The slightest mention of AI and machine learning (ML) was enough to strike fear into the hearts of many not so long ago.
To be fair it’s not surprising, particularly given the cultural references we’ve been fed over the years – see Skynet (Terminator), Hal (2001: A Space Odyssey), and Ava (Ex-Machina) – it’s little wonder there’s been a smidgen of anxiety.
However, in recent times, technologists have started to acknowledge that AI and ML are actually good at automating the laborious processes we as humans and businesses can’t be bothered with – most of the time they do this more accurately too.
The question still remains though, do we really have anything to worry about when it comes to automating our working lives via ML and AI?
Why we automate
Taken on the findings of a recent PwC report, there’s still some substantial negativity among the general population when it comes to automation, with 60% of people believing that it will take their job (and there are further concerns raised when you start to mention the AI elements). That is really two questions in one though: can we automate everything, and can we make that a full end-to-end process?
Well, we automate for multiple reasons: repeatability, speed, parallelism and removal of operator error. All of these are great reasons; cloud computing followed that evolution only recently and now we have the ability to commission, configure, deploy and make available entire estates in minutes.
After all, whenever we see a branch of computing become popular, we seem to go through a similar curve of manual implementation; then often into a UI to make things easier; then into scripts that get things running manually (but repeatably); then into fully automated processes, and finally the automation of the quality gates around it.
In the last few years alone, we’ve seen that automation has branched out from the early automated builds and unit tests into Security, UI testing, infrastructure, deployment and even regulatory compliance to name a few. Not all of these branches of automation are currently leveraging AI, but over time I predict they will.
Of course, where there’s AI and automation, there’s always the worry that it will somehow “take our jobs”, when often the opposite is true (with a caveat), as when we can deliver more consistently, business value is unlocked sooner and programmes are more likely to succeed and expand.
Unlocking value, unlocking headspace
Unfortunately, some jobs will become obsolete in the short term as a result of automation – the World Economic Forum predicts as many as 85 million in fact. However, according to the same research, 97 million new roles will also be created.
Automation in the form of RPA2.0 (which leverages AI and ML, hence the 2.0 moniker) is an example of a tech that’s already doing a lot of the work that people really don’t want to be doing. The time-consuming chair turning that distracts people from giving a good, personal service to customers could be numbered as a result of its rollout. During the pandemic too, we saw a 58% increase in intelligent automation programmes of this kind – ironically enough, we actually didn’t see a dip in the number of roles required in these types of customer service jobs though.
For the most part, automation only ever seems to come after we’ve solved the problem in hand, and understood that problem thoroughly enough to be able to turn it into an automated process. Although many companies have implemented a full Continuous Delivery lifecycle, there’s almost always a person between chair and keyboard writing the artefacts to be delivered.
In reality, automation is just that, it’s not doing the thinking or problem-solving for the most part. Sure, as automation starts to embrace more elements of AI and ML (especially in the fields of Security and RPA2.0) it isn’t just an imperative set of steps anymore, but it will still need the human touch, at least in our lifetime.
Have no fear, seize the opportunity
AI based automation will, in my opinion, keep freeing us of the tedium of repetition as our industry grows, giving us back that time we so desperately need to think more strategically, but we will need to be flexible and learn new skills along the way too. It’s not going to do all the work for us after all; we still have to correctly model the systems in which it operates.
The famous economist and Bloomsbury acolyte, John Maynard Keynes once predicted that technological change would lead to improvements in productivity for all. In fact, he said we’d all be working a 15-hour week as a result. Although I’m not expecting such a technological revolution in my lifetime, I certainly think AI based automation will provide each and every one of us with the much needed headspace we crave to improve and optimise our working lives.
About the Author
Jeff Watkins is CPTO at xDesign. Specialising in bespoke mobile and web app design and development, we offer complete custom digital and mobile app solutions. We’re not afraid to strive for the very best and push boundaries to ensure our clients achieve the best possible result. We are a team of ideators, designers, developers and data scientists that work as a cohesive team to add phenomenal value to your project. We work with you to make sure we understand your company and its clients, and help deliver the very best digital tools for your business. We are intent on delivering return on investment and we innovate with design and new technology to ensure we are always on the cutting edge. To find out more about xDesign, visit: www.xdesign.com
Featured image: ©Siarhei
