I’m going to start this piece with a confession; I am a ‘trend’ skeptic. Over the last few years I’ve developed something akin to list fatigue; growing weary of the constant stream of ‘six things you must know’ clickbait headlines that pop up in my feed.
If I was being kind I would say that as an industry we are sometimes guilty of exaggerating our predictions on the potential impact of emerging technologies. If I wasn’t being kind, I’d probably say that in truth a lot of our industry habitually over-hypes everything ‘new’ so that anything actually meaningful gets buried in the noise.
AI is not a trend, it's here already, and although its utility is still emerging in places it is undoubtedly here to stay.
Artificial Intelligence (AI) is one of those topics that you’ll regularly have seen on lists throughout 2016. And editorially, it’s fair to say that it’s been covered across a pretty broad spectrum. A quick Google search will either lead you to an article where AI will bring an end to the food going off in your fridge, or where AI will bring an end to humanity.
So, what do I think? Well firstly, let me say this, I certainly believe that the application of AI is a watershed moment for technology similar to the transformative power of the early years of the Internet.
I’m also of the opinion that the most helpful way to define what AI is at a high level, is to think of it as a tool. In this sense, how we, as designers and practitioners, choose to deploy it in to our lives will ultimately dictate how useful, useless or indeed dangerous it becomes. This idea of application through design is represented in the microcosm of ‘innovation’ that is CES. AI is a thread that marketeers weaved in to many product stories during this show this January, but the utility of those products stretched from the sublime to the truly ridiculous.
Design in the age of AI
As our understanding of what we can do with AI (not simply what AI can do) evolves in 2017, I’m excited to see designers catch up to the tech. In January, Yves Béhar spoke at the inaugural A/D/O/ Design Festival in Brooklyn and introduced 10 Principles for Design in the age of AI. (Rather than regurgitate it here, you can find the full list here). Much of what he eloquently spoke about crystallised in my mind some of the key themes that I myself was musing on throughout 2016; the importance of solving real human problems. The need for AI to enhance, not replace, human ability. And, the concept of good design creating relationships with technology, but not dependencies.
Different flavours of AI already power some of the everyday products and services you may use; Google Translate, your Netflix recommendations, even the running of trains on the London Underground have all had a recent intelligence ‘kick’ by introducing AI and machine learning into their core programming. It’s fair to say then that we are well beyond the question of ‘if’ AI will become common place.
Perhaps the more immediate question facing us is what what principles and thinking will govern exactly 'how' we want AI to change things.
That specific question of ‘how’ the exponential growth of AI will affect the future was one of the primary discussion topics that dominated Davos 2017. Discussions hot on the agenda at the annual World Economic Forum Annual Summit included how the huge anticipated levels of automation via AI will impact jobs, how the world will address the emerging skills gap that the exponential speed of AI growth will inevitably drive and how we will govern exactly who and how machines are trained in the first place.
So, what next?
It’s fair to say that the full picture and answers to these questions aren’t things that we’re going to have conclusions on overnight. Much like the early years of the Internet, no-one can accurately predict how and where AI might take us (remember what I said about being skeptical of trends).
However, my mindset for this year will be framed by two key thoughts:
Firstly, as with any tool, it makes sense for us to focus on the utility of what we can make and discuss the principles that then govern our making. Yves Béhar’s list would seem like a good place to start.
Secondly, there is no clear reason that our outlook needn’t be optimistic when it comes to AI. Anything truly disruptive will clearly come with economic and societal challenges, but surely it’s how we navigate those changes positively that is the real challenge and price of progress.
This piece originally appeared in The Drum in February 2017.