The Paradox of Progress (Part 1)
Why AI Feels So Uncertain and Why I’m Still Optimistic
Before diving in, a quick note: AI is much bigger than generative AI, but most of what I’m sharing here focuses on the past few years, since tools like ChatGPT launched in 2022. The Fourth Industrial Revolution has technically been underway since around 2015, driven by cloud computing and automation. But it wasn’t until generative AI started to be widely adopted that the Fourth Industrial Revolution’s impact on jobs, markets, and daily life was really disruptive.
Making Sense of What’s Happening
Over the past few months, I’ve been hearing from lots of friends and colleagues who’ve been caught in this latest wave of layoffs. Many are anxious, wondering if they’ll ever find another role and how they’ll support themselves and their families.
One colleague sent me a posting for a senior engineering position that had over 1,000 applicants!! I can see why so many people are feeling discouraged and anxious. Today, I want to share my interpretation of what’s happening and how I think about this moment in time. Tomorrow, I’ll share a few things you can do to help you stay calm, focused, and prepare yourself for what’s next.
Every Revolution Feels Existential
One of the things that I did during my last few years at Microsoft was speak to community leaders about the Fourth Industrial Revolution and the impacts and implications that this would have on their community.
One of the points that I made is that EVERY industrial revolution has followed the same pattern:
excitement -> fear -> disruption -> reinvention.
When the steam engine first appeared, it transformed the way work was done; instead of humans or animals providing power, machines provided the power at a significantly lower cost. And of course, there was resulting fear that people would no longer be needed. Decades later, electricity and the assembly line reshaped production again, driving scale and efficiency but creating a lot of anxiety about who would be left behind. Then in the mid 20th century, computers started to be introduced into factories and offices along with the fear that certain roles would be replaced. (A great article on this can be found here: Automation on the Job | American Scientist.)
While the pace of change of the Fourth Industrial Revolution seems to be faster than any proceeding revolution, there’s little reason to believe it will follow a different pattern. If history is a guide, we’re simply moving through the familiar middle stages, somewhere between fear and disruption but on our way to reinvention.
Each wave of innovation changed the meaning of work. Some jobs disappeared and were replaced by new technology but in their place, and in each case, new kinds and unexpected kinds of work was invented. People learned new skills, found new ways to create value, and built entirely new industries. Every revolution changed the definition of work but created new roles with far more opportunity than the one before it. And it’s worth noting that even though there are short term and regional fluctuations in the unemployment rate, the long-term global unemployment rate has remained between 3% and 6% for the last two hundred years.
The Paradox of Progress
One of the reasons that industrial revolutions don’t reduce the number of jobs is that When technology makes something cheaper or more efficient, we consume more of it. That increase in consumption creates new demand, often new industries, and new types of jobs. Economists call this the Productivity Paradox, or sometimes Jevons Paradox.
During the First Industrial Revolution, when machines powered by steam made production faster, factories multiplied, output soared, and demand created entirely new kinds of work. The Second Industrial Revolution brought electricity and the assembly line, transforming manufacturing. Production became faster, cheaper, and with higher quality, and created demand for new roles in engineering, design, logistics, and management. In the Third Industrial Revolution, when computers and digital systems made information cheaper, we turned more data into more information and information into insights and of course and built entire industries around data and software. And now, in the Fourth Industrial Revolution, as AI lowers the cost of intelligence itself, we’re finding new ways to apply that intelligence, new problems to solve with it, and new work to build around it.
The AI Hype Cycle
When ChatGPT launched publicly in November 2022, it triggered one of the fastest adoption curves in history and an even faster fast wave of expectation. Within months, generative AI became synonymous with AI itself.
According to the Gartner Hype Cycle, this is what happens with every major innovation:
Innovation Trigger: A breakthrough sparks excitement.
Peak of Inflated Expectations: Everyone races to apply it everywhere.
Trough of Disillusionment: Reality sets in — it can’t do everything we imagined.
Slope of Enlightenment: Real learning begins.
Plateau of Productivity: The technology quietly changes everything.
Most technologies follow this pattern. They surge to the peak on a wave of excitement and then descend into the trough when reality catches up. The crash isn’t caused by the technology itself, but by our unrealistic expectations of what it could do and how quickly it could change everything. Right now, AI, particularly generative AI, is somewhere between the Peak and the Trough in this model.
Why I’m Hopeful
We're in a challenging time. It's not just about the technology, t's about our responsibility. Questions about AI's impact on things like energy use, bias, and trust are forcing organizations to think carefully about how they build and govern this technology. But this brings a huge opportunity.
I believe that over the next decade, there will be a huge increase in demand for data scientists, engineers, and QA specialists who can design and test AI systems safely. It will also create new roles for AI ethics, sustainability analysts, and policy leaders who will help ensure these tools are used responsibly. We’ll need educators, communicators, and designers to help people learn, adapt, and use AI thoughtfully. And it will increase the importance of leaders who can manage this innovation and its impact on society.
Yes, the nature of work will change; it’s obviously already happening. With every industrial revolution before this, we adapted, evolved, and built something better. So, if you’re feeling anxious now, you’re not alone. When your job is at stake, change always feels personal and stressful. But we have every reason to believe that like all preceding technical revolutions, this is where opportunity is created.
To paraphrase Winston Churchill, 'This is not the end. It is not even the beginning of the end. But it is, perhaps, the end of the beginning.'
Today isn’t the end of something; it’s the beginning of what comes next, which I think is a new period of innovation, human creativity and of social responsibility. The technology is changing fast as is the associated disruption, but the opportunity to learn and to lead is still ours."
In Part II , I’ll share a few practical ways to navigate this transition, how to stay calm, reposition your value, and see the possibility in the middle of this disruptive change.