Will AI turn everyone into an entrepreneur – Financial Shenanigans #2

Thinking about AI and the future of work.

At the beginning of 2019, I wrote an article about AI and its impact on the future of work. My thoughts were based on several books and papers, as well as the in-depth research for the article itself.

I wanted to revisit some of that research as it played a role in my decision to opt-out from the existing labour framework and pursue my own path.

Back then, the subject of AI and jobs seemed less urgent. But the pandemic has forced the issue by rapidly accelerating the adoption of job-disrupting technologies. The nature of COVID-19 also clearly exposed the gaps in our society and, arguably, further entrenched them.

In 2019, I believed that the AI-driven changes to the job market, once underway, “might be too much for the social fabric of our society”. The current labour market stress has made it crystal clear that we don’t have the necessary societal, economic and political structures to excel in the new environment. And the main effects are yet to be felt.

The World Economic Forum coined the term “Industry 4.0” to describe the Fourth Industrial Revolution in 2016. It was meant to signify significant structural changes in the way we do things. Since then, many people have argued that we have seen this movie before. And that every time, we have successfully adapted to the changes. Historically, from the first industrial revolution through the digitisation of the late 20th-early 21st century, the impact on jobs has mostly been positive. New technologies eventually created more jobs than they eliminated. I find that this argument has serious flaws.

In my view, the current wave of technological disruption is different, for the following reasons:

  1. Speed of change – simply put, the rate and the velocity of changes is much greater than before. Less time between major innovations and scientific breakthroughs. More significant impact and consequences of climate change. The list goes on. This is forcing precipitous changes in the way we live.

  2. Funding ecosystem – also known as the “too much free money” problem, courtesy of the Central Banks around the world. That money is funding innovation at a magnitude not comparable to history. Not only that, but near-term profitability is no longer a criteria for securing funds.

  3. Infrastructure required for adoption – it is much easier and cheaper to upgrade software than hardware. Take Tesla as an example. According to Musk, the hardware (i.e. the car) is already capable of supporting fully autonomous driving. What will get us all the way there is software updates. But you don’t need to ever buy a new car to participate in the upgrade cycle.

  4. Economic cycles – the essence of this argument is that major adoption cycles coincide with recessions. Big businesses, in their aim to cut expenses, lay off a lot of people and pursue efficiency through automation and technology deployment. Those old jobs never come back. The COVID-19 cycle is no different.

Now back to how this affected my thinking on my own career path. First, not having a full-time job allows you to quickly pivot the strategic direction of your “career”. It simply is much easier to acquire new skills. Second, it forces you into a proactive vs reactive state of mind as there’s no longer a safety of a steady paycheck. And third, it puts you ahead of the curve. The nature of AI-driven changes will push more and more people into this location independent, on-demand, potentially entrepreneurial work environment. It’s nice to test it out before it becomes a necessity. In some way, this approach or mindset is comparable to being an agile start-up vs an established corporation. Although we clearly don’t know if this start-up will upend the existing industry or prove to be a futile attempt to change the status quo.

I understand that many might disagree with my hypothesis. But whether we agree or not, some contingency planning has never hurt anyone.

P.S. For those so inclined, you can read the full AI article here.

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