Beyond Prediction: Shaping Your Work Story in an Uncertain World
New research shows 7 dominant narratives on the Future of Work - from Dataism to the Singularity via Job Destruction. Which one will you choose?
Everybody has a ‘work story’ – what we do for a living and our career journey.
Researchers have identified seven dominant narratives shaping the future of work.
Which of these will define your journey?
I’ll explore these narratives, look for signals to support them, and ask whether they really matter.
According to Christopher Booker, there are seven basic plots that underpin almost every novel, movie, or even TV advert we encounter. Imagine your career as one of these archetypes:
Are you on a quest for purpose, overcoming challenges, or writing a rags-to-riches story?
We can’t predict the future, but we can predict your prediction
In the study researchers asked experts to rank the likelihood of predictions and the year they were most likely to happen. They landed on the sequence of events which included:-
2044: Surveillance societies become the norm worldwide
2051: Governments introduce universal basic income
2063: Technocratic elites start colonizing other planets
2065: All human qualities are surpassed by intelligent technology
So, nothing to worry about with these scenarios!
The researchers found that…
“…the tech entrepreneurs were radical optimists, the economists believed in rationality above all, and the authors and journalists held attitudes indicative of misanthropy and a belief that much in society is decided by those in power behind closed doors.” HBR.
This was an interesting finding - but maybe not so surprising. What I found particularly insightful was the authors summary of seven identifiable narratives on the future of work.
Seven Competing Narratives about the Future of Work
The authors identified competing narratives in terms of seven different schools, and below I have illustrated, amplified and added my take on each of them.
1 - Dataism - Trust the Algorithm
The Story: Data and algorithms dominate workplace decision-making, replacing human intuition.
Signals: Algorithmic management at Amazon warehouses. The rise of Digital Workers.
Extreme Future: The Quantified Worker – our personal AI agent tells us what to eat for breakfast based on our sleep patterns and work schedule…
My Take: This assumes data is neutral and infallible. Without scrutiny, we risk building systems that reinforce biases and strip away human agency. We will see more Quantified Workers, but only at the speed of trust.
2 – Exterminism - The Robots Take Over
"The factory of the future will have only two employees: a man and a dog. The man will be there to feed the dog. The dog will be there to keep the man from touching the equipment." – Warren Bennis
The Story: Automation leads to catastrophic job losses, creating a dystopian future.
Signals: Hollywood’s first AI strike highlighted fears of automation in creative industries. Studies predict millions of displaced jobs by 2030.
Extreme Future: By 2050, mass unemployment dominates society. Governments scramble to create universal job replacement programs.
My Take: This assumes humanity is static. History shows we adapt, ecosystems evolve, new industries emerge, and societies recalibrate. We must push for systems that prioritise fairness to prevent such extremes.
3 - Re/Upskilling - Learn or Be Left Behind
"The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn." – Alvin Toffler
The Story: Lifelong learning becomes a necessity to stay employable.
Signals: Singapore’s SkillsFuture framework for workers over 40. The rise of online education platforms like Coursera.
Extreme Future: Education becomes AI-driven, with personalised microlearning tailored to real-time job market demands.
My Take: Re/upskilling feels less like a narrative and more like a universal feature of all the others.
4 – Augmentation - Humans and Machines in Harmony
"The machine does not isolate man from the great problems of nature but plunges him more deeply into them." – Antoine de Saint-Exupéry
The Story: Technology enhances human capabilities rather than replacing them.
Signals: AI-powered surgical assistants improving precision. AI tools analysing case law.
Job Interview Question “I’m sure MIT was fun, but now tell me about the AI Agent team you use every day?”
Extreme Future: Brain-machine interfaces allow people to solve problems while dreaming.
My Take: This is a hopeful and practical vision. Machines as collaborators, not competitors should be our goal. However if only a few benefit, augmentation won’t fulfil its promise.
5 - The Singularity - When AI Surpasses Us
Story: AI surpasses human intelligence, transforming society.
Signals: Futurists like Ray Kurzweil predict this by 2045. Philosophical debates about AGI dominate ethics boards.
Extreme Future: Super-intelligent AI demands citizenship. People upload their minds to live digitally.
My Take: Fascinating but speculative - let’s first agree what ‘intelligence’ means?
6 - Job Destruction - The Death of Low-Skilled Work
The Story: Automation disproportionately impacts low-skilled jobs, exacerbating inequality.
Signals: Retail jobs disappear with cashier-less stores like Amazon Go. Autonomous trucking pilots in the U.S.
Extreme Future: Governments issue ‘transition stipends’ to keep displaced workers afloat.
My Take: Automation is inevitable, but inequality is a choice. This narrative is compelling but incomplete. It doesn’t account for the historical resilience of economies in creating new types of work, or how labour markets unbundle tasks and then rebundle.
7 - Work Deintensification - The Age of Leisure
"The end of labor is to gain leisure." – Aristotle
The Story: Technology reduces work hours, leading to more leisure and creativity.
Signals: Four-day workweek trials around the World. Advocates like Andrew Yang champion Universal Basic Income.
Extreme Future: By 2051, UBI is standard, and governments mandate digital detoxes.
My Take: Culturally appealing, but when will we stop tying our identities to work? This is the utopian narrative I want to believe in, but work deintensification would require significant cultural shifts and systemic reforms, which I feel far off in many parts of the world.
