G. Jake Chanenson

Examining how children and youth encounter generative AI in school and at home, what data is collected about them, and what design and policy interventions can meaningfully improve their safety. Work includes co-organizing a CHI 2026 workshop on developmentally safe AI environments for youth.

Investigating whether LLMs can assist humans in annotating privacy policies using a contextual integrity framework.

Investigating how K–12 public schools keep student data private and secure, with emphasis on marginalized student populations. Foundation for multiple publications and ongoing work on children's online privacy.

Research intern with Sunny Consolvo. Work contributed to a CHI 2026 paper on people's emotional responses and help needs during scam experiences.

Covered by USA Today, The Markup, EdSurge, K12 Dive, The 74, and Fox 35.

Co-organized a workshop bringing together researchers, designers, educators, and policymakers to examine how generative AI shapes youth development and to co-create frameworks for safe, inclusive AI experiences for children.

Co-organizing a workshop that brings together researchers, practitioners, designers, educators, advocates, and youth to define accessible AI safeguards and develop a shared research agenda for disabled and neurodivergent youth.

Sole instructor for the required foundational CS course for majors. Taught Python programming, core algorithms, data structures, and command-line basics.

Designed and taught a human-centered design summer course to 20 under-served high school students per cohort.

Designed and led a CS mentoring and enrichment program for 30 marginalized and under-served high school students.

Designed and taught a Python coding course to 15 marginalized and under-served high school students.

Sole TA for a course serving 20 marginalized and under-served high school students with limited CS background.

Invited guest lecture in Inclusive Technology: Design for Underserved and Marginalized Communities.