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A yearlong global "premortem" by the Brookings Center for Universal Education (2026) examining generative AI's risks and benefits for students. Based on 500+ interviews across 50 countries, 400+ studies reviewed, and a Delphi panel.

Brookings Report: AI and Students (Prosper, Prepare, Protect)

Definition

A yearlong global "premortem" by the Brookings Center for Universal Education (2026) examining generative AI's risks and benefits for students. Based on 500+ interviews across 50 countries, 400+ studies reviewed, and a Delphi panel.

Central Finding

At this point in AI's trajectory, the risks of utilizing generative AI in children's education overshadow its benefits. This is because risks strike at foundational child development and may block realization of AI's potential benefits.

Two Paths

1. AI-enriched learning β€” well-designed AI tools with sound pedagogy can offer significant benefits

2. AI-diminished learning β€” overreliance threatens learning ability, social-emotional wellbeing, teacher-peer relationships, and student safety/privacy

Three Action Pillars + 12 Recommendations

  • Prosper: Design AI that expands student potential; co-create with educators and communities; use tools that teach not tell
  • Prepare: Holistic AI literacy for all stakeholders; prepare teachers to teach with and through AI; clear vision for ethical use
  • Protect: Comprehensive regulatory frameworks; privacy and safety in procurement; break engagement addiction; support families
  • Connected Concepts

  • Regulation
  • Student Experience
  • AI Literacy
  • K 12
  • LLM
  • Connected Articles

  • Stanford Evidence Base AI K12 2026 β€” AI in K-12 Evidence Base
  • Transfer Of Learning β€” AI Learning Transfer
  • AI Tutor Safety Harms β€” AI Tutor Safety and Pedagogical Harms
  • LLM Fallacy Misattribution β€” The LLM Fallacy and Misattribution of Competence
  • Tutoring Specific Vs General AI β€” Tutoring-Specific vs. General-Purpose AI in Education
  • Aaai2026 Prompting Literacy K12 β€” Learning to Use AI for Learning: Teaching Responsible Use of AI Chatbot to K-12 Students Through an AI Literacy Module
  • Academiclaw Student Agent Benchmark β€” AcademiClaw: When Students Set Challenges for AI Agents
  • Access Not Enough AI Tutoring 2026 β€” Access is Not Enough: Human Support Improves Engagement with AI Tutoring
  • Adapt Adaptive Lesson Plan Transformer β€” AdaPT: Adaptive Lesson Plan Transformer for Cross-Regional and Differentiated Instruction
  • Affective Text Wearable Student Health β€” A Formative Study of Brief Affective Text as a Complement to Wearable Sensing for Longitudinal Student Health Monitoring
  • Agency Gap AI Writing β€” The agency gap in AI-supported writing: how reactive and proactive agent designs shape multimodal reasoning
  • Agent Voice Accents K12 Group Learning β€” Exploring How Agent Voice Accents Shape Human-AI Collaboration in K-12 Group Learning
  • Agentic AI Education Scoping Review β€” Agentic AI in Education: A Scoping Review of Research Landscape, Capabilities, and the Frontier Agent Paradigm
  • Agentic Literacy Debt β€” Agentic Literacy Debt: A Structural Problem the AI Literacy Field Has Not Yet Named
  • Agents That Teach Incidental Learning β€” Agents That Teach: Designing Incidental Learning Back into AI-Assisted Software Development
  • Agreement Not Quality LLM Coding Verification β€” Agreement Is Not Quality: Blind Expert Verification of Human and LLM Qualitative Coding When Human Consensus Is Not G...
  • AI Adoption Training Public Sector β€” The Main Barrier to AI Adoption in the Public Sector is Lack of Training
  • AI Agents Peer Learning Discourse β€” When AI Agents Teach Each Other: Discourse Patterns Resembling Peer Learning in the Moltbook Community
  • AI Assessment Scale Reform β€” A bit of chaos and madness": The AI Assessment Scale and the work of assessment reform
  • AI Assistance Discretionary Feedback β€” AI Assistance for Discretionary Work: Increasing Feedback Provision in Higher Education
  • AI Assisted Learning Modes Eeg β€” An exploratory behavioral and electroencephalographic study of artificial intelligence-assisted learning modes in hig...
  • AI Availability Student Motivation β€” Why Put in This Much Effort?": How AI Availability Shapes Students’ Motivation in Introductory Programming
  • AI Campus Wellbeing Tools β€” AI-Driven Tools for Enhancing Campus Well-being: Prevention and Intervention
  • AI Changing Teaching Workflows β€” How AI Is Changing Teaching Workflows
  • AI Education Global Capacity β€” What AI in Education Needs Next: Lessons from Youth Leaders Across Five Countries
  • Citation

    Institution, S.B. (2026). A New Direction for Students in an AI World: Prosper, Prepare, Protect