Evidence

Selected work and research

Research, frameworks and projects across the people making, working with and experiencing AI.

Trust by Design

Trust isn't a branding exercise, and it doesn't appear automatically when technology works. It has to be designed: through transparency, control, explainability, honest communication of uncertainty, human oversight and accessibility, so that people's trust matches what the system can actually do.

Trust by Design is the research foundation under this practice. I developed the framework through embedded research with more than 14 public sector AI implementation teams.

Explore Trust by Design

ExplainabilityCan people understand what the system did and why?
OverrideCan they question, stop or correct it?
RecoverabilityCan they get back on track when it goes wrong?
AccountabilityIs it clear who is responsible?

AI Learning Pathways
Research-driven, role-based approaches for moving employees from awareness to applied AI capability.
AI Adoption Research
Understanding barriers, behaviours, confidence, workflows and organisational readiness.
Agentic Experience Prototypes
Exploring how humans understand, supervise and collaborate with AI agents.
AI Self-Service
Exploring how automation can simplify complex services without removing human agency.
Trust by Design
Research and a framework for trustworthy AI experiences, built with public sector AI implementation teams.
Responsible AI and Governance
Translating rules and principles into understandable human decisions and product behaviour.
Human-Centred AI Research
Research into expectations, mental models, accessibility, trust and human oversight.

Each project shows which of the three perspectives it involves and which method stages it covers.

Trust by Design

AI Learning Pathways

AI Adoption Research

Agentic Experience Prototypes

AI Self-Service

Trust by Design

Responsible AI and Governance

Human-Centred AI Research