Hackathon participants included Sara Amadon, Stephanie Cochran, Kaylor Garcia, Alex Gabriel, Tracy Gebhart, Kristen Harper, Garet Hedlund, Ashley Hirilall, Samantha Holquist, Lauren Kissela, Asari Offiong, Matthew Rivas-Koehl, Jing Tang, and other Child Trends staff.
Child Trends is excited to share new work to apply emerging technologies like Artificial Intelligence (AI) to advance the well-being of children and families! Toward that end, we recently hosted an internal hackathon—an event where computer programmers work with subject matter experts to rapidly develop prototypes of products that can support our research. These prototypes—developed with experts in education, reproductive health, child welfare, and research operations—all incorporate recent advances in AI.
These advances (especially in large language models, a technology that interprets and produces language) have received widespread publicity and are already substantially changing most industries. They include highly publicized chatbots like chatGPT and Google’s Gemini, which allow users to type interactively with an AI model. Our goals in the hackathon were to test how these technologies can be applied to Child Trends’ research priorities.
Readers interested in learning more about Child Trends’ work in data science and AI should sign up for our data science newsletter. Read on for a more in-depth overview of prototype products developed during the hackathon and our lessons learned.
What AI tools can 13 researchers and three data scientists create in three hours to support the well-being of children and youth? Quite a few. Our first ever “mini hackathon” included brainstorming products, developing working prototypes, and creating product roadmaps.
Caption: Researchers hard at work brainstorming AI products
During the hackathon, teams of researchers came up with prototypes (sometimes called minimal viable products, or “MVPs”) for four ideas, which then informed operational and technical lessons learned.
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MVP prototypes
Source: Image generated by DALL-E on March 4, 2024.
Caption: Example of a DALL-E image produced in response to the prompt, “Can you create an image of what an ideal math classroom looks like featuring a group of students engaged in project-based learning in a modern looking classroom?”
Caption: Screen capture from the prototype app developed during this hackathon to allow querying of specific RFP text.
Our team learned three operational lessons from the hackathon:
The team also learned the following three technical lessons:
The current generation of AI tools has promising applications for research—spanning data collection, data transformation, quantitative and qualitative analysis, and research operations support. With these new tools, researchers can build prototype solutions in just a few hours to allow for greater innovation and pilot testing.
Kelley, S., & Kelley, C. (2024). Child Trends hackathon applies AI to products that advance child well-being. DOI: 10.56417/3485f4773k
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