Existing AI Design Patterns
In this lesson, we will discuss key interaction design patterns for AI-powered products. These patterns emphasize the importance of combining effective AI with strong UX, while addressing both established practices and emerging challenges.
Summary
Education and NUX: Effective onboarding through upfront and contextual education, using examples like Duolingo and DOT.
Contextual UI: Strategies like inline actions, side panels, and quick actions to offer users more control.
Addressing the Cold Start Problem: Solutions like icebreakers, templates, and guided input to help users get started.
Continued Guidance: Providing suggested prompts and contextual assistance to keep users engaged.
Personalization: Customizing user experiences through memory, suggestions, and personal input options.
Enabling Experimentation: Allowing users to preview, undo, and retrace steps for enhanced control.
Feedback Mechanisms: Implementing thumbs-up/down ratings and regeneration options for better AI refinement.
Providing Controls: Offering users tools like source verification, image editing, and content manipulation for more control over AI outputs.
Transparency: Ensuring trust by watermarking AI content, labeling generated text, and clarifying data usage.
Voice and Streaming: Exploring voice interactions and message streaming patterns to create seamless experiences.