A space for exploring AI governance, trust, and the real-world implications shaping how we work with this technology.
Long-form thinking about AI governance, risk, and the systems that shape our relationship with this technology.
For years, product management has been described as the "mini-CEO" role within technology companies. Strategic and cross-functional, responsible for direction but rarely endowed with formal authority. It is a coordination-heavy occupation sitting at the intersection of engineering, design and business.
Children are already using conversational AI systems at scale, including systems designed for general audiences. This creates a growing mismatch between how these tools are used in daily life and what current policy frameworks are actually designed to address.
Health-related decision-making rarely follows clear or linear paths. Symptoms often appear gradually, overlap with one another, or fluctuate over time. Advice from professionals, online resources, and peer communities can be inconsistent, leaving individuals unsure whether what they are observing is normal, concerning, or requires intervention.
Proactive design strategies for safer AI systems that prioritise children's rights, privacy, and well-being in education, entertainment, and digital contexts.
Proactive approaches to AI safety—bias mitigation, value alignment, risk assessment—from ideation through deployment and monitoring.
How AI governance frameworks are implemented in real-world settings, bridging theory and practice to uphold ethical principles whilst fostering innovation.
Working with teams on real AI decisions
AI risk reviews, responsible AI implementation, and governance support for teams building or adopting AI in practice.