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
"A design system is never a done thing, it’s a continuous evolution of best practices."
Dan DonaldDesign Systems as a Vehicle for Systemic Change
June 1, 2023
"Move fast and break things doesn’t work when you’re designing for cancer patients or disaster victims."
Barb SpantonDoing Work That Matters: A Look Beyond The Idealistic Notion of 'Doing Meaningful Work'
June 10, 2022
"A viable service is one that not only functions well but can also develop, grow, and flourish."
Laura Smith Tom GaylerEmbedding Service Design and Agile Practice within UK Planning Teams to Create Services that Last
December 3, 2024
"It was taking an average of 14 days from intake to delivery for most of our research projects."
Marjorie Stainback Kelsey KingmanTransforming Strategic Research Capacity through Democratization
October 24, 2019
"Excel is the mental model of the scientific research world—a two-dimensional grid of literal data."
Victor Lombardi Ted Booth HK Dunston Andrew OtwellBridging Design and Climate Science
February 14, 2024
"Attrition is real and painful but also an opportunity if we have a deep and broad hiring funnel."
Jennifer Bolduc Diane Gregorio Emily DayWhat's involved with getting people back to work?: A panel discussion
July 1, 2021
"Look at your old data again with a new lens; reanalyzing can save money and be less extractive."
Dane DeSutterKeeping the Body in Mind: What Gestures and Embodied Actions Tell You That Users May Not
March 26, 2024
"We calculated nearly 10,000 hours saved in one year from redesigning compliance training, equating to three million dollars in opportunity cost."
Julie BaherCulture Change—My Journey
May 14, 2015
"A simplifier can explain complex situations in the easiest way possible without losing nuance."
Kate SternScaling Learning for the Future
September 9, 2022