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
"We went from a team of 80 to 170 overnight, and that was a wide open cheeks flushed moment for me."
Isaac HeyveldExpand DesignOps Leadership as a Chief of Staff
September 8, 2022
"Getting accessibility integrated into all company processes is essential because accessibility is a culture change."
Sam ProulxUnderstanding Screen Readers on Mobile: How And Why to Learn from Native Users
June 6, 2023
"Diverse teams build diverse products."
Sam ProulxAccessibility: An Opportunity to Innovate
March 9, 2022
"You’re hired for the wrong reasons—those buzzwords and expensive stamps aren’t what really make you successful."
Mackenzie GuinonM.C. Escher’s UX Research Career Ladder
March 9, 2022
"As a civic designer, it’s really up to you to hold managers accountable for their promises on inclusion."
Yalenka Mariën Marie MervaillieDesigning for Digital Inclusion in the Belgian Government
December 8, 2021
"Budget and time are the enemies of inclusivity in research."
Chloe Amos-EdkinsA Cultural Approach: Research in the Context of Glocalisation
March 27, 2023
"Advanced quantitative methods can amplify our work in ways we didn’t expect, and also show us how to get started."
Megan BlockerTheme 2 Intro
March 12, 2025
"The prompt becomes part design spec, part requirement doc, and part programming language."
Josh Clark Veronika KindredSentient Scenes and Radically Adaptive Experiences
June 11, 2025
"If AI makes building trivial, the challenge shifts to figure out who’s best to decide what to make."
Erin MaloneUnderstanding the past to prepare for the future
July 19, 2024
