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.
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
"At DTA, distributed teams and lack of local diversity meant everyone was out in the field a lot to get diverse input."
Leisa ReicheltOpening Keynote: Operating in Context
November 7, 2018
"What exactly did you observe that makes you say that? What past experience let you think that way?"
Lin NieWhen Thought-worlds Collide: Collaborating Between Research and Practice
March 10, 2021
"Those days are over this new big tech is coming in so time to move on."
Dan HillStrategic design, slowdown, and the infrastructures of everyday life
April 21, 2022
"When organizations have regime change, shifting high leverage points can cause catastrophic effects, sometimes destructive and unintended."
Erin Hoffman-JohnThis Game is Never Done: Design Leadership Techniques from the Video Game World
November 6, 2017
"I walked into the building and it just felt surreal. It didn’t feel right in my body to be there anymore."
Mary-Lynne WilliamsExit Interview #4: From Product Design Leadership to Sound Healing
January 14, 2026
"Participants can skip any questions they don’t feel comfortable answering; most demographic questions are optional to respect privacy."
Lisa Spitz Nikki BrandBuilding Trust Through Equitable Research Practices
November 18, 2022
"Evals are the key to knowing when an AI’s output is good enough."
Peter Van DijckBuilding impactful AI products for design and product leaders, Part 1: The new product journey
July 16, 2025
"Creating one adopted component can be harder than creating a hundred that never get used."
Nathan CurtisDesign Systems for Us: How Many One-Source(s)-of-Truth Are Enough?
January 17, 2019
"Research is research. An executive doesn’t care which team conducted it."
Andy WarrUnder My (Research) Umbrella: The Benefits and Challenges of Building a Unified Insights Function
March 25, 2024