Getting ready for a digital workforce

Artificial Intelligence is the new buzz word on the street and like its cousin, Digital Transformation, it is causing quite a stir. From harvesting people's data to stealing people's jobs, or on a more positive note, detecting likely medical conditions with greater accuracy and teaching itself game strategies in Go that no single human has ever experienced – the uses are wide, deep and varied.

It's a complex area and one to most outsiders that looks too hard to even begin digesting. Here are three of my main observations.

1. Automation vs Intelligence

Artificial Intelligence is often mistaken to be the same as Automation (Robotic Process Automation to give it it's full name) but they are two very different entities.

RPA is typically about taking existing process and replicating them exactly as is but with the goal to reduce error rates by taking the human risk factor out of a series of often mechanical or procedural steps - low in complexity and high in volume.

AI on the other hand is about exploring the art of the possible, often guided by human intervention but increasingly without that bias. The results of AI are typically brand new ideas, revolutionising the way things get done with efficiency of time, resources and cost built in. AI is arguably a maturity of Automation but, like a lot of hype, it is easy to jump in at the deep and ask why later.

Typically, to automate however is significantly cheaper in implementation, and with returns seen more quickly, than AI which usually has a big upfront cost and a longer return horizon. If organisations have a clear intent on AI and the business benefit, a good emergent change step would be to mature through to AI using increasing automation – evolving the computer based ‘workforce’ to tackle the 60-80% of workload.

2. Giving a 110% - The Automation Paradox

AI leads to both a possible reduction in headcount (for bottom line focussed programmes) and / or a heavy focus on picking up "higher value" tasks (for the more evolving business change programmes) but it doesn’t remove all the risk. Automation changes the roles and responsibilities we have, redefining in two ways 1) undertaking new responsibilities AND 2) resolving issues when the automation doesn’t work. So automation is far from making humans lazy, it is about making us more alert and more resilient to the things happening around us – not something that comes naturally to us when technology innovation comes our way.

Think of a modern day airline pilot, 95% of flight time is controlled by the autopilot but it doesn’t remove the need for knowing how to fly a plane or restrict their learning to take offs and landings (where the pilot is actually doing something). The role has evolved to need to anticipate and react to issues for which the automation was not designed as well as picking up new responsibilities to ensure the safety of the plane and it’s passengers, before, during and after the flight. In essence, the automation replaces like for like the human resource to complete the task but only partially removes the risk - the remainder belongs to those left doing the new job. I think this is a nuance that is misunderstood – you only have to look at the autopilot equivalent for the average Joe, the sat nav. People do become less alert, more lazy and hence, when things do go wrong, panic, fear and ultimately accidents still do happen. It is important that the personal responsibility we all take for adopting technology into our lives isn’t undermined when it gives us the freedom to do more with our time.

The good news is that, maturing from Automation to full AI for the majority of organisations allows roles and responsibilities to evolve with the maturity of the workforce – helping people move along the change curve more naturally and giving decision makers to time to establish the right support tools, assuming they join up the dots.

3. The slave becomes the master

I grew up when the terminator genuinely struck me with a little fear – so forgive me for being a bit melodramatic on this next one!

We create technology to enable humans to do more. Go further and faster whilst using less to get there - it is an enabler of greater efficiencies, as Steve Jobs "bike for the mind" analogy reminds us. The thing is, for once the technology can do more than we ever intended it to and on occasion we won't even know how it did. When Alpha Go can learn more in 3 days, playing against itself, than humans have done in 3000 years and only armed with the rules of the game you have to wonder what AI could do in some less benign contexts (no offence meant to human Go players)

Think of your favourite pet for a moment. If over the course of the next 5 years, said pet, began to evolve intelligence to surpass human capabilities then we would feel pretty threatened. Possibly even thinking about some drastic actions for little old Fluffy. In the case of the AI, who is governing the progress of AI and even if we put so called "circuit breakers" into the AI environments - can we be sure they are strong enough that a computer capable of teaching itself won’t find a way around. Can we ensure it stays within bounds that don't put it at odds with humanity? Dun Dun Dahhhhh!

Final word

However you look at it, Automation and AI are set to completely redefine what we know today as work. There is no doubt then that with AI, job roles will be reshaped beyond recognition meaning that

We (the humans) will be forced to continually evolve our skills, whilst retaining core knowledge, beyond any pace we have experienced before and more persistently throughout our careers. Failure to do so, places us at greater risk when the tails of probability come up more often than modelled.

The government, via education and industry, will equally need to adapt policy and procedure to ensure a seamless transition through the evolution of increasingly digitised workforce.

For change managers, helping organisations focus on developing new skills in their people will take greater focus but we will also need to be well versed in these technologies, their bounds and the impacts they have on human behaviour to ensure we can help create a world where human and digital work forces mesh seamlessly together.