Summary
Ovetta will talk with us about reinvigorating the practice by incorporating Design Anthropology into our research tool-kits and further broadening our set of methodologies to include new research methods for AI/ML design.
Key Insights
-
•
Design and research are inseparable and symbiotic in AI system development.
-
•
In an automated future, deciding what not to design is as important as what to design.
-
•
Machine learning models rely on historical data and lack active environmental interaction.
-
•
AI systems introduce multi-agency contexts where humans and machines share control.
-
•
Traditional software is static and task-based; AI is dynamic and decision-based.
-
•
Researchers must be highly literate in AI and data to influence fairness and reduce bias.
-
•
Design anthropology helps surface human values, culture, and rituals for AI design.
-
•
Explainability in AI models is critical but challenging, especially with deep learning.
-
•
Model governance provides external auditing to ensure fairness and equity in AI.
-
•
Future-oriented, speculative research is essential as users often can’t articulate AI needs upfront.
Notable Quotes
"Design is the conscious and intuitive effort to impose meaningful order to chaos."
"Research is design; they are two sides of the same coin."
"Our role as designers is to determine what technology should not do, not just what it can do."
"Machine learning focuses on problem solving based on past observation, not active interaction."
"The relationship between users and AI is multi-agency: the user, the machine, and the environment all have agency."
"Traditional software interaction is one-way; AI systems require two-way communication between user and machine."
"Nuance is the enemy of machine learning and AI."
"You cannot affect the outcome of a model at the end; you have to influence data collection first."
"Explainability means turning AI from a black box into a glass box through model governance."
"We must seek unexpressed rituals, cultures, values, and irrational practices that make us distinctly human."
Or choose a question:
More Videos
"Teaching product managers heuristics took 15 minutes, and now they use that shared language to articulate design."
Standardizing Product Merits for Leaders, Designers, and Everyone
June 15, 2018
"Building a map is like learning to play chess—you have to see the board to decide your move."
Simon WardleyMaps and Topographical Intelligence (Videoconference)
January 31, 2019
"There’s a gap between intentions and impact; humility is needed to close it."
Sandra CamachoCreating More Bias-Proof Designs
January 22, 2025
"We’re all capable of creating and perpetuating toxic work relationships."
Darian DavisLessons from a Toxic Work Relationship
January 8, 2024
"After each interview, I input the transcript into ChatGPT and ask for three key takeaways that I can quickly share with stakeholders."
Fisayo Osilaja[Demo] The AI edge: From researcher to strategist
June 4, 2024
"Working with CEOs like Mark Templeton is like Dancing with the Stars — an interpretive dance of translating fuzzy ideas."
Uday GajendarThe Wicked Craft of Enterprise UX
May 13, 2015
"What’s so difficult about designing a login? On the surface, it’s simple, but the real challenge was cultural alignment across business units."
Davis Neable Guy SegalHow to Drive a Design Project When you Don’t Have a Design Team
June 10, 2021
"People felt designs were self-evident and too much explanation was a barrier to using the patterns."
Eniola OluwoleLessons From the DesignOps Journey of the World's Largest Travel Site
October 24, 2019
"Finding a single source of truth for design documents and artifacts is extremely hard because most tools operate in silos."
Aurobinda Pradhan Shashank DeshpandeIntroduction to Collaborative DesignOps using Cubyts
September 9, 2022
