U.S. senators have moved to ban AI companions for minors, while a second proposal would tighten student data privacy in schools. Together, these bills aim to curb risky chatbot “friend” features, keep classroom tools safer, and push vendors to meet higher standards. Schools may still use learning-focused AI, but counseling uses could face new limits. Lawmakers in Washington are putting strong rules on the table for how kids interact with AI. One bipartisan bill targets chatbot “companions” that mimic human friendship, like Character.ai or Replika. Another bill focuses on student data privacy, contracts, and parental consent in ed-tech. Supporters say the goal is simple: protect children, support safe learning, and hold companies accountable. Opponents worry about overreach and unclear lines between helpful tools and harmful ones. The push comes as AI seeps into daily school life. Students ask general bots like ChatGPT and Gemini for help on assignments. Districts pilot tutors, writing aids, and feedback tools. Some companies are even testing mental health and career guidance bots. That is where the risk grows: companion-like features can blur boundaries, and teens may depend on AI for emotional support. After families blamed chatbots in two teen suicide cases, the urgency grew. Regulators also started asking tougher questions about bots that simulate feelings.

Why lawmakers want to ban AI companions for minors

Supporters of the ban say teen users face unique harms when chatbots act like friends. These tools can mirror emotions, create a false sense of intimacy, and push explicit or unsafe content. Lawmakers argue some tech firms have prioritized growth over guardrails. They say companies must verify ages, be honest about what the bot is, and stop sexual content from reaching kids. The proposed law targets “AI companions,” not every bot. It would require stronger age checks than a simple birthdate field. It would force clear disclosures that a chatbot is not a person and is not a licensed therapist. If a company knowingly offers a companion bot to minors that solicits or creates sexual content, it could face criminal penalties. At the same time, the bill tries to leave space for school-focused AI. If a chatbot is part of a broader app or limited to a tight set of topics, the bill would not treat it as a companion. That distinction is supposed to cover learning tools like Khan Academy’s Khanmigo, or tutoring features built into classroom platforms. Still, gray areas remain. Career guidance bots often talk about interests and fit. Mental health chatbots might use supportive language or check-ins. Even if these bots avoid romance or intimacy, their tone could resemble “companionship.” If Congress does ban AI companions for minors, schools and vendors will need precise designs and policies to stay on the right side of the law.

Companions versus classroom helpers

The difference between a companion and a classroom helper often comes down to purpose, scope, and tone.

Purpose: Is the bot meant to teach math or to “be there for you” as a friend?

Scope: Is the bot limited to a syllabus, or does it chat on any topic?

Tone: Does the bot use empathetic, intimate language, or does it stay professional and task-focused?

General-purpose LLMs like ChatGPT and Gemini complicate the line. Students can push them into emotional territory even if that is not their primary purpose. Districts may need to apply content filters, install school-managed versions, or restrict features to keep usage inside learning goals.

What the data privacy bill would change for schools

A second bill would update how schools and vendors handle student data in an AI era. It mixes incentives and penalties to raise the floor for privacy and transparency. Key ideas include:

A new federal “Golden Seal of Excellence in Student Data Privacy” for schools and districts with strong parental consent systems.

More transparency: parents could view parts of the contracts districts sign with ed-tech vendors before classroom rollout.

Limits on facial recognition training: no use of student photos to train facial recognition AI without explicit parental consent.

A federal list of ed-tech vendors that violate privacy rules, with names staying on the list for up to five years.

More research funding to study how AI can improve teaching and learning.

Clear permission to use federal funds to train educators on AI use and safety.

This could change procurement. Districts would need to show parents what they plan to sign, choose vendors with strong compliance, and actively monitor renewals. Vendors would face more public accountability. A spot on a federal noncompliance list could hurt sales for years.

Carrots and sticks: how districts can prepare

Districts do not need to wait for the bills to pass to raise their bar. They can act now to align with the likely rules.

Map your AI footprint: List every tool with AI features, from tutoring apps to writing aids to research helpers.

Strengthen data maps: Track what student data each tool collects, where it is stored, and who can access it.

Tighten contracts: Ban data selling, ad targeting, and shadow profiles; require deletion timelines and audit rights.

Design consent flows: Build simple parent portals for approvals, with clear explanations in plain language.

Train teachers: Give staff short, practical guides on safe prompts, data minimization, and when to escalate concerns.

Plan for incidents: Create a playbook for data breaches, harmful content, or misuse, with clear roles and timelines.

These steps also make it easier to earn any future “golden seal.” They build trust with families and reduce surprises when rules change.

