The future of work is here and it’s not all about robots!
People talk a lot about ‘the future of work’, but what does it mean practically for our job opportunities in the future? The term ‘future of work’ conjures up images of driverless trucks, AI medical practitioners and even the classic film I,Robot (because who doesn’t love seeing Will Smith save the world!).
While we know that the way we work and what we do for work is changing, how can we actually apply this to the way we approach our work and career?
On my millennial career we chat with Dr Julian Waters-Lynch about how the future of work will impact jobs and career planning. Jules is a lecturer at RMIT in innovation, organisational design and the changing nature of work. He’s a unicorn combo of creative, jazz musician, thought leader and academic.
Jules, what does ‘the future of work’ mean to you?
There’s a lot of different ways to approach this question but let me set out an idea to frame more specific responses.
Often the way this question is framed leads people to imagine ‘the future’ as already set – and discussing this is a matter of predictive crystal ball gazing. But many of us prefer to talk about futures, there is not simply one future to predict, but multiple possible futures based on the collective outcome of choices we make today.
So in thinking about the kind of tasks that will make sense for humans to perform in the future one of the most important places to begin is thinking about our relationship with technology. It’s also important to take a big history vantage point of this process, not simply be captured by the latest buzz about AI and robots.
For tens of thousands of years, humans have crystallised knowledge in the form of technology that has amplified our productive capacities, which in turn improves our capacity to develop more knowledge and further build technology. This process was gradual at first – our technology didn’t change very noticeably during the foraging era of our history, but once we developed agriculture that could support cities and more complex divisions of labour, we started to see more rapid progress. Things really began to pick up pace after the industrial revolutions a few hundred years ago, and we have started to approach a steeper part of this curve in the last 50 years – particularly with regard to information or digital technologies. With each major techno-economic paradigm shift, we see a major portion of a population eventually move from labouring in one area of the economy to another.
For most of history, most people were engaged in primary food production. Even just 120 years ago nearly half the US population was employed in agriculture, whereas that figure is under two percent today. So, the industrial revolutions triggered a shift in human labour from agriculture, towards manufacturing. Over the past fifty years there has been another transition away from manufacturing into services and knowledge work. Each of these major shifts amplified a different grade of human capability; agricultural tools made our ability to dig and plant more efficient than using our hands; industrial machines are far more efficient than human muscles; and more recently computational devices make many cognitive tasks far more efficient – just try and beat your calculator at arithmetic.
So, computing has been, as Steve Jobs was fond of saying, a kind of bicycle for the human mind – making cognitive labour far more efficient. And this is why it makes sense to keep paying attention to developments in computational capacity – Artificial Intelligence, Blockchains, 5G, Internet of Things, Autonomous Vehicles – because they are likely to shape all industries and their impacts could take effect rather quickly. Often there is a long period of deep infrastructural development where it doesn’t look like much is happening, and then things move very quickly at the consumer level – remember that the ‘smart phone’ is only 13 years old.
But the challenge today and going forward is to work out where human labour and our individual talents will add the most value to our economic system. Just as digging a hole with your hands doesn’t make as much sense as using a shovel or assembling a car manually doesn’t make sense if the process can be automated, routinely moving bits of data between spreadsheets will increasingly make less sense. This is what economists call ‘routine’ forms of work – where you’re turning up and essentially following the same processes each day, whether manual or cognitive tasks. As computational algorithms have improved, fewer people are required to work in these areas. So more human labour has moved into ‘non-routine’, but the better paid, and usually more interesting forms of work. These tend to involve ongoing learning, emotional and figuring out how to do new things.
So this ongoing relationship between the distinct kinds of value we add as humans and the productivity enhancing capabilities of technology, is how I think about ‘work futures’.
What skill sets do we need to have to respond to an unknown, rapidly changing world?
Well no one knows exactly what’s going to happen, so I think it’s less about planning for an ideal ‘future job’ and more about building an approach that will increase your success at whatever you need to learn, which will render you more resilient in the face of change. There are two things here that can be helpful.
The first is to think of your domains of skill as Venn diagrams. It’s very hard to be in the top tier of a single domain, but the more you position yourself at the intersection of a few areas, the more you narrow the field to stand out. And we’re starting to see this reflected in the way we discuss industries – not just ‘tech’ and ‘health’ but ‘HealthTech’ – for example. So asking yourself how you become knowledgeable in mental health interventions and ambient (voice controlled) computing puts you in a much more competitive place than one of these areas alone. And the technology vector moves so fast that there’ll always be an emerging frontier to learn about. I like Kevin Kelly’s line on this point, that given the pace of change, we all need to remain comfortable being ‘newbies’.
