GUEST COLUMN | by Teddy Hartman
MUHAMAD CHABIB ALWI
As students return to school this fall, educators face a new reality: AI is integrated into many of the edtech tools teachers and students use every day. With 252,000+ new websites created daily, the digital universe our students inhabit expands at a dizzying pace. This explosion of content—both educational and harmful—has prompted a critical question from parents and educators: “Can we trust AI with our children’s data?”
The same AI capabilities that can identify a student in crisis or block harmful content must, by necessity, process identifiable student data to function. The challenge facing schools isn’t whether to embrace AI, but how to ensure these powerful tools respect the privacy rights of the students they’re designed to protect.
‘The challenge facing schools isn’t whether to embrace AI, but how to ensure these powerful tools respect the privacy rights of the students they’re designed to protect.’
Beyond the Checkbox: Real Privacy Engineering
Simply claiming FERPA and COPPA compliance no longer suffices when AI systems are making real-time decisions about student safety. True privacy protection requires what engineers call “privacy by design”—building data protection into the DNA of the technology itself.
This means AI systems that automatically minimize data collection, anonymize information at the point of capture, and delete unnecessary data without human intervention. When analyzing the 450 million digital events that flow through school networks daily to identify potential self-harm indicators, responsible AI should retain only the essential signals needed for intervention, discarding everything else immediately.
This approach represents a shift from reactive compliance to proactive protection. Rather than asking “What does the law require?” privacy-first organizations like GoGuardian ask “What’s the minimum data needed to keep students safe?”
The Human Cost of Getting It Wrong
Consider the reality facing today’s schools: youth mental health crises, cyberbullying, online predators, and an endless stream of inappropriate content just clicks away. Research indicates that properly designed AI systems and filters keep students focused and secure, and have helped prevent thousands of students from physical harm by providing time-sensitive information that counselors use to respond and intervene when minutes matter.
When a system alerts a counselor about a student in crisis, there’s no room for doubt about data handling. The technology must equip staff with the information needed to take the appropriate action, while being respectful enough to preserve dignity. Studies show that in regions where comprehensive digital safety systems are deployed, youth suicide rates were 26% lower, even when accounting for demographic and regional differences—evidence of what’s possible when privacy and safety work together.
This dual mandate shapes how responsible development should proceed. Safety and privacy must be foundational, not afterthoughts, engineered into every aspect of AI from algorithms to data flow.
‘Safety and privacy must be foundational, not afterthoughts, engineered into every aspect of AI from algorithms to data flow.’
Beyond Safety: Responsible AI in Curriculum and Instruction
The privacy imperative extends beyond student safety into the classroom itself. Recent research highlights how AI teaching assistants, while useful for tasks like grading and content creation, can pose significant risks if not properly designed. When AI generates educational content or provides instructional support, it processes student learning data, writing samples, and academic performance indicators—information just as sensitive as safety data.
These curriculum-focused AI tools must adhere to the same privacy-first principles. Whether helping teachers create differentiated lessons or providing real-time feedback to students, educational AI should collect only what’s necessary for the specific learning objective. The risk isn’t just data exposure—it’s the potential for AI to make instructional decisions based on incomplete or biased data, affecting student academic trajectories. Schools need the same transparency about how AI influences instructional practices as they do about student safety.
Transparency: Building Trust Through Clarity
When educational AI operates as a “black box,” it creates anxiety. But clear explanations transform fear into confidence.
Meaningful transparency means schools can tell parents exactly what data AI processes —search terms, URLs, or documents. They should know retention periods, access protocols, and escalation procedures. This openness demystifies AI, transforming it from an omniscient watcher into a tool with specific functions. When parents understand that AI flags patterns rather than recording every keystroke, technology becomes less threatening.
Transparency also empowers educators in curriculum and instruction. When teachers understand how AI processes student work samples, assessment data, and learning patterns to generate differentiated materials, they can make informed pedagogical decisions. It’s not magic—it’s responsible AI design that clearly shows the connection between data inputs and educational outputs. By demystifying how AI creates personalized lessons or adapts content for diverse learners, schools enable teachers to leverage these tools confidently while maintaining their professional judgment. This transparency shifts the conversation from “Is AI making decisions about my students?” to “How can AI enhance my instructional practice and teach more students?”
Lessons from the Field
After years of AI deployment in K-12 education, several principles have emerged:
Human judgment remains paramount. AI should amplify educator capabilities, not replace teacher intuition. When systems flag concerning behavior, trained professionals must interpret context and determine appropriate responses.
Less is often more. The most effective AI systems often collect the least data, focusing on specific signals rather than comprehensive surveillance.
Scale requires responsibility. When technology serves millions of students, every design decision has widespread impact. This reach demands leadership in establishing industry standards.
Community involvement matters. Schools that actively engage parents and students in understanding their AI tools see better outcomes and higher trust levels.
The Path Forward
As another school year begins, the education community stands at a crossroads. We can continue down the path of opaque, data-hungry AI systems that prioritize features over privacy. Or we can demand better—AI tools that protect students while respecting their fundamental rights.
‘We can continue down the path of opaque, data-hungry AI systems that prioritize features over privacy. Or we can demand better—AI tools that protect students while respecting their fundamental rights.’
The technology exists to do both. Modern AI can identify threats, support learning, and empower educators while maintaining the highest privacy standards. The question isn’t technical—it’s one of values and priorities.
For schools evaluating AI solutions, the trust factor should be non-negotiable. Ask tough questions about data handling. Demand transparency about algorithms. Insist on privacy by design, not privacy by policy.
Because ultimately, the promise of AI in education isn’t just about efficiency or even safety—it’s about creating digital environments where students can learn, grow, and thrive without sacrificing their privacy. That’s not an impossible standard. It’s the minimum our children deserve.
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Teddy Hartman, a former high school educator and school district privacy administrator, leads privacy and trust initiatives at GoGuardian, where he works to ensure that educational technology respects student privacy while enabling critical safety interventions and empowering educators with transparent, responsible AI tools for curriculum and instruction across millions of K-12 students. Connect with Teddy via LinkedIn.
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