Original research on AI risk to children

Submitted to the Department for Science, Innovation and Technology consultation on extending Online Safety Act obligations to AI services. Presents original quantitative findings from DigiShield Kids' open-source AI intelligence programme — covering HuggingFace model proliferation, consumer-hardware deployment, abliteration lag analysis across a 57-model panel, and Chub.ai character card data — alongside six policy recommendations addressing the s.216A definitional gap, model disclosure requirements, and criminal liability for harmful character card manufacture.

Phase One of DigiShield Kids' open-source AI intelligence programme. Assessment of 59 AI chatbot platforms against child safety criteria, finding an 85% bypass rate and 91.5% of platforms rated Poor or Critical. Submitted to Ofcom, DSIT, ICO, 5Rights, and AI developers during responsible disclosure. The first structured independent assessment of its kind in the UK regulatory context.

Intelligence note on the accidental disclosure of approximately 512,000 lines of Anthropic Claude Code source code on 31 March 2026. Documents three findings with direct policy relevance: the KAIROS autonomous persistent agent architecture; Undercover Mode (AI identity concealment, on by default); and autoDream (self-directed memory consolidation). Sets out child safety implications and a single policy recommendation on mandatory AI identity disclosure. Submitted as Annex B to DigiShield Kids' DSIT consultation response.

The DigiShield Human–AI Synergy Framework is a practice-oriented model for the transparent, structured, and educationally purposeful use of AI tools in school and educational settings. It is designed for use by students, teachers, and school leaders across Key Stages 1–5 and further education, and it is equally relevant to the safeguarding professionals, governors, and policymakers who support those settings.