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Who does the math: A designer’s journey in building an AI-based tutoring app

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Tuesday, June 10, 2025 • Designing with AI 2025

This video is featured in the Designing with AI 2025 playlist.

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Who does the math: A designer’s journey in building an AI-based tutoring app
Speakers: Aras Bilgen
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Summary

We built a novel math tutoring app for 11-year-olds in the UK. Since this was our first AI project, we expected lots of technical issues. Those happened and on top of it, we ended up questioning the value of designers in AI-driven products.

Key Insights

  • Designing AI products demands a strong understanding of AI’s inner workings to anticipate challenges and create meaningful alternatives.

  • AI model updates can unpredictably impact performance, requiring flexible design solutions and rapid iteration.

  • The Boost 11 Plus app used photography and step-by-step AI tutoring to assist stressed students and their families effectively.

  • Strict SLAs, like 24-hour design comment turnarounds, help teams manage rapid changes and keep alignment in AI projects.

  • Design principles such as avoiding gamification and clarifying the app is a calculator, not a person, were crucial to maintaining ethical clarity.

  • Designers face loss of traditional precision and predictability when designing with large language models due to their inherent opacity.

  • Rapid AI advances demand constant adaptation; designers must create multiple design alternatives to navigate ambiguity.

  • The plastics analogy illustrates how shiny new technologies can deliver powerful capabilities but carry unforeseen long-term harms and ethical risks.

  • AI’s environmental cost, like energy use for generating content, is significant and often overlooked in design and deployment choices.

  • AI systems can diminish critical cognitive skills like memory and critical thinking, highlighting the need for mindful usage and design.

Notable Quotes

"The app reads the question and prepares tutoring material, then helps solve it step by step or through chat if further questions remain."

"We realized designing for AI is very different from other computational mediums we used before."

"Understanding the lifecycle of AI code is essential because AI is essentially code running in constant evolution."

"With LLMs, precision is not possible; no one really knows why it decided what to say."

"AI is like plastics on the surface — it gives amazing powers but has hidden damages we must not repeat."

"Design is an excellent way to navigate chaos, turning ambiguity into direction through alternatives."

"We used design principles like look but don't copy, this is a calculator not a person, and no gamification to guide tough decisions."

"AI companies focus on the shiniest thing that comes without caring about stability or reliability."

"It costs about as much as a bottle of water in energy to generate a single email from an LLM system."

"AI users have reduced critical thinking skills within just two years of using AI-assisted tools."

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