As an AI company, we have a responsibility to keep on eye on the future of work. According to a report by PwC we are largely in the ‘first wave of AI’ where rules-based algorithms, often applied to deliver personalised recommendations, advertisements or business insights from ‘data lakes’ – repositories of every kind of information an organisation generates. This period is expected to be completed by the early 2020s before moving on to the ‘augmentation’ stage by the middle of the decade, concluding with a third wave of ‘automonous’ AI, which is self-learning and can operate successfully for long periods without human guidance. You might think of this as a move from personalised playlists to autonomous cars. That’s quite a progression for the future of work.
How this will affect the jobs market, in general, is best viewed in the spread of jobs that can be taken completely out of the hands of human workers. In the short term, the outlook is pretty good, with only 3% of jobs across professions threatened by automation by algorithms. Under the augmented period we are staring into, this rises to 19% during the augmented wave and a startling 30% during the autonomous wave.
At Galvia our technology delivers ‘decision intelligence’ by delivering actionable insights through bespoke dashboards focussing on what you want to focus on. Our solution is scalable, so it can maintain performance regardless of how quickly your company grows.
We have found that chatbots encourage users to engage with data and information resources, saving time at the client side and delivering a better customer experience.
In our work with the University of Galway, Ireland we developed a chatbot solution we named Cara (Irish for ‘friend’) and was intended to handle basic questions about student services. Our experience delivered two fascinating statistics: that the number of tasks considered ‘mundane’ tasks dropped by 40% and that 84% of queries dealt with by Cara were resolved instantly.
This is not to say that unemployment lines will be filling up by the end of the decade, more that in the future of work, the kind of work humans do will be changing, thanks to AI. Think of it more as an assistant than a colleague or manager.
ChatGPT: The absent-minded co-worker
A few years ago everyone was asking whether the future of AI was in digital personal assistants. Academics and IT departments were excited by the possibilities of IBM’s Watson. That conversation has moved on more from how AI can organise what we know and do already to how it can help us learn and strategise, as well.
Ask anyone today about AI and they want to know how ChatGPT (generative pre-trained transformer) will change fields like art, code, and even marketing. The idea of not just finding something out, but having entire bodies of work reproduced on command is the stuff of science fiction and now it’s here – all you have to do is ask through a simple chatbot interface. Mind you, the question is how to find the best way to ask what you want instead of assuming you’ll get it.
ChatGPT has taken up much of the conversation around AI since its release last November, as much for the limits of the technology as what it can add. For as much as educators worry about students submitting AI-generated essays, or magazines putting a halt on submissions owing to an avalanche of AI-written stories it should be recognised that for the moment such material suffers from a number of problems – some of them serious enough to adopt a conservative approach to using it. Despite some progress, the problem of hallucinations – where the system creates text that is structurally correct but factually nonsensical – can be a deal breaker. You can ask ChatGPT to do your homework but you will need to do so much fact-checking that it might be easier to do the basics instead of putting in effort circumventing the assignment.
Errors and omissions aside, ChatGPT can be an excellent sidekick if you know what exactly to ask of it. For this reason, there is a growing body of articles such as this about the best prompts to get ChatGPT working for your team. You’ll find it a mixture of the fascinating and the frustrating – a bit like an absent-minded but occasionally brilliant colleague who has been stuck a few years in the past.
What it means to the future of work
The key to good AI is, always, the quality of data that goes into the platform. When it comes to finding good information to base a decision around you won’t find much better than that circulating around your organisation.
Using historical data to predict future performance and business intelligence platforms do an excellent job of what worked in the past or is going on right now. The challenge is coming up with ways to predict performance based on factors outside as well as within your control.
In the future of work when AI joins your team don’t get worried, let it do the simple stuff so you can get better at the things that matter.