Responsible AI
Developed design principles, features, and processes to create safer and more responsible AI tools.
Now a part of the People + AI Guidebook
A Responsible AI toolkit for all
AI models have flaws: bias, stereotypes, hallucinations, misuse. Given this how do we embed responsibility into the design of the product experience?
With the astronomical adoption of GenAI for productivity and personal use, there is an urgent need for product makers to understanding and combat the risks of GenAI, namely bias, harm, and falsities.
In partnership with Google Research and Deepmind, I developed a clearer definition responsibility risk and user needs alongside actionable UX guidance and new design patterns for teams across Google.
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Principles
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Patterns
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Features
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Workshops
Principles
Design guidance and user-validated patterns for more responsible AI products across 6 essential areas.
Patterns
New interaction patterns that ensure clarity and prime users to contextualize outputs.
Features
Essential features for precise inputs, clear feedback, and user control to correct biased outputs.
Workshops
Processes and workshops to support product teams in auditing and improving their own AI experiences.
My role
I lead the research, concepting, strategic frameworks, and workshop structure, supporting a team of junior designers and senior strategists while forming a multi-year partnership with the Research organization at Google.
Team + timeline
Design lead (me)
Senior strategist
Jr. UX designer
Project manager
3 months
Activities
Research
Expert interviews
Landscape audit
Stakeholder interviews
Generative IDI’s
Diary studies
Audience definition + recruiting
Product strategy
Insights & synthesis
Journey mapping
Future scenarios
Ideation workshop
Opportunity definition
Strategic frameworks
Workshop development
Toolkit design
Product Design
Concept development
User flows
New feature prototyping
Design principles
UX pattern design
Development
Conversation design
Prompt engineering
Confidential work.
Details are available on request