This post is the first part of a series on the impact of Automation, AI and Deep Learning.
Some changes appear from out of the blue. We can prepare ourselves for the unexpected, but can’t preempt the change. there are others we can anticipate. For many of those big transformations there are early signs; a gathering of signals that combine to point to a very different future.
The internet is a great example of massive change that came with plenty of warning. The growth of computers and communications followed a path of progression. It may have accelerated, but for developed nations there were few unknowns. For those that could read the signs the change was easier; for others it has been something of a challenge.
There is another event on the horizon: automation. This isn’t the story of robot overlords, one hopes, but the shift of a technology from the realms of research into the zone of commercial viability. And it’s a big delivery. The number of projects achieving solid goals in AI indicates we’re reaching a tipping point where significant investment will start to be made in anticipation of return. The success of AlphaGo, winning 4-1 against the world’s best Go player, was just such a pointer. On its own it’s interesting, but as part of an increasing number of stories it serves as a symbol of a new reality. Deep learning is increasingly being utilised for incredible and mundane tasks in our lives, and the pace is accelerating.
The impact of automation cannot be underestimated. Aside from requiring us to question the distribution of wealth – something I’m not going to tackle here – it will change the way we understand work. Those first impacted will, as always, not have the advantage of an organised response – for them it will be a hard-luck story to which they must adapt. So when we look at the current growth of driverless vehicles it’s not difficult to think that taxi drivers and truck drivers will be affected first. For these and other early impact groups, organisations and society at large will be disinterested. The extra efficiency will be applauded, the cost savings banked. The market may see new entrants, a few may go bankrupt, but for most companies it will be business as usual. The mistake, the same one made with computing and the internet, is to assume that the change will stop at these niche skillsets.
Listen to this Christmas song. Terrible isn’t it? It’s written by AI. I think it would be a bit ambitious to predict this one as the Christmas charts #1, but like AlphaGo, it represents Artificial Intelligence beginning to get to grips with activities that we assume to be “human”. The problem is that this is a blindspot for most people as they’ve become extremely relaxed with the nature of computers. This has led to a move of people away from the jobs in the firing line for “dumb automation” towards two “safe zones”: those who interface with computers, and those who offer skills that a computer can’t easily replicate. Both groups are under threat, though both believe they are immune. In my posts I’ll look at both.
I’m also going to look at different aspects of automation and the practical impact on the relationship between users and tooling in the workplace. I’ll discuss the assumptions we make when we first set out to integrate IT with user activities and how this needs to change for an automated world; how we can assist those affected in adapting; and the future of process engineering as the systems become more adaptable.