How to Use These Guides
- Before meetings: Prepare questions for AI project reviews or board discussions
- During decisions: Ensure you're considering the right factors
- For development: Identify areas where you want to build capability
Responsible AI
Are we doing the right things? — Related Briefing
Ethics & Accountability
Transparency, human oversight, and clear responsibility when AI makes consequential decisions.
Bias & Fairness
Preventing algorithmic discrimination and ensuring equitable treatment across all groups.
IP & Creative Sustainability
Training data provenance, creator rights, and building sustainable AI ecosystems.
Economic Transition
Managing automation impact, workforce transition, and strategic capability building.
Responsive AI
Can we adapt to change? — Related Briefing
Technology Evolution
Adopting new capabilities while managing technical debt and maintaining stability.
Societal Expectations
Tracking and responding to shifting public attitudes and stakeholder demands.
Organisational Learning
Building adaptive capacity through cross-functional governance and continuous learning.
Robust AI
Do our systems actually work? — Related Briefing
Security & Adversarial Resilience
Protecting against AI-specific attacks and supply chain vulnerabilities.
Reliability & Performance
Ensuring consistent operation across conditions, populations, and edge cases.
Data Integrity & Quality
Building on solid data foundations with provenance, quality, and drift monitoring.
Operational Resilience
Maintaining continuity through dependency management, redundancy, and recovery testing.