You can read the full paper with a link at the end of the article.
Poll: What Narrative Do You Believe In Most?
📊 Which narrative about the future of work resonates most with you?
Dataism: Algorithms dominate decision-making, sidelining human intuition.
Exterminism: Robots and AI lead to catastrophic job losses.
Re/Upskilling: Lifelong learning is necessary to remain employable.
Augmentation: Humans and machines collaborate in harmony.
The Singularity: AI surpasses human intelligence, reshaping society.
Job Destruction: Automation erodes low-skilled jobs, deepening inequality.
Work Deintensification: Technology ushers in shorter workweeks and UBI.
The Next Chapter of Research
While the study offers a useful framework, it’s not the complete story, as the authors admit. First, it’s based entirely on Belgian media, so they didn’t include Workforce Futurist! The seven narratives aren’t entirely mutually exclusive. E.g. Augmentation can be seen optimistically as an empowering narrative, while sceptics might question its feasibility or equitable access.
The Future of Work is What We Make It
The past was yours, But the future's mine. The Stone Roses.
When it comes to shaping our future work story, it is far too easy to become distracted by the many competing narratives out there.
"These competing narratives are not just predictions; they’re choices. By recognising the signals and shaping your own work story, you can decide how these trends impact your future."
The media presents a very narrow view of the future of work – the perspective is too local, or doesn’t reflect economic history, and lacks context and imagination. In other words it is wrong!
They are also too many fear-based narratives.
As I mentioned in my article below, looking at the past 250 years featuring Carlota Perez’s research, a golden age for work will only happen when there are positive visions.
“we would like to invite every citizen, every policy maker, and every manager and CEO to enter the public debate around the future of work to ensure that it unfolds within a social and democratic dialogue. The future is what we make it.” HBR
The seven narratives are not mutually exclusive—you don’t have to pick just one.
For Workforce Futurists, I would suggest :-
Understand and critique the dominant narratives in your industry
Shape your own narrative
Invest in flexible strategies for the future which,
links to your own financial independence, health and welfare.
The question here is not
“What will happen?” but rather:
“What kind of future do we want to create?”
What’s your narrative?
Tell me in the comments, or hit reply.
Future Reading
Dries, Nicky & Luyckx, Joost & Rogiers, Philip. (2023). Imagining the (Distant) Future of Work. Academy of Management Discoveries. You can download the full PDF article here
My views on five pathways towards building a better future of work - which of the 7 narratives dominate? 🤔
Capitalist Realism: Is There No Alternative? Fisher, M. (2009) This book critiques neoliberalism, framing the inevitability of current economic structures, and contributes to the understanding of the "There Is No Alternative" (TINA) mindset reflected in the narrative of Re/Upskilling.
The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI" (2023) Fei-Fei Li. In this book, Dr. Li delves into her journey in AI, she advocates for AI systems designed to augment human capabilities rather than replace them.
Future of Employment: How Susceptible Are Jobs to Computerisation? Frey, C. B., & Osborne, M. A. (2013) This foundational paper examines the susceptibility of occupations to automation - influencing the somewhat flawed narratives of Exterminism and Job Destruction.
Writing the next chapter of my future,
Andy
Thanks for sharing these insights, Andy. Very interesting read!
Dataism – your take: '(...) only at the speed of trust.' It seems that the threshold for trust is low, allowing the speed of acceptance to be high. The real question is whether humans are critical enough in assessing all the implications of this trust to balance technological advancement with human values.
Google Maps is a perfect example of this. By using Google Maps for navigation, individuals place their trust in algorithms fueled by vast amounts of data, guiding them more effectively than intuition or traditional methods. This reliance on data-driven solutions over personal experience is a hallmark of dataism. While the app has undeniably revolutionized navigation, it also highlights the need for a balanced approach to integrating data-driven tools into our lives. This involves challenges that extend beyond navigation and into other areas of human decision-making, such as:
Privacy Concerns: Continuous location tracking raises questions about how user data is stored, shared, and monetized.
Over-Reliance: Blind trust in Google Maps can lead to overdependence, diminishing navigational skills and geographic awareness.
Algorithmic Decisions: The app may prioritize routes or businesses for reasons users don’t fully understand, such as advertising or biases in the algorithm.
Ultimately, while data-driven tools offer undeniable convenience and efficiency, they also serve as a reminder of the need to critically assess how much trust we place in algorithms. As we increasingly rely on data to guide our decisions, it’s crucial to ask:
Are we allowing technology to enhance our lives, or are we letting it redefine our autonomy? Striking the right balance between embracing technological advancement and safeguarding human values will be essential as we navigate the future.
For a second, I read Dataism as Dadaism (the art movement that emerged during WWI). I was curious if we could draw parallels between Dataism and Dadaism.
ChatGPT helped me with that:
Dadaism: Asserted human agency by rejecting societal norms, turning the individual artist into a disruptor of traditional values.
Dataism: Risks diminishing human agency by over-relying on algorithms to guide decisions, from hiring to breakfast choices.
Parallel: Both highlight the need for humans to reclaim their agency. Dadaism did this through art; Dataism might need a similar humanistic counter-movement to ensure that data serves humanity, not the other way around.