Hedging Your Bets on AI

My friend and colleague Patrick Prill has been writing articles about AI in our industry at a prodigious rate over the last couple of weeks. (Here's the second of yesterday's pieces.) I recommend reading them for a thoughtful and detailed analysis and reflection on today's software and social ecosystems and the ways that AI is reshaping them.

I can't compete with the breadth, depth, or frequency of his output so, although this post is on the same topic, I offer only a short analogy.

Step back in time 60, 70 or 80 years and wander through England's pleasant pastures. You will see lanes and fields bordered with hedgerows maintained by skilled workers, living and breathing boundaries, functional for keeping stock in and intruders out but also a functioning component of the local ecological web.

Hand-laid hedges are habitats. Birds nest in them, rodents and small mammals use them like a road network to travel safely around the landscape, stock animals use them as windbreaks or for shade, flowers are protected by them, and insects get sustenance from the flowers then stick around to predate pests on the nearby crops. And let's not forget aesthetics: hand-laid hedges can be beautiful too.

The expert hedge-layer takes local context into account when choosing how to approach a particular stretch of hedge: the time of year, the weather, the nest that still has eggs in it, the seed pods that haven't yet burst, the microclimate in this corner of this field, the deliberate kink in the otherwise straight line that is sensitive to the badger's sett at its foot. All of these will influence their practice and strengthen the symbiosis between the borders and the bordered.

Like so many crafts, hedgework takes time to learn and intentional exercise to master. This is not fast, and it is not cheap, and it is not easy to resurrect once the chain of skill-passing from generation to generation has been broken.

There is justifiable pride in this kind of work, and being part of a community that values it, and the environment around it. However, these days it has been replaced by a tractor with a flail mower attachment crudely lashing straight lines into whatever happens to be at the allotted location on any given day.

Of course, the mechanical approach has great benefits: it is fast, it is cheap, it requires little skill, and, on the surface, from a distance, in the master spreadsheet back at head office, the job got done.

✅ Boundary maintained.

James C Scott's Seeing Like a State gives numerous examples of such paucity of vision, where distance from the work enables it to be commoditised, homogenised, and optimised: a unit of hedge maintenance is a unit of hedge maintenance is a unit of hedge maintenance. Local context? Systemic benefits? Aesthetics? Ha! Just look at those numbers!

✅ Maximum value efficiently extracted.

Yes, maxium value efficiently extracted ... for some highly-focussed metric. But what about the externalities, what about the side-effects, what about the impacts downstream in time and place?

You can see where this is going so I won't labour the analogy.

Your product is the hedgerows of Britain. Your developers are the hedge-layers. Your codebase and your colleagues and your company and your industry and the econonmy are the ecosystem. AI is the brutal and unsubtle mowing machinery. Your leadership is pursuing the immediate return.

The problem is that the potential return is there, and it looks like it can be taken ... today. You can write the code with LLMs and you can make half your workforce redundant and you can feel like you're moving faster ... today. But at what cost? At what time? Where? To who? And is there a way back if you don't like it?

The world changes and we can't stop that. This technology is important and already pervasive enough that we can't ignore it. It's also clear that there is enormous risk attached to its use, from basic correctness through the underlying morality of its training to the environmental impact of its use.

My advice? Think of the system and hedge your bets.
Image: CXCS

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