Gen AI Voices Review
The Gen AI Voices Review is a quarterly online publication featuring original research and reflections from students exploring the intersection of artificial intelligence, ethics, and human discovery.
Each issue showcases short research features, essays, and commentary from students whose participation is supported through the Gen AI Voices Access Fellowship Fund. The Fund sponsors advanced research opportunities in partnership with leading educational organizations.
Through these experiences, students investigate real-world questions about AI and society, from bias and sustainability to creativity, health, and innovation, and learn how to communicate their findings with clarity, purpose, and integrity.
By publishing their work in The Review, these young researchers contribute their perspectives to the broader conversation about how AI can serve humanity, reminding us that the future of technology depends on the insight, curiosity, and leadership of those who will inherit it.
Featured Articles
Can AI Help Save the Bees?
Twelve-year-old Maya L. explored how artificial intelligence can help scientists track bee populations and protect pollinators. Her project shows how technology can inspire environmental awareness and remind us that caring for nature starts with curiosity and small actions, even for the youngest researchers.
When an AI Tutor Feels Too Smart
Fifteen-year-old Lila M. examined how students use AI tools for homework and learning. Her research found that while AI makes schoolwork faster, it can also weaken curiosity and understanding, reminding us that true learning still depends on reflection, effort, and asking deeper questions.
Predicting Drought: Using AI to Map Water Scarcity
Seventeen-year-old Daniel R. used satellite data and machine learning to study drought risk in the American Southwest. His project shows how accessible AI tools can help communities predict and prepare for environmental change before the first signs of crisis appear.
Teaching Fairness to Machines
Sixteen-year-old Sofia T. uncovered bias in an image-classification model that mislabeled women in lab coats as nurses more often than scientists. Her research reveals how fairness in AI begins with human choices and the responsibility we carry when teaching machines to learn from us.