Talking about AI and everyday complexity at MOD. in Adelaide
A talk at MOD. in Adelaide about how AI might change everyday expectations, what becomes possible to build, and who takes on the work of keeping it useful.
On 10 September, I spoke at MOD. in Adelaide for the South Australian Foresight Community of Practice. The talk asked a question I’ve been working through in my own practice: what kind of complexity should we afford ourselves? The full presentation is now online.
I started with the dishwasher. Once washing-up becomes manageable, a more elaborate meal becomes possible. More plates, more courses, more preparation and coordination. You could also eat the same meal and spend less time cleaning up. The machine makes room for either arrangement.
Ruth Schwartz Cowan’s history of household technology, More Work for Mother, helps explain why this matters. As tasks became easier, expectations of care changed, and responsibility shifted within the household. Who gets to expect more, and who has to provide it? I explored that question in an earlier essay. In Adelaide, I used it to look at what we might organise around AI.
The talk followed a simple sequence: Assumed. Expected. Built. What capability can we count on? What starts to feel normal to expect? What gets built around those expectations? Each step involves choices about how people live and work together.
One example came from a visit to a childcare centre in Berlin. The director mentioned that daily toothbrushing had become mandatory. My child goes to childcare in Berlin, and I had no idea. The information was public; it simply hadn’t reached me.
That evening, I built a prototype called MeinBezirk. It organises public decisions by life situation and place, so someone can begin with their own circumstances: I have a child in childcare. I rent my home. Which decisions affect me?
Being able to explore that idea in an evening changed what I could imagine asking a public service to do. If a first explanation can be produced repeatedly, checked and kept affordable, a different expectation becomes plausible: tell me what matters where I live. A neighbourhood-information service could be organised around that expectation, while keeping the original public sources accessible.
The prototype let me see enough of the idea to ask what regular use would require. Someone would have to check explanations, keep information current and handle corrections. Who might run it? What would make that work worth sustaining?
That’s where the title question becomes practical for me. AI makes it possible to attempt things I had previously put aside because they needed other people and a budget. Once I can try them, I can begin to judge which additional responsibilities I want to take on.
Thank you to Ariella Helfgott and SA Futures Agency, MOD., and Flinders University’s New Venture Institute for making the evening happen.