Shape
How do we make it real, and keep it relevant?
Build and refine anticipatory experiences that balance automation with control, calibrate trust, and evaluate against real user outcomes.
Behavioral Alignment
Who's in control, and when?
Match the level of autonomy to the stakes, with clear override and feedback.
Interaction-control protocols across the levels of autonomy: from simple adjustments to advanced customisation of the system's decisions.
Read the guide →
Feedback loops and recovery mechanisms that keep the user aware of system state and able to act, especially during errors and failures.
Read the guide →
Prototyping
How do we build trust?
Prototype personalization and the four components of trust.
Trust-building features tested across scenarios against Kore's four components of trust: competence, reliability, predictability, benevolence.
Read the guide →
A progressive-disclosure pattern for explanations: surface (one line), detail (structured reasons), full (provenance + confidence), matched to the stakes of each decision.
Read the guide →
Evaluation
How do we keep it relevant?
Measure against user outcomes and re-run over time. This is where AI-UX Score lives.
A respondent-backed measure of the AI experience across seven dimensions of trust and usability, run as part of ongoing evaluation.
Read the guide →
A two-layered measurement practice: A/B tests for short-term causal attribution, longitudinal cohorts for behavioural drift over weeks and months.
Read the guide →