Professor Rachel Chung Publishes Children’s Book to Teach AI Fundamentals
In a world increasingly dominated by artificial intelligence (AI), a team from the Raymond A. Mason School of Business is making strides to demystify the seemingly complex technology for the young learners. Led by Clinical Associate Professor Tingting (Rachel) Chung, the group is publishing a groundbreaking children’s book: AI: The Magic Box.
Set to launch on October 15th on Amazon, the book aims to introduce middle schoolers to the mathematical fundamentals of AI and machine learning in a fun and engaging way, transforming what many see as an intimidating subject into an accessible and enjoyable learning experience.
“Everyone is talking about AI today, but few people truly understand what it is at a basic level,” Chung said. “I think it confuses a lot of people but it’s actually very easy. It’s just a math equation.”
Genesis of the Magic Box
The idea for this creative project was born during the early days of the COVID-19 pandemic. Chung’s sister, Peggy Chung, was stuck in Taiwan due to travel restrictions after visiting their family for Chinese New Year. With her career on hold, Peggy sought out ways to spend more meaningful time with her daughter and explored various avenues of children’s education.
“She was always interested in children’s education but never became a teacher. The timing ended up being perfect,” Chung said of her sister.
Together, the sisters brainstormed ways to teach kids about data science—an area they felt was underrepresented in early childhood education compared to the booming trend of coding classes.
“At the time, a lot of programming classes were related to robotics but it’s hard to teach someone how to program a physical device remotely, during the pandemic” she explained. “So I suggested we look at teaching kids about data science instead.”
Inspired by her own teaching methods in William & Mary’s MBA and MSBA programs in which she uses everyday objects like chocolates and sticky notes to explain key ideas, Chung suggested creating a curriculum that could translate complex data science concepts into kid-friendly activities. This led to the creation of “Data Scientist Junior,” an online program where children learn about data science through fun, interactive exercises. This program was also a collaboration with her former MSBA student, Rani Banjarian. A former math teacher and a creative writing enthusiast, Banjarian joined forces with the Chung sisters to develop content tailored for children. Their efforts proved successful, with two of their young students winning top prizes at a national data visualization competition.
“We sent two of our best students to the American Statistical Association’s 2021 visualization competition and they won first and second place, nationally. I couldn’t believe our little elementary schoolers did so well,” she beamed.
From Online Classes to the Written Word
As the pandemic eased and the online classes wound down, the team realized the potential to reach an even wider audience through a book. AI: The Magic Box emerged from the lessons learned in the Data Scientist Junior program, repackaged into an activity book format that makes AI accessible and fun for children.
“As people moved past COVID and restrictions, we began to ease off of the Data Scientist Junior program, but we also knew there was a lot of valuable content in the curriculum. It was just a natural progression to look at repurposing that content and turning it into a book,” she explained.
The book follows the story of Connor, named after Chung’s son, and his sister, Atena, named after Peggy’s daughter. They are on a mission to find a hypoallergenic dog for Connor’s birthday. Young readers are introduced to the basics of AI, including classification algorithms and three major of the AI Process—Collect, Train, and Decide.
As the siblings navigate the challenge set by their data scientist mom, they encounter a friendly AI device called Magic Box at their local library. With Magic Box’s help, Connor and Atena learn how to break down complex data into manageable pieces, train the AI, and use it to make decisions—in this case, identifying the perfect puppy breed that suits their family’s needs.
The book not only simplifies big terms like “machine learning” and “AI models” but it also incorporates hands-on activity worksheets to reinforce key principles, allowing children to practice what they have learned, mimicking the teaching style Chung employs in her classes at William & Mary.
“Our goal was to take what I teach in my AI and machine learning courses at the graduate level and distill it into a form that children can grasp,” said Chung. “We want to remove the mystique and jargon that often makes AI seem like a “black box” to the uninitiated. With this book, middle schoolers can see that AI is not magic—it’s just math, and it’s something they can understand.”
Navigating the Publishing World
The journey from concept to publication was not without its hurdles. The team initially faced difficulties in securing funding and finding an illustrator who could bring their vision to life. A Kickstarter campaign launched to raise funds fell short of its goal, but with persistence and resourcefulness, the team eventually met their goal.
Also, with the help from the William & Mary community, talented undergraduate students Alisa Yang and Danielle Seay were funded through the university’s Fuse Scholarship and the book’s illustrations and design were completed in-house.
“We had no idea how challenging the process of self-publishing could be, especially finding the right illustrator,” Chung reflected. “But the support from the William & Mary community made all the difference. We feel so lucky that Alisa convinced her friend Danielle to join the team as the illustrator. This project is truly a Tribe family effort.”
AI for the Next Generation
AI: The Magic Box is designed not just as a book but as a learning tool. It aims to foster an early interest among middle school-aged children in AI, data science, and STEM fields by showing that these subjects are within their reach. The book’s activities simplify AI concepts such as neural networks, and model training, often using playful analogies and clear visuals to explain how AI works.
Chung’s approach to teaching AI emphasizes the importance of real-world applications and removing the barriers of intimidating jargon. In her courses at the Mason School, she has developed tools like Excel-based simulators that allow students to understand AI by manipulating simple formulas, an approach mirrored in the book.
“We use analogies that young readers can relate to, such as learning to bike,” she said. “We show that what an AI model does is just adding and multiplying numbers—something that middle schoolers can easily do. The idea is to make AI something that’s not scary, but something that they can play with and learn from.”
The book’s publication marks a significant step in making AI education more inclusive and accessible. Chung plans to promote the book at two events hosted by the Williamsburg Regional Library on October 26th and October 30th titled, AI: The Magic Box Workshops. She will also present it as part of a Society 1918 alumni event in Washington, DC on November 20th.
Chung will also continue to identify and seek opportunities to fill gaps in the market with materials to help educate students of all ages on the technology. Most recently, she secured a book deal with a renowned higher education publisher on an AI textbook that she is authoring with Mason School online adjunct professor, Steven Hojnicki.
As AI continues to shape the future, equipping the next generation with the knowledge to understand and engage with this technology is more crucial than ever. Chung and her team hope that AI: The Magic Box will be a small but impactful contribution to that cause.
“AI isn’t just for adults or computer scientists—it’s for everyone, and we need to start that education early,” she added. “I’m excited to see where this journey takes us, and I hope the book inspires children and parents alike to explore the fascinating world of AI."
