Generative AI shows many of the hallmarks of being what’s known as a general purpose technology – something that will reshape things across our society and our economy.
As a public servant with a background in innovation, I’m keen to make sure those of us in the public sector understand this technology as much as we can, as early as we can. With GenAI potentially being an one of the most powerful and accessible technologies we’ve ever seen, with potentially disruptive effects, it feels wise to try and think through where the technology might be headed.
Of course it’s futile to try and predict this exactly. But what we can do is to try and reduce some of the uncertainty around generative AI by identifying which mental models can help guide our expectations and thinking about the technology. While there will be many unpredictable developments, we can try to understand the broad directionality of where things are likely to head. We can be clear about the rules of thumb that might aid us, if only so that we can know when they are no longer helpful. As always with innovation, the more we can make the implicit explicit, the more we can ensure that we are entering into a deliberate process rather than one shaped by untested assumptions.
In the attached document I’ve attempted to pull together some of the mental models and relevant evidence points that can I think can give us insight into the field of generative AI and where it’s headed.
This is very much a learning exercise, and I’m keen to hear from others what mental models / evidence points they are relying on in thinking about the evolution of this powerful technology.
This also does not attempt to cover or replicate the important work being done around ethics and guardrails for the technology. Rather, it’s an attempt to understand the direction of the technology, so we can better understand the implications.
I’d love to hear any thoughts or suggestions on what might be missing.