Marking the homework of a twelve year old

“I want to make an AI…“ says my son at the dinner table. He’s 12. This isn’t an uncommon discussion in our household. He continues “what piece of code can I write to help you?”

“Err… that’s a really difficult question to answer.” I respond, “Why don’t you flip the order of your question and first ask me what kind of things I struggle with. Then you can decide if AI or code is the best fit for solving my problem.” UHRG! design-thinging-researcher-dad-cringe!

Humouring me he asks “What kind of problems do you have?” I describe my ongoing problem of having bookmarks and saved for later items across the internet with no way of joining them all up. “Okay let’s make that!” he exclaims. Again, this isn’t an uncommon scenario. How to scale back the vision without crushing his enthusiasm?

The day before he showed he a drawing exercise called ‘piece of cake’. It employs constraints to increase the number of drawings and improve your technique over increasing time periods: draw the same image for 30 sec, 1, 3, 5, 10 min, 1 hr.

This technique reminded me of the Design Sprint Crazy Eights, a method for generating lots of ideas in a short amount of time. Coming up with ideas is easy, most of which are destined for the cutting room floor. The hard bit is working through ideas, identifying the parts of value, iterating and testing. The Crazy Eights method is a great way to flush out the obvious – crap – ideas and over the course of the session helps us to loosen our grip on the preservation our own ideas.

Back to the dinner table… “Remember the ‘Piece of cake’ technique you showed me yesterday? Your AI example is a bit like the 1 hr sketch. What could we do that’s more like a 30 sec sketch?” We talked about the different technologies at our disposal, worked out what type of sketch they represent on the ‘piece of cake’ timescale and found the smallest example we could start with. We decided on a simple chatbot that suggests manga. We discussed the types of categories that might help broaden or narrow the scope of suggestions, the kind of questions that the chatbot might ask and how as a user you would interact, and lastly what would happen after selecting a final result. All the while trying to keeping our time and effort toward the shorter sketch duration, to reduce time effort and risk.

My son isn’t alone in the wonder of AI. It seems to be everywhere solving the problems that didn’t know we had, like pollyfilla spread between every nook and cranny of our digital products. Did design teams skip the Crazy Eights session? Did they go straight for the 1 hr sketch and just build the damn thing? I‘m left wondering if, when we look back at this era of the web and digital, we’ll be left with the AI technology equivalent of the gaudy aftermath of Laurence Llewelyn-Bowen’s Changing Rooms?

Don’t get me wrong, there are some features under the mislabeled bracket of AI that have made a huge impact and improvement to my process. Audio transcription has been an absolute game-changer to research analysis, reimbursing me hours of time to focus on the deep thinking work. This is a perfect example of a problem seeking a solution, not the other way around. The latest wave of features feel a lot like because we can rather than we should, because.

I’m looking forward to the promise of more of my time being freed up to focus on thoughtful work. But the handover of this work needs to be rooted in trust and not come at the cost of other people or the planet. I’m looking forward to reading about genuine problem-solving products and not like I’m marking the best-of-intentions homework of a twelve year old.