Tag: human-ai-interaction

Calibrated trust means users rely on AI when evidence supports it, question it when uncertainty is high, and never confuse a confident interface with dependable capability.

Tool-using AI turns motivation design from advice into execution, making permissions, visible state, recovery, and user control part of the motivational experience.

Capability discovery should teach users what an agent can and cannot do through progressive, contextual demonstrations rather than vague claims of intelligence or giant tool catalogs.

Relationship meters can clarify how an AI companion responds, but gamifying affection, exclusivity, or dependency can turn useful feedback into synthetic intimacy and pressure.

A good AI coach has an exit condition: as competence and self-regulation grow, it should fade prompts, transfer responsibility, and make independent action easier.