Flying Blind: Into the Future of Work

In light of recent developments in AI, many people, organisations as well as public institutions have been asking the question how work and its requirements will change in the future. And there have been many attempts to answer this question, or even predict future work demands so we know exactly how to prepare and adapt to these changes.?

Already in 2021 BCG wrote in their piece “The Future of Jobs in the Era of AI”, that

“in order to ensure that they are prepared for the jobs of the future, individuals will have to take greater responsibility for their own professional development” …and that they should “make lifelong learning the new normal. Whether through programs offered by employers or through private channels, continuous learning and the acquisition of new skills must become central to an individual’s working life. Individuals should also invest not only in digital skills but also in metaskills, which will serve them well regardless of shifts in the market”.

But of course such a generalised statement is easily made, forgetting that there are actually much bigger, systemic, social as well as institutional challenges humanity is facing when it comes to preparing our future workforce. Given the complexity of these challenges, no one is expecting a swift or simple solution, but of course that does not mean that we have to fly blind into a completely unknown future of a new type of work, whose characteristics will most probably have been fundamentally altered by the radical pervasiveness of an omnipresent, ambient AI infrastructure. If we are to trust AI - which we should never do blindly - then the following jobs are at risk to be replaced, or looking at it more optimistically, “enriched” by AI:

It is in light of these impending changes that the following thoughts should be understood, not as a definitive or comprehensive roadmap but rather as five points of orientation for a new work environment, one where your traditional education and your well-thought out career plan doesn’t matter anymore, because the job you came to do, does probably not exist any more*, or it has changed so radically that it might be easier for you to find a new one. OK, buckle up, here we go…

1. Stop relying on Tricks, Tools & Short-Cuts. The new era of AI-empowered work will have such a high background-level of advanced AI-assistance, that almost anyone with a basic literacy level can tap into tools which can give you output which will excel anything we have been creating so far manually. Whether it is writing, design, music, calculations or anything else a generative AI is capable of: relying on specialist tools will not be enough in a new age where almost all tasks which until now have been too complex for computers to manage can easily be accessed by anyone at the click of a button. And it is exactly this democratisation of information which will make simple, tool-based expertise almost laughable, especially as these new AI-tools will evolve and progress so quickly in their functionalities, that there is no point trying to specialise in any of them. Key insight: Instead of specialising in the use of specific tools - think skill descriptions like “Advanced Excel skills, basic understanding of Photoshop, …” - you should rather consider developing highly relevant and much sought-after “meta-skills” like “advanced combinatorial design capabilities using generative AI tools such as DALL·E, Midjourney and Huggingface”.
2. Quality over Quantity: As in all other advanced skill-based markets, there will be a huge divide between low-skilled and highly skilled information workers, significantly increasing the pressure on the “mediocre”, averagely skilled workforce, who will eventually be pushed out of their jobs as their jobs will be increasingly automated over time. Statistically speaking this means that there is a massive need for upskilling the majority of today’s workforce unless they will accept to retire early or fall down into a much worse remunerated sector of what we have already started to get to know as “gig economy”. Key insight: Start building up your skills by learning and experimenting with AI tools in your area of interest. Because there is no better investment than in your own skills, or as Warren Buffet has famously put it: “The best investment--by far--is developing yourself”.??
3. Emphasis on Subject-Matter Expertise: Specifically in light of the shortcomings of AI including its lack of understanding of complex matters such as causality, context or social expectations, the future work context will have an exceptionally high demand for subject matter experts with a deep actual understanding of the inner workings of any given field or industry. Unfortunately this means that it is not abstract knowledge any more, which will matter in the future, but only actual experience based, applied, empirically tried and tested knowledge that can stand the test with reality. It is this kind of applied knowledge that will make all the difference in making output practically useful. We will hence need respective subject matter experts with such knowledge to guide any AI applications towards generating output that will create practical value in real-world applications. Key Insight: Get your hands dirty and start to learn more by actually doing things yourself and don’t just repeat what you have read somewhere else. This means that you have to get comfortable with getting uncomfortable, especially by making mistakes, suffering set-backs and investing long hours until you get solutions to work in the real world instead of just referring to abstract second-hand knowledge. Or in short: #neverstoplearning by #failingforward
4. Develop interdisciplinary & cross-domain Thinking Skills: In the old age of traditional careers and clearly defined disciplines, it was enough to learn whatever your specific curriculum included, pass a final exam, and then rely the rest of your career on that knowledge, which you would demonstrate by having a fancy certificate on your office wall. The recent developments in AI have however shown that these times are over, specifically for disciplines which were essentially never relying on real skills, but more on formalised training and government-led approval processes. It is safe to assume that in the new era of AI-enhanced work, these will be the jobs which will be automated first. This is however no reason to complain, because at the same time we are embarking into a future of multiple complex challenges, including non-trivial, interconnected issues such as sustainability, energy stability, economic resilience, health & wellbeing, international politics, and many more. And in order to develop solutions to any of these complex challenges, we will not just need isolated, domain-specific skills but cross-functional intelligence, which can connect the dots and think of radically new, original solutions. These are exactly the type of skills no AI will ever be able to demonstrate, because it lacks real, active and original thinking (see also point 5). Key Insight: Stop thinking in silos and artificially isolated disciplines and domains. The world is more complex and requires you to draw upon all the knowledge available and bring it together in a practically useful, consilient manner. You can however only do that if you dare to look over the edge of your traditional, well defined and well kept area of your own little garden and have a peek what’s beyond.???
5. Curiosity & Creativity as complementary Key Skills: In this new work environment of pervasive “Ambient AI”, data will become ubiquitous, so that it will all come down to the most advantageous recombination of freely available information in order to solve any actual challenge in the most effective and efficient way. As can be seen in the increasing adoption rates of digital platform technologies since the invention of the internet, we will likely see another such “fulguration moment” with AI-powered information becoming a ubiquitous resource upon which any new digital solution will be able to draw and build on. This will effectively make our own curiosity and creativity the only bottlenecks, but at the same time also the actual superpower, which will decide how far our AI-powered information muscle will be able to reach. Consequently, our own imagination will be the only limitation to what will be technically possible. Key Insight: Stop limiting yourself to what exists and start to develop new, original and better solutions based on what you can imagine to be possible. Be as much an artist as you are engineer / manager / technician.. Or to put it like Einstein: “Imagination is more important than knowledge. For knowledge is limited, whereas imagination embraces the entire world, stimulating progress, giving birth to evolution.”? ?

* Even ChatGPT does not seem to suggest that AI will simply make jobs redundant: