AI has been around for years. Machine Learning is new, and cooler. You can tell because we now call it ML and nod, and pretend we know what people are talking about.
In our recent interview with Openet CEO Niall Norton, he talked a little about AI and summed up our feelings (and where we are with AI) by saying this (we were talking about input devices):
A keyboard will just be less of a ‘thing’. I am not sure I will be talking to my oven but I talk to my Google device, while I am cooking, to play what my son calls ‘old man’s music’. That kind of ‘faux’ AI will become more engaging over the next two to three years.
‘Faux’ AI is a great expression (and will get a lot of use here at Disruptive.Asia). It sums up the feeling that, while it is useful, it also overhyped and, well, faux.
If you write for a tech publication, you spend a fair chunk of your day scrolling through various feeds and channels, looking for something to comment on. Today, what stood out was just how many of these channels said things like ‘AI to revolutionise Content Marketing,’ and ‘AI deployed to win cyber wars’ and ‘AI to revolutionise Education’.
Yet, actually, in reality, gloves off – where exactly are we with AI?
The answer is that we are probably on the cusp of seeing real benefits. This decade will see industries adopt AI wholesale. For the first half of the decade we will see benefits that are brought about by AI engines being able to spot patterns faster and more effectively than any computer based algorithm to date.
AI is revolutionising HR, perhaps not in a good way. If you know that a bot is going to be the first hurdle to getting an interview, you Google how to write a CV for a bot and go that way. You take your humanity out of your CV. The same already applies to articles on a web site. Instead of being able to write an article and publish it, if you want Google to rank it so you get more hits you have to mention the keyword (AI, AI, AI) a certain number of times, have it in the title and in the first paragraph and, essentially, you have to accept a robotic editor that has the literary skill of a Panda.
Sifting through large amounts of data is very useful, if sometimes misguided. Healthcare is probably the arena that will see the most useful advances in the next few years. The ITU believes that because of AI, ‘the healthcare landscape will completely shift in the next few years’.
And we agree.
AI – the faux kind – needs to get better so that Niall Norton will use it for more than playing ‘old man music’. It will be the equivalent of the advances in the world of computers over the past 30 years. AI will get better at processing data and, for the most part, that is all.
It remains to be seen what will happen when and if we reach the next stage where neural networks begin to mean things.
What we must always remember is that, as in computers over the past 30 years, if you put garbage in, you will get garbage out.