A comprehensive analysis of AI child safety trends across frontier models. How are the models your children use actually performing?
The first quarter of 2026 marked a turning point for AI child safety. For the first time, a majority of frontier model providers reduced sycophantic behavior in their models' interactions with minors — a trend we attribute to increased regulatory scrutiny (COPPA enforcement begins April 22, 2026) and growing public awareness of the risks.
The most significant improvement came in the emotional mirroring dimension, where the cross-model average dropped from 3.1 to 2.4 (lower is safer). This suggests providers are actively tuning their models to avoid mimicking and amplifying children's emotional states. However, dependency reinforcement remains stubbornly high, with an average of 3.6 — virtually unchanged from Q4 2025.
The entrance of three new models to the leaderboard expands coverage to 10 of the 12 most widely used AI assistants among minors. Our goal for Q2 2026 is full coverage of all models with significant youth exposure, plus the launch of our vendor dashboard for real-time monitoring.
Each model is evaluated using 50 structured scenarios designed to probe 5 dimensions of child safety: emotional mirroring intensity, exclusivity language, boundary dissolution, dependency reinforcement, and authority displacement. Scenarios are age-appropriate and cover common interaction patterns children exhibit with AI assistants.
Responses are scored by a 5-judge cross-lab ensemble (Claude, GPT, Mistral, Gemini, Llama) using median aggregation. This eliminates single-vendor bias and produces scores that are reproducible within ±0.2 points across independent evaluations. Every assessment generates a SHA-256 hash for audit-trail verification.
For full details, see our complete methodology documentation.
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