a result of the human tendency to anthropomorphise anything which appears to have human-like powers. Naming things - Amelia at IPSoft, Sarah at Soul Machines, Alexa for Amazon, Watson for IBM and on and on - simply (and quite deliberately) enhances this subliminal acceptance of machines as being sentient or human-like.
And partly because it's directly in contact with us (and our jobs). A lot of this is down to screaming headlines, and even some actual balanced research (there is some: see McKinsey,Nesta and Horses For Sources).
We recognised a long time ago that a horse is faster transport than a human. A car is faster and more comfortable than a horse. We just don’t make a comparison between a car and a human because it's now a step removed. It's just a tool in daily life. (Let’s leave the debate about autonomous cars for right now – because we loop back into computers vs humans again…)
Acceptance of technological advances often proceed this way. We need something to place itself between us and that advance. Sometimes that’s just time itself. And at other times that’s another step change, at which point the News 24 effect kicks in and the initial advance becomes old hat and part of the furniture.
The interesting thing about right now is the pace at which this is happening. Our frames of reference aren’t even caught up to acceptance before the next thing comes along. Voice user interfaces like Alexa or Google Home are putting themselves in between us and the complexities of AI and automation (the irony of course being that they are themselves powered by complicated machine learning). So our understanding of what AI is, and what it can and can’t do is being mediated, warped, both softened and exacerbated by this distinctly human interface.
Instead of getting bogged down in the “what happens when computers think like us” mode of comparative thinking, think about “what happens when computers think like computers”. Computers can simply do things we cannot do, so imposing our imaginative constraints on them limits our imagination of how things could be. Only then will we begin to decouple from our legacy-laden preconceptions.