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 realized that everyone kind of has a different definition of the voice of customer and that we needed to define our own to make it relevant for us."
Anna Nguyen Emily BroganWhy Our Voice of the Customer is Better Than Yours
March 10, 2022
"The ultimate measure of our research is its impact—did we build the right thing and did it have the expected effect?"
Dr. Jamika D. Burge Robert Fabricant Peter Merholz Noam Segal Teresa TorresA Genuine Conversation about the Future of UX Research
March 20, 2024
"Duplicative research will become less acceptable; researchers must act as natural connectors to reduce it and enhance organizational knowledge sharing."
Jemma Ahmed Megan Blocker Eduardo OrtizRedefining the research toolkit: Expanding methodologies for a changing world
March 12, 2025
"People are starting to catch on with the fact that design matters and that it’s maturely important to solving the problems we face."
Greg PetroffSoftware as Material—A Redux
June 6, 2023
"That unit there is kind of like a sprint."
Jim KalbachJazz Improvisation as a Model for Team Collaboration
June 4, 2019
"We actively reduced jargon to make our process accessible for non-designers."
Alexia Cohen Adriane AckermanIncreasing Health Equity and Improving the Service Experience for Under-Served Latine Communities in Arizona
December 4, 2024
"Design leaders actually like having a strategic partner to focus on the how and when so they can focus on the what and why."
John CalhounHave we Reached Our Peak? Spotting the Next Mountain For DesignOps to Climb
October 1, 2021
"My goal for today is to showcase how generative AI can go beyond just speeding up our processes to actually catapult us in our career."
Fisayo Osilaja[Demo] The AI edge: From researcher to strategist
June 4, 2024
"Allow people to tell you how trauma extraction feels; don’t assume based on your cultural lens."
Matt Bernius Sarah Fathallah Hera Hussain Jessica Zéroual-KaraTrauma-informed Research: A Panel Discussion
October 7, 2021
Latest Books All books
Dig deeper with the Rosenbot
What does a successful healthcare UX career look like in terms of accumulating influence and aligning with clinical/business goals?
How does User Interviews use AI to improve participant matching and reduce fraud?
Is it possible to bypass HIPAA by initially targeting veterinary markets for clinical app development?