Log in or create a free Rosenverse account to watch this video.
Log in Create free account100s of community videos are available to free members. Conference talks are generally available to Gold members.
Designing with and for Artificial Intelligence
This video is featured in the Josh's test playlist playlist.
Summary
Rapid advances in Artificial Intelligence and machine learning are transforming the world in many ways. For the product designer or design strategy practitioner this megatrend manifests itself in 2 orthogonal dimensions: AI as a product design material – AI enables solutions that are smarter, faster and can answer questions well beyond human capability alone, but you must deploy them effectively and responsibly to be successful. AI designing the product for you – AI generation of competent oil paintings and music based solely on a set of input requirements has been repeatedly demonstrated in the past decade. Emerging AIs can design entire digital user experiences, code them, and deploy to the cloud with one button click. While AI automation can provide huge benefits in both megatrend dimensions it carries spectacular risk when deployed within life and death systems such as autonomous vehicles and medical products. Concurrently, generative AI for product design carries significant liability risk plus the potential of employment disruption for creative and strategic job careers.
Key Insights
-
•
AI in UX splits into using AI as a design material versus AI augmenting or replacing designers in creative processes.
-
•
Soft AI, which uses structured data and domain rules, is more explainable and suitable for critical applications like genomics than hard AI.
-
•
Trust and perceived credibility in AI-driven medical systems depend heavily on both explainability and interface design quality.
-
•
The genomics AI case analyzes massive, changing DNA variant data impossible for humans alone to process in real time.
-
•
Ben Schneiderman’s classification of AI as super tools or teammates helps frame AI’s role in augmenting human work.
-
•
Clean Software’s AI builds entire UX workflows and code through semantic interaction models, speeding up app development for enterprises.
-
•
Generative AI UX designs face risks like sameness and depend heavily on accurate, high-quality input data to avoid creating useless outputs.
-
•
AI can accelerate UX exploration by generating multiple alternatives quickly, supporting iterative design and decision-making.
-
•
Accessibility and localization best practices can be baked into AI-generated UX code automatically.
-
•
Ethical and regulatory oversight become crucial when AI influences high-risk decisions like clinical diagnoses.
Notable Quotes
"If you don’t trust it, then there’s nothing here."
"The AI is looking through material and that material’s changing every day."
"Visual design quality actually affects perceived trustworthiness."
"You can’t evaluate bias if the AI can’t explain itself."
"Garbage in, garbage out—if the requirements are wrong, the AI will instantly create a useless UX."
"You don’t want to game anybody here. This is persuasion by evidence, not by trickery."
"The marketplace is going to decide if it’s close enough in cost-benefit tradeoff."
"AI-generated UX is not about replacing designers, but removing grunt work to focus on higher-order design."
"Human beings understand graphical user interfaces as composed of objects and actions—this grammar is key to AI design."
"The future was already here. It’s just not evenly distributed."
Or choose a question:
More Videos
"AI prototypes can get lost on Slack because they're not always collaborative or integrated yet."
Shipra Kayan Robert Kortenoeven Eileen TangEmerging principles for using AI in Design: What the product design team at Miro has learned from deeply integrating AI in their workflow
June 11, 2025
"Daniel Day-Lewis went so far as to suffer three broken ribs immersing in his role for My Left Foot."
Daniel GloydDesigning From the Inside Out: How Method Acting Can Inspire Design Research
February 12, 2026
"It’s not that our subscribers aren’t smart, they just don’t always feel smart."
Louis RosenfeldYou’ve got Gold! A Rosenverse demo with Lou Rosenfeld
June 9, 2026
"Different perspectives across functions generate insights you never would have thought of on your own."
Brad Orego Ned DwyerBringing Customer Research to More Internal Teams
March 10, 2022
"It’s a muscle to build: agreeing on goals, measuring, learning, and adjusting over time to avoid wasted effort."
Christian Crumlish Aditi Ruiz Johanna Kollmann Catt SmallMorning Insights Panel
December 6, 2022
"Care is defined as the process of protecting someone or something and providing what that person or thing needs."
Etienne FangThe Power of Care: From Human-Centered Research to Humanity-Centered Leadership
March 10, 2021
"If you falsely think you are having the same experience as a native user, you become afraid of accessibility and say it's impossible."
Sam ProulxUnderstanding Screen Readers on Mobile: How And Why to Learn from Native Users
June 6, 2023
"Research has layers like an onion; we operate at multiple layers, from discovery to concept evaluation."
Anna Poznyakov Richa PrajapatiGet The Most Out Of Stakeholder Collaboration—and Maximize Your Research Impact
March 12, 2021
"Nobody wants to do evals because it's hard work, but for UX people, it's interesting and fascinating."
Peter Van DijckBuilding new AI skills: Creating outsized UX value with evals
June 10, 2026
Latest Books All books
Dig deeper with the Rosenbot
How can designers handle modality routing between voice, chat, UI, agents, and human support?
What lessons can we learn from Corridor Digital’s open-source AI project about community-driven design?
What new workflows or tools have been effective in bridging the gap between design, engineering, and product teams using AI?