AI and the Race for the Light
The temperate rainforests in New South Wales, Australia — my home state — contain very different trees than rainforests in the American Pacific Northwest. However, those different trees fill out their respective forests in a remarkably similar set of sizes. A 2016 study found that rainforests all over Earth derive their similar structures from identical events: the falling of large trees.
A massive trunk crashes to the ground (or does it fall silently?), and a sudden gap in the rainforest canopy allows rare direct light to hit the forest floor, marking the start of a race for the sun.
Multiple small trees stretch out for the sky, growing rapidly in an attempt to outcompete their neighbors. Perhaps one tree takes the lead and looks certain to win before collapsing under its own weight, hypergrowth taking it too far, too soon. Others strangle their competition early, clearing a patch around them, but in the effort lose position against less aggressive species.
In the end, one tree wins, filling the canopy gap and growing into the next giant of the rainforest. Some of the other racers, now starved of sunlight, must curtail their growth and play smaller — though no less important — roles in the greater life of the forest.
Right now, tech companies are in their own race to own the sunlight. Generative AI has created a gap in the market, and hundreds (thousands!) of companies are trying to fill that gap. There will be big winners, but most of them are likely to fill smaller roles or be so stunted as to eventually disappear. The challenge we’re all facing is that we don’t know yet how big that market gap actually is or even if it is a true gap versus just a temporary glimpse of the sun created by a falling branch, soon to be filled by the existing trees.
Will AI fundamentally change how business is done? Or is it an expensive tool that will no doubt fill important niches but not dominate the future of the market?
From our position in the midst of the race, the answer is impossible to perceive. That is to be expected. Every technological shift is messy and complicated, and it’s only afterwards that the winning approach seems obvious and inevitable all along. We might, for example, have had electric vehicle dominance a century ago if the infrastructure had been prioritized and the external environmental costs were built into car prices.
Thomas Kuhn’s book, The Structure of Scientific Revolutions, shows us that big changes in our shared understanding (paradigm shifts, as he calls them) are always accompanied by some chaos. He describes those moments as containing:
“a proliferation of compelling articulations, the willingness to try anything, the expression of explicit discontent, the recourse to philosophy and to debate over fundamentals”
Doesn’t that remind you of the discussion around AI today? All sorts of odd ideas, disturbing thought experiments, inexplicable products, claims of sentience, and philosophical discussions of what it means to be a human.
We should expect to see all of this eventually resolve into a new world view where most people agree on what AI is, what it is good for, and how it is not. There’s just no way to get directly to that point. We have to live through the confusing present.
AI will be stuck into every conceivable tool, and we’ll all figure out which ones are valuable, even incredible, and which are not worth the very real economic and environmental costs.
So what should we do? How do we, as humans with jobs to do and families to support and lives to live, figure out what to pay attention to during a potential upheaval of our working lives? How will we know what to adopt, what can be safely ignored, and what might represent a real risk?
There is no easy or obvious answer. For those of us in customer support, we’re dealing with all this ourselves while also trying to help our customers navigate those same AI-driven changes, perhaps even in our own products and services.
The best we can do is to remain engaged. Pay attention to the potential, evaluate it critically, try things for yourself, and make informed judgements. Something big might be happening here, and we need to know about it. Most of the changes driven by AI will not be directly under our control, but if AI is going to be a core tool in our future, then we will need to grapple with it and figure out how to fit it into our lives (and our companies).
We must always be aware that what looks today like the clear winner in this race might turn out to be a dead end, a side branch that leads nowhere, or a tree that will wither away.
The race is only just beginning. The gap remains to be filled.
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