AI, work, educated guesses: what’s next for us?

The surging issues tied to AI — artificial intelligence — are complex. Much like the internet before it, AI seems to be touching every aspect of our lives, one way or another; but, if possible, at a seemingly even larger scale. It is not only impossible to cover everything in one place, but the pace of progress in the AI space makes every attempt at a comprehensive snapshot moot. It all changes too fast.

In the book Intelligenza Artificiale: Arte e Scienza nel Business, co-authored by JAKALA General Manager Marco Di Dio Roccazzella and Senior Partner Francesco Pagano, our Partners Vittorio Di Tomaso and Tomas Barazza and our writer and content designer Edoardo Maggio have thus tried to focus on two things thing: timelines and work.

AI wasn’t born with ChatGPT, so the introductory chapter of the book — by Vittorio Di Tomaso — serves as a comprehensive overview of the history of artificial intelligence: where it started, where it’s at, and where it’s (apparently) going next. Then, speaking of possible future destinations, the book’s closing chapter (written by Tomas Barazza and Edoardo Maggio) ventures into the realm of speculation to try and understand where the overlap between the future of work and AI lies. Below is a brief introduction to its themes.

Beyond their sheer technical progress, large language model (LLM) applications have shown us what happens when systemic changes happen seemingly overnight. Like an earthquake, these (admittedly rare) phenomena are democratic, in that they hit everyone indiscriminately; but they are also profoundly shaking events, seeping into the minds of the affected and triggering chain reactions of all sorts. Two, more importantly: a social and an engineering one.

The latter, in the case of AI, looks like a steamrolling machine that unlocks new skills what appears to be every other hour. Some are useful, some aren’t, but the feeling is that the introduction of ChatGPT has pushed humanity past a significant threshold: AI is here, it works, and it’s getting better quickly. And things have only picked up accelerated further since, perhaps finally catapulting us into the long-sought-after “AI summer”.

As for the social component, things are trickier: everyone and their mother has an opinion, newly self-appointed “pundits” pop up behind every corner, and executives across the board appear Moloch-trapped into pontificating about the future and how, surely, their firm will use AI for the better. After all, if AGI — artificial general intelligence — has indeed become a visible endpoint, every weird (or even borderline nonsensical) prediction is fair game, as something will undoubtedly stick to the proverbial wall.

With this publication, however, our goal was not to play the soothsayer. Rather, we took a step back and based our thinking on first principles, to drag our hypotheses (better: our educated guesses) into their ostensibly natural conclusions — fully aware of the immense leeway these mental exercises bring with them, no matter how grounded.

We take into account the very many movable pieces at hand, but instead of focusing on the exact shape of the path (a frankly unnecessary endeavor), we set our eyes on the terminus: what would it mean, for workers and companies of all kinds, to live in a world where an AGI actually exists? Is this technology the harbinger of an automation apocalypse (or even a step change in evolution), or do humans still have something up their sleeves?

Beyond looking at the future of AI and work from both a technical and a practical perspective — what will be possible in principle and how it will enter the real economy — we examine the unique, all-round nature of humans, suggesting that the solution to opposing an unbeatable adversary might be in the cunning switch of the game itself. The surging issues tied to AI — artificial intelligence — are complex. Much like the internet before it, AI seems to be touching every aspect of our lives, one way or another; but, if possible, at a seemingly even larger scale. It is not only impossible to cover everything in one place, but the pace of progress in the AI space makes every attempt at a comprehensive snapshot moot. It all changes too fast.