Articles

Kate Moran

Kate Moran is a former NN/G employee who worked on research, teaching, leadership, and design thought leadership. Her expertise spanned both qualitative and quantitative research methods. At NN/G Kate discovered and published ground-breaking findings on artificial intelligence (AI), interaction design, digital content, and information-seeking user behaviors.

Articles and Videos

  • A Millennial’s DVD Collection: I’m Returning to Physical Discs

    Frustrating streaming apps and smart TV design pushed at least one user (me) back to physical discs for reliability, ownership, and simpler choices.

  • How AI Succeeds (and Fails) to Help People Find Information

    AI chat and search lets users describe needs without exact keywords, but many don't know AI's full capabilities or how to prompt effectively.

  • How AI Is Changing Search Behaviors

    Our study shows that generative AI is reshaping search, but long-standing habits persist. Many users still default to Google, giving Gemini a fighting chance.

  • The 3 I’s of Microcopy: Inform, Influence, and Interact

    Microcopy can have three different purposes: informing users, influencing them, and supporting their interaction.

  • Designing Use-Case Prompt Suggestions

    Use-case prompt suggestions show how to effectively prompt AI tools. They aid learnability and creativity, helping users explore what AI tools can do.

  • CARE: Structure for Crafting AI Prompts

    To get better results from generative-AI chatbots, write CAREful prompts. Include context, what you’re asking the system to do, rules for how to do it, and examples of what you want.

  • Prompt Suggestions

    System-generated suggestions for AI prompts must be contextually relevant, personalized, and specific to the task and the user’s level of experience.

  • Synthetic Users: AI “Participants”

    Synthetic users are fake users generated by AI. While there may be a few use cases for them, user research needs real users.

  • Your AI UX Intern

    Work with AI tools in UX the way you’d work with an intern: Treat their work as a first pass, double-check their facts, and provide specific instructions.

  • Discoverability of AI Features: Learn from Amazon’s Mistakes

    Even AI features that offer value won’t be used if people don’t notice them. Consider existing mental models and design best practices to increase engagement.