Last Tuesday I held a presentation on the Meaning of Work to a group of students, and I was captured by the number of questions I received on the topic of Automation, Artificial Intelligence and their impact on Work.
It’s a topic that has always fascinated me, but until now, I also could not find a reading key that would be useful to understand what’s at stake truly.
On one side, I grew fascinated by the Transhumanistic view of Kurzweil’s Singularity
. But the question arose: what will humans do if robots do everything?
On the other side, I was reassured by the views on Artificial Intelligence (or rather, the lack of Intelligence in AI) by Luciano Floridi
. But then, what’s the danger in developing technologies that are never going to be truly Intelligent?
Today, with my reflections on The Meaning of Work
, I got a new layer of understanding, and probably, I can share a first provisional conclusion.
Yes, AI is probably coming to take most of our jobs.
The reason is simple. Jobs are created as the result of an engineering process, assembling tasks and responsibilities to achieve maximum efficiency. Technology is currently working to ensure that machines are more efficient
than humans strictly at these tasks. And the truth is, that AI is going to be incredibly impactful in a lot of jobs we assume are complex. Accounting, legal, procurement, engineering, medical diagnosis are just examples. You can check online what is the risk of your Job being taken
Fact is that where tasks can be automated through the application of deterministic processes, the risk of Automation becomes higher. It is especially true for a lot of the jobs mentioned above, because these are expensive, and it justifies investments. I doubt we will see soon robotic servants in-store, or robotic cooks at the nearby fast food. Why? Because labour is so cheap at this level, the incentive to automate is too low.
Pretty ugly picture, uh? Well, we’re not yet there in reality. In many contexts, Automation is proving to be much harder than expected. We should all have been driven by autonomous cars by now, according to Kurzweil. Yet, Elon Musk is very cautious in releasing new self-driving features on its Teslas
is challenging, and so is Unpredictability, Volatility and Ambiguity.
Apparently, Humans are still better off in facing these ingredients of the current reality
Reading Uncharted, by Margaret Heffernan
, gives you an extraordinary tale of why forecasting
is not our best skill as human. How can we then pretend to be able to teach it to a technology that we build?
pandemics has brought a significant element of uncertainty on all of us. All the models we had built have evaporated
. I still observe with amazement the incredible dedication that my finance colleagues put in drafting budgets over budgets for a future that clearly cannot be derived from the past. Yet, people are reacting: facing adversity through the very human capabilities of adaptability
. And most Human Activities that create value, in the arts and crafts, but also many professions, are strictly linked to all these talents that make us human.
No, AI will not take away our Work.
And I genuinely think the difference is in the way Job has replaced Work, based on a narrow definition of efficiency. We are losing that battle because technology wins based on traditional productivity measures unless human labour is cheaper. It is not a sustainable future.
This is where reappropriating ourselves of a new meaning of Work is vital. Think of housework, the care given to children and older people, the voluntary Work for NGOs and communities. Most of this is not captured in GDP measures of unemployment metrics, because all these elements are not relevant in an efficiency-based discourse.
Yet they are very relevant for what makes us human.
We don’t have to train in making our algorithm more complicated. We need to prepare in experimenting surprise, in acknowledging newness and creating a hypothesis for a better future. Again, Covid-19 is showing the power of doctors and scientists able to imagine something different than the electronic models we have created. Imagination being another truly human trait.
So, what is that lies ahead of us? As a student, I bet you probably are going to be confused. Studying for a Job that has a high potential of being automated, puts yourself in an existential crisis about your future
. My recommendation would probably be to increase the breadth of topics you can cover during your studies. Specialisation, especially in so-called STEM domains, is the area were machines will reign. We need instead to walk back to the origins of Academia and think in terms of breadth of knowledge
, particularly of those disciplines that help our distinctively human competencies. History, Arts, Philosophy
. After all, the highest university degree is called Philosophiae Doctor,
emphasising the need for every academic to love the wisdom of human thought.
Here is where we have an advantage over AI, Machine Learning, Robots. In the breadth and wisdom that allows us to comprehend complexity from small weak signals. And imagine and craft future worlds where we still dominate technology as practical support to our lives, not a replacement thereof.