Tailored content · A use case
What is all this “exploration reasoning” about? Bear with us. We are getting there.
Imagine a future scenario where all kinds of data are taken from wearables: watches, wrist bracelets, ankle bracelets, collar microphones, glasses… An AI would process all that data taken from your speech and biometry. It will know you better (more objectively) than yourself.
Now you want to buy some trousers. Your AI assistant will know exactly what type of clothes you like: they should be produced of recycled material in fair conditions. Size 40. Your thighs and bum are larger than your waist. Ideally transportation routes are minimised. Cut: Straight large, high waist, in black. Secondhand is preferred to new. It will even know you gained two kilos!
After some questions to refine the search, the AI is done. You unfold your screen and look at a UI full of auto-generated models, posing with your body shape, wearing the kind of trousers that you asked for. You can see exactly how they would look on you. AWE-SOME
Now. Imagine you very well know what you want, but your taste has not changed in the last few years. Your preferences will show up all over the place. Wouldn’t you end up being tired of yourself? You would want to check the trends. Leave your island. At some point you would be willing to forget about your own taste and expand it upon the exploration of others.
AI prophets sing their praises for personalised content but it is easy to envision a scenario in which you get sick of it and want to switch back to a discovery mode that allows you to re-connect with the designers and search for new trends. Artists will, again, save us from ourselves.
And here is where the analogy between Mondrian’s act of creation and the algorithmic act of imitation from Bell Labs comes into place.