Applied AI Development: a twelve-week residency with software artist Ryan Kelln
Thirty-four free sessions from October 1 to December 19: talks, panels, hands-on workshops, and two community days.
AI is suddenly everywhere: in your search bar, on your phone, in your software, in your news. This residency is twelve weeks of putting it to work on things you care about, and looking deeply to see how it works.
There are 34 free sessions: two talks, three panels, fourteen workshops, and two community days. Most workshops run twice.
Each session needs its own registration, and registration opens a month at a time. October is open now, and some October sessions are already full: they are marked below. Where computers are needed, they are provided.
The opening talk sets up the twelve weeks. The closing talk asks what we do with them.
Where AI came from, who is building it now, and what it costs.
An illustrated talk with live demos. We look at what has changed in the last few years, the people who make it and why, and how it shifts power. Then the part the AI companies cannot offer you, and how to get the most out of the twelve weeks ahead.
Twelve weeks of making and testing. Now what?
We look back at the projects people built, the failures that taught us the most, and the needs we found but could not solve. Then it is your turn: in small groups, help turn what we learned into what this community does next.
Three important conversations, each with time for your questions. No pitches, no boosterism.
Young people are the first generation growing up with AI everywhere.
An honest conversation about AI and youth: what young people are actually doing with it, what worries them, and what adults keep getting wrong. Audience questions welcome. This is not a lecture about cheating. It is the older conversation about thinking for yourself, now that digital intelligences are developing too.
If AI becomes as important as roads or electricity, who should own it?
A panel of people building public-interest AI, working in civic tech, and organizing communities affected by AI decisions. You will draft your own public AI requirements and compare them with what everyone else thinks should be guaranteed to all of us.
Toronto is one of the biggest AI cities in the world.
A panel of people who know AI from very different angles, on what AI is doing to this city and what we want it to do instead. Work, money and meaning. Who gets to shape it, and who is left out. An honest conversation, not a sales pitch for the future.
Workshops for your own life: problems, habits, learning, family, and staying safe.
Do you keep doing something by hand that feels like it should be easier?
Bring a real problem, or come help your neighbours with theirs. Learn a simple seven-step way to think it through: what is annoying you, what you have tried, what AI could actually do, and where it would fail. The problems AI helps with most are often the most personal, and those are worth the most care.
You have asked a chatbot questions. This is the other kind of AI: the kind that acts.
A demo-driven look at always-on AI assistants that read your files, use your apps, and remember what you have told them. We open up what happens inside: the hidden instructions, the tools it reaches for, what it keeps and what it forgets, and what can go wrong when something else gets hold of those powers.
AI can help with schoolwork. So why does it feel like walking a tightrope?
For teens. Use AI as a tutor, quiz partner, and explainer rather than an answer machine, and learn the difference between learning with it and fooling yourself. We also cover what school policies actually say about AI, and when AI is the wrong tool entirely.
How does a machine actually think?
A hands-on class on what is really going on inside an AI system: how it decides what matters in your question, where its training data comes from and who is missing from it, and how hidden instructions can sneak in and hijack it. No math, just intuition. And the question underneath everything: is there anyone home inside the machine?
Staying in touch, keeping track of appointments, finding programs that interest you.
A gentle, jargon-free class with no pressure and no experience needed. Write a message in your own voice, turn a spoken thought into a checklist, plan questions for an appointment, and find community programs. We are also straight about the risks: anything that sounds like a person deserves caution, and we practice spotting the scams that use AI. Afternoon sessions.
What if your to-do list could notice what has been stuck for weeks?
A personal productivity system built around an AI agent and a weekly review. It loads your goals, counts what actually got done, flags what keeps slipping, and drafts next week's plan. Support without cheerleading. Try it with a practice set of goals and leave with the plain-text templates.
Always wanted to learn to cook, draw, knit, fix a bike, or speak another language?
Set up a personal AI tutor for something you love, or something new you want to fall in love with. Turn a goal into a small, doable learning experiment: options instead of answers, a practice that survives a bad day, and a decision made in advance about how you will know it is working. Revise, or stop without guilt.
What if your AI did not need the internet at all?
Watch AI models run entirely on one computer, with no connection and no data leaving the room. We compare a small local model against a much larger cloud model and against plain search: what each gets right, what each costs, and what the privacy trade-off really is. You leave with a decision sheet for your own hardware and an honest look at what open really means for AI.
For job hunters, small business owners, and anyone who is the whole company.
Job hunting is a job in itself: applications, deadlines, follow-ups.
Explore a job-hunting dashboard built with AI. It tracks applications, watches for postings that match you, and practices interviews with you through role-play. You leave with the templates to build your own. We also talk about how employers screen applications, and how that can be unfair.
You have the business idea. Now come the thousand questions.
Use AI as a research and planning partner. We practice on a sample business: turning a rough idea into a plan, digging into a market, drafting customer-discovery questions, and setting up low-maintenance automation. The most valuable thing you will get is usually a better question to test in the real world.
When you are the whole company, the admin never ends.
Design an administrative system for a one-person business: intake, email drafting, client communication, scheduling. And learn to sort the work into four piles: what is rules-based, what AI drafts, what only your judgment can do, and what should never be automated at all.
Describe what you want and build it. No coding experience needed.
Write a story where the reader decides what happens.
Use an AI coding assistant to build a branching adventure, a mystery, or a small game. You design the branches, describe the rules in plain language, test the tricky edge cases (what if the player picks the weird option?), and end up with one file you can share with anyone. Bring a story you want to tell.
Build your own reading app, just by describing it.
A small app for your reading life: the books you have read and the books you want to read, all in one private place, with each title linked to the library catalogue so placing a hold is one click away. Your reading list stays on your own computer. The library keeps the books; this file keeps your reading life, and it travels with you.
What if you could build an app just by describing it?
Use an AI coding assistant to build a small, useful webpage, checklist, or organizer from scratch. You learn the build loop: describe what you want, review the plan, build one feature, test it, fix the bugs, and write it down so you or anyone else can understand it later.
Two bigger days, open to everyone.
What are people actually building with AI, in your city, by your neighbours?
An afternoon of live demos and projects from the AI Tinkerers community, hosted at the library. See what local builders are working on, ask them questions, and take ideas home for your own experiments. Real projects, real people, no product pitches.
Presented with Human Feedback Foundation.
What could a room full of neighbours and AI tools build in one day?
Our community hackathon. Teams pick a local problem, design a small and responsible AI tool or workflow to help with it, build a prototype, and show everyone what they made. You do not need to code: teams need researchers, designers and storytellers as much as builders, and everyone tests the work. Mentors help all day. The challenge briefs come from problems neighbours brought to the library this fall. Bring your own computer.
All 34 sessions in date order. Every title links to that session's listing.