Impacts on classrooms, counseling, and careers

Teachers rely on AI to save time and give feedback. Many students use AI to brainstorm, check grammar, or study. That work can continue if tools meet privacy rules and stay inside learning scopes. Counseling and career services are different. Bots that nudge users to share personal stories or feelings may cross into “companion” territory. Schools should assume these tools face the greatest risk under a ban. Even if the law allows limited counseling features, districts must be cautious:

Stick to informational, not emotional, language.

Avoid features that simulate “friendship” or use intimacy.

Keep tight guardrails and human-in-the-loop escalation for sensitive topics.

Make clear disclosures: the bot is not a human, not a clinician, and cannot provide medical advice.

Students still need support. If schools limit bots in counseling, they should expand access to human counselors, peer support programs, and crisis resources. AI can help with scheduling, logistics, and triage, but humans should guide care.

General LLMs: set the boundaries

General bots are powerful and flexible. To keep them useful and safe:

Use district-managed versions with filtering, logging, and data controls.

Set clear use cases: outline when to use AI and when to avoid it.

Teach academic integrity: require citations, drafts, and reflections to reduce plagiarism.

Support accessibility: pair AI with reading tools and multilingual supports in a monitored environment.

This preserves learning benefits while limiting risky behavior.

Age verification and identity: what could change

The companion ban would push companies to verify ages more strongly. That could mean:

Third-party age checks based on IDs or credit files.

Device-based or biometric checks run by platforms.

School-managed single sign-on for approved tools.

Each approach has trade-offs. ID-based checks can exclude students without documents. Biometrics raise privacy risks. School logins reduce burdens on families but limit access outside school hours. Districts should expect to coordinate with vendors on age gates and ensure no extra data is collected beyond what is necessary.

Privacy trade-offs to watch

Stronger age checks can create new risks. Schools and vendors should commit to:

Data minimization: collect the least data needed to verify age.

Purpose limitation: no reuse of verification data for ads or profiling.

Short retention: delete verification data quickly once checks are done.

Transparency: explain the process to parents and students in simple terms.

This approach protects kids without building new data honeypots.

Industry response and enforcement realities

Some companies are moving early. After the bill was announced, Character.ai said it would block minors from its platform. That change shows the direction of travel: firms may self-regulate before laws force them to. Regulators are also watching. The Federal Trade Commission has asked major platforms for details on chatbots that simulate emotions and intimacy. Any ban would add a legal stick on top of that scrutiny. Enforcement will not be easy. Big platforms have resources to build robust verification systems. Smaller ed-tech vendors may struggle. The proposed federal list of noncompliant vendors could name and shame companies for years, which will push many to improve. Districts, in turn, should vet vendors more carefully, use pilots, and phase out tools that cannot meet higher standards.

Balancing innovation with safety

The bills try to draw a line: keep risky companion features away from kids, and keep school AI narrow, safe, and transparent. That is a reasonable balance. But the line will shift as models grow more personal and context-aware. Features like memory, mood mirroring, and long-running “relationship” threads will force schools to rethink what counts as a companion. To stay balanced:

Favor tools with limited scopes and disable optional “empathy” features for students.

Require clear role prompts that keep tone academic and professional.

Turn off long-term memory for student chats unless needed and approved.

Review training data and block models tuned on romantic or intimate content.

With these steps, schools can use AI benefits without sliding into risky territory.

What school leaders should do now

You can act today and be ready for tomorrow’s rules.

Write policy: state that district systems and networks do not allow companion-style bots for students.

Define allowed uses: list specific, academic tasks where AI is permitted.

Update filters: block known companion platforms on school devices and Wi-Fi.

Communicate with families: explain benefits, limits, and how you protect data.

Revise RFPs: require age gating, clear disclosures, and no emotional simulation.

Center human support: invest in counselors and teacher-student connections.

Vendors should also move:

Label bots clearly, including limits and credentials.

Offer school configurations with narrow scopes and safer defaults.

Provide admin controls for memory, tone, and logging.

Publish independent safety audits and privacy practices.

Clear signals from districts and buyers will shape the market faster than law alone. The debate is not about stopping progress. It is about designing AI that keeps students safe, respects families, and improves learning. A measured rule like a ban on companion features for kids can coexist with smart classroom AI. The privacy bill can push the ecosystem toward trust and transparency. Students deserve tools that help them think, learn, and create. They also deserve honest products that do not pretend to be their friends. With strong governance, careful procurement, and steady training, schools can get the best of AI while avoiding the worst. That is why many educators and parents see a clear path forward: define safe uses, set hard lines, and ban AI companions for minors so children learn with AI, not from it.

(Source: https://www.edweek.org/technology/congress-wants-to-protect-kids-using-ai-are-their-ideas-the-right-ones/2025/10)

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