Stefania Druga on Designing for the Next Generation

How do you teach kids to use and build with AI? That’s what Stefania Druga works on. It’s important to be sensitive to their creativity, sense of fun, and desire to learn. When designing for kids, it’s important to design with them, not just for them. That’s a lesson that has important implications for adults, too. Join Stefania Druga and Ben Lorica to hear about AI for kids and what that has to say about AI for adults.

Timestamps

• 0:27: You’ve built AI education tools for young people, and after that, worked on multimodal AI at DeepMind. What have kids taught you about AI design?
• 0:48: It’s been quite a journey. I started working on AI education in 2015. I was on the Scratch team in the MIT Media Lab. I worked on Cognimates so kids could train custom models with images and texts. Kids would do things I would have never thought of, like build a model to identify weird hairlines or to recognize and give you backhanded compliments. They did things that are weird and quirky and fun and not necessarily utilitarian.
• 2:05: For young people, driving a car is fun. Having a self-driving car is not fun. They have lots of insights that could inspire adults.
• 2:25: You’ve noticed that a lot of the users of AI are Gen Z, but most tools aren’t designed with them in mind. What is the biggest disconnect?
• 2:47: We don’t have a knob for agency to control how much we delegate to the tools. Most of Gen Z use off-the-shelf AI products like ChatGPT, Gemini, and Claude. These tools have a baked-in assumption that they need to do the work rather than asking questions to help you do the work. I like a much more Socratic approach. A big part of learning is asking and being asked good questions. A huge role for generative AI is to use it as a tool that can teach you things, ask you questions; [it’s] something to brainstorm with, not a tool that you delegate work to.
• 4:25: There’s this big elephant in the room where we don’t have conversations or best practices for how to use AI.
• 4:42: You mentioned the Socratic approach. How do you implement the Socratic approach in the world of text interfaces?
• 4:57: In Cognimates, I created a copilot for kids coding. This copilot doesn’t do the coding. It asks them questions. If a kid asks, “How do I make the dude move?” the copilot will ask questions rather than saying, “Use this block and then that block.”
• 6:40: When I designed this, we started with a person behind the scenes, like the Wizard of Oz. Then we built the tool and realized that kids really want a system that can help them clarify their thinking. How do you break down a complex event into steps that are good computational units?
• 8:06: The third discovery was affirmations—whenever they did something that was cool, the copilot says something like “That’s awesome.” The kids would spend double the time coding because they had an infinitely patient copilot that would ask them questions, help them debug, and give them affirmations that would reinforce their creative identity.
• 8:46: With those design directions, I built the tool. I’m presenting a paper at the ACM IDC (Interaction Design for Children) conference that presents this work in more detail. I hope this example gets replicated.
• 9:26: Because these interactions and interfaces are evolving very fast, it’s important to understand what young people want, how they work and how they think, and design with them, not just for them.
• 9:44: The typical developer now, when they interact with these things, overspecifies the prompt. They describe so precisely. But what you’re describing is interesting because you’re learning, you’re building incrementally. We’ve gotten away from that as grown-ups.
• 10:28: It’s all about tinkerability and having the right level of abstraction. What are the right Lego blocks? A prompt is not tinkerable enough. It doesn’t allow for enough expressivity. It needs to be composable and allow the user to be in control.