Evolving relationships with AI systems

AI systems learn and adapt over time, and users' relationships with these systems similarly change through distinct phases. New smart home users might need step-by-step guidance to set up basic features, while longtime users want shortcuts and personalization options. Good design anticipates this evolving relationship and creates appropriate touchpoints throughout the journey.

Design patterns supporting this evolution include:

• Adaptive onboarding that adjusts based on user expertise, showing fewer instructions as users demonstrate proficiency
• Periodic check-ins that invite reflection on system performance, asking about users’ experience lately
• Explicit preference setting rather than silent adaptation ("We noticed you often skip songs by this artist. Should we play fewer like this?")
• Meaningful memory of past interactions.

This approach also considers how to gracefully handle endings, whether temporary breaks or permanent departures, with appropriate data portability and deletion options. Effective evolution design creates systems that grow with users over time, accommodating changing needs while respecting boundaries.