The second point is that thinking in terms of compounding is helpful here. In financial terms, compound interest is really remarkable – Einstein reportedly called it the eighth wonder of the world. But you can also approach learning and development in the same way – getting one percent better at something each day yields remarkable results over time. In a world where learning has to become a regular part of work, taking a ‘cram for the exam’ approach – where we put in extraordinary effort for a short time – doesn’t win over the long run. Rather, our daily habits are the key unit to focus on here, and the question to ask is whether they are optimised to best serve what we need to improve at given who and where we want to be. Almost all of us can gradually improve here.
You talk about the need to build up a tolerance for ambiguity. How can we do this?
As work moves away from routine forms – turning up to the same place every day at the same time and following the same set of procedures – we’re likely to encounter more ambiguity in our work. What’s the right thing to do next? The answer often isn’t clear. So learning to develop a tolerance –even a kind of appreciation – for ambiguity is an important skill.
While some of our orientation towards ambiguity is likely innate – related to fundamental personality traits– there are things we can all do to increase our comfortability here. For me, spending a lot of time learning to play improvised music with different people in a variety of settings has been very helpful here, and has translated across domains – from music to facilitation, teaching and public speaking. I think, for example, improv theatre classes – which are widely accessible without years of technical training (unlike jazz music), are a great avenue to improve your comfortability here.
Ok, so let’s talk about robots, AI and automation. Many people fear that they will lose their job due to AI or new technology. Do we need to be worried and how can we assess how our job will be impacted?
The more a job looks routine or ‘algorithmic’, the more vulnerable it is to outsourcing and automation. But in some ways a job is the wrong unit of analysis here. A job is really a collection of different tasks, which we approach by drawing upon different skills or forms of labour. As technology frontiers improve, some tasks within the job become easier to outsource or automate. Ideally this frees us up to direct more of our energy into the non-routine, creative parts of our jobs. My job as an academic essentially has three parts – producing research, teaching and public engagement through channels like this. If I just take the teaching part, there’s a small part of this that is highly interesting, creative, involves emotional and affective labour, like providing real time feedback to students on their work or discussing applying the ideas their studying to their businesses. I tend to feel this is most high value part of my teaching role too, both the most interesting for me and better experiences for students. But a great deal of my time is also absorbed in administrative tasks – dealing with enrolment issues, marking assessments, responding to the same questions via email over and over. If technology can intervene to reduce the repetition of these routine tasks, and free up more of my time to spend on the higher value tasks like real time interaction with students, this is a good thing. My encouragement is to think less in terms of ‘is my job at risk’. Instead, think more in terms of which tasks within my role might be automated, and which parts actually benefit from human touch. Leaning into the latter is a good strategy.
When it comes to future-proofing our career, why is vibe important and how can it help to create job opportunities?
We often appreciate people or things when they’re non-generic. People, products or services stand out in our mind when they’re non-generic, non-routine and surprisingly delightful. By bringing together an unusual and novel mix of experience and skills, you create a distinct and difficult to copy combination. Given our setting, podcasts are actually an interesting format to consider here. Joe Rogan, who has one of the most popular podcasts of all time, has a very distinct offering based on the combination of elements related to his experience – comedy, mixed martial arts, psychedelic drugs, and a willingness to engage in long-form conversations with a really diverse set of people in his quirky studio. Telling a 17-year-old to pursue those various interests as a career strategy would have sounded like the worst advice ever, but he’s been able to bring these disparate interests together in a way that people experience as a distinct ‘vibe’ that people clearly appreciate.
Using this word vibe might sound imprecise, but it can be useful to point to a distinct assemblage of elements. Vibe is often experienced as this ‘I can’t quite put my finger on it’ quality that is actually highly valuable when we think about experiences today. Why do you love this place? I don’t quite know, it just has this vibe about it… we often find ourselves using this word about people, places, products and services to refer to such combinations. So working out what this interaction between your personal and professional vibe is, which might soften the more commodified tone of notions like ‘personal brand’, can be a nice way to reflect on how you show up in a work context.
For more about Dr Julian Waters-Lynch, you can connect with him on LinkedIn.
