“This new AI technology—it’s very interesting to learn how it works and understand it more,” says 10-year-old Luca, a young AI model maker.
Luca is one of the first kids to try Little Language Models, a new application from Manuj and Shruti Dhariwal, two PhD researchers at MIT's Media Lab, that helps children understand how AI models work—by getting to build small-scale versions themselves.
The program is a way to introduce the complex concepts that make modern AI models work without droning on about them in a theoretical lecture. Instead, kids can see and build a visualization of the concepts in practice, which helps them get to grips with them.
The program starts out by using a pair of dice to demonstrate probabilistic thinking, a system of decision-making that accounts for uncertainty. Probabilistic thinking underlies the LLMs of today, which predict the most likely next word in a sentence. By teaching a concept like it, the program can help to demystify the workings of LLMs for kids and assist them in understanding that sometimes the model’s choices are not perfect but the result of a series of probabilities.
Students can modify each side of the dice to whatever variable they want. And then they can change how likely each side is to come up when you roll them. Luca thinks it would be “really cool” to incorporate this feature into the design of a Pokémon-like game he is working on. But it can also demonstrate some crucial realities about AI.