Last week I met with a group of civic tech leaders in San Francisco to share a bit about how AI can help augment the emotional and logistical work of community-builders. Thank you to the SF Civic Tech organization for inviting me to come speak!
In this video, the first 30 minutes is a speed run-through of many of the common frameworks and principles that I use when teaching AI to beginners.
We cover:
What makes an problem a good fit for an AI solution (ie: what's an AI-shaped problem)
Why I still believe that making and deploying custom GPTs for yourself is a great practice ground to get comfortable building AI workflows
How to use the basic framework, "POP-IT" that I developed with Decoded Futures as a way to guide you toward prototyping and iterating on AI workflows
Some examples of entry-point use cases for AI problems that I've used specifically for block-building and community use cases
After the initial presentation, folks stuck around for some Q&A, and we covered a lot of ground. I was impressed to get some questions I'd never been asked before, including some tough-to-answer ones about how to protect your own personal IP and web assets in a world of prolific AI-enhanced content scraping.
I wasn't entirely sure how to answer that one, to be honest. If you've got a better idea, let me know.
Until then, tune in and you can watch the full video here: