Li-Yuan Chiou
Interaction Designer
Based in Seattle
Published researcher on Designer-AI Collaboration.
Former UI/UX Intern worked on AI product design at Logitech and ASUS.
Master of Interaction Design at the University of Washington.
2025
Context
Problem
USER INTERVIEWS
Design Principles
KEy functions
Customer Journey Map
Ideation
Prototyping
Solution
Reflection
Role
Product Designer
Developer
Skills
UIUX Design
Prototyping
Coding
Collaborators
Me
Myself
and I
Duration
14 Days
Context
Ever caught yourself oversharing with AI?
Major companies, government agencies, and millions of users have already paid the price for AI oversharing.
Problem
Users frequently overshare sensitive information with AI without realizing it.
In the flow of chatting with AI, sharing sensitive details feels natural and harmless.
Data Leaks
Personal details, work secrets, financial info slip into conversations
Trust Gap
High user trust in AI creates blind spots for data privacy
No Protection
No built-in privacy protection in popular AI tools
Missing Privacy Tools
No convenient way to de-identify sensitive information before sharing
USER INTERVIEWS
Convenience leads to unintentional privacy risks.
Whether it’s work notes, personal info, or even IDs, they only realize it might be risky after hitting enter.
Users want AI help that feels seamless and invisible. They value being fast, simple, and uninterrupted while staying “in flow.” At the same time, this desire for smooth interaction creates blind spots where oversharing occurs without awareness.
Design Principles
User insights guided us in defining four key design principles.
Instead of blocking users outright, small contextual cues can make them aware while maintaining trust and productivity.
Design Principles:
Protect user privacy while preserving their flow state.
Provide contextual nudges that educate rather than block user actions.
Offer flexible sensitivity controls that scale from novice to expert privacy needs.
Ensure all privacy detection happens locally with zero data transmission or storage.
KEy functions
Real-time Privacy Nudges for AI Chats
Based on the design principles, we came up with four key functions.
Real-time Detection
Instantly alerts you when sensitive data is detected as you type
Built-in Protection Rules
Automatically identifies multiple data types without configuration
Custom Rules
Create your own privacy rules without writing code
100% Local Processing
Your data never leaves your device. Complete privacy guaranteed.
Customer Journey Map
How Privacy Guard AI Should Transform User Experience
This journey map represents the design vision for how Privacy Guard AI should integrate into users' natural workflow.
•
AI platform homepage
•
Chat interface
•
Extension icon (subtle)
•
Opens AI chat platform
•
Thinks about question
•
Prepares to ask for help
•
Types detailed content
•
Shares sensitive information
•
Focuses on articulating the problem clearly
•
Prepares to click send button
•
Text input field
•
Real-time text analysis
•
Text input interface
•
Typing indicator/cursor
•
Send button
•
Notices privacy warning popup
•
Stops to read the alert
•
Evaluates the warning message
•
Privacy alert modal
•
Warning message text
•
Action buttons
•
Reviews privacy explanation
•
Chooses to modify content
•
Adjusts future sharing behavior
•
Decision options
•
Settings panel
•
Feedback system
Privacy Warning
Ready to Send
Seeking Help
Sharing Context
Making Choice
Actions
Touchpoints
Value Created
High Confidence
Mid Confidence
Low Confidence
•
Feels confident about AI safety
•
Has clear privacy expectations
•
Receives intelligent protection
•
Maintains productive flow
•
Gets just-in-time education
•
Feels empowered to make informed choices
•
Learns without disruption
•
Builds trust in protection system
•
Gains long-term privacy awareness
•
Feels secure in AI interactions
“I need ChatGPT to help me with this work problem. It's so much faster than figuring it out myself.”
“More context means better help, right? Let me add our internal strategy details too.”
“Perfect, this explanation should give me exactly what I need. Time to hit send.”
“Oh wow, I didn't realize those details could be risky to share.”
“I feel much more confident now that I understand what to share and what not to share.”
The temporary confidence dip during Privacy Warning stage is crucial. It represents the moment users gain true privacy awareness. The final high confidence level is more valuable than initial confidence because it's based on understanding, not ignorance.
Ideation & Concept Development
Exploring Notification Patterns
During the ideation phase, I explored multiple approaches to privacy notifications, balancing user awareness with workflow preservation.
A: Minimal popup with basic privacy warning (doesn’t have enough room for further actions)
B: Enhanced popup with actionable buttons and clear "sensitive data" labeling
C: Corner-positioned notification for less intrusive experience
D: Center-screen modal (too proactive, would heavily disrupt user flow)
Prototyped
Prototyped
Smart Detection Interface Design
Warning triangle with specific data type identification
Action Options:
Replace with placeholder text
Replace with fake data
Keep origin
Settings
Multi-Item: When multiple sensitive elements are found, users can review and act all at once
Settings & Control
Built-in Rules
Pre-configured: SSN, email addresses, phone numbers, IDs...etc.
Rule Cards: Visual representation of each privacy rule
Custom Rule Creation
Users can define their own sensitive patterns with:
Rule naming
Regular expression patterns
Custom replacement text
Test field for validation
Prototyping
Vibe-Coded interfaces to test the usability
Pattern B
The centered popup forces an immediate decision, completely breaking the user's writing flow. When users are in a creative mindset, this interruption can cause them to lose their train of thought entirely.
Pattern C (Decision)
The corner-positioned notification maintains peripheral awareness without demanding immediate attention.
Pattern B feels like the system is "taking control" away from the user. Pattern C feels like the system is "offering helpful information" , a crucial psychological difference that reduces user frustration and increases long-term adoption.
Solution
Real-time Detection
Get instant alerts the moment you're about to share sensitive information, before you hit send.
Built-in Protection Rules
Comes preloaded with common privacy rules for US and global identifiers—SSNs, phone numbers, credit cards, passports, and more.
Custom Rules for Any Data Type
Easily define your own detection patterns with regex, example data, and optional replacement text—no coding expertise required.
Quick Templates for Fast Setup
Start with ready-made templates for IDs, license plates, medical records, product serials, and other frequent formats.
Reflection
When AI Made Me Feel Unstoppable
It's Actually Live on Chrome Web Store!
Seeing real people download and use something I built feels like a dream. What started as me worrying about accidentally sharing work details with ChatGPT somehow turned into a little tool that might help others too.
What I Learned:
With AI helping me code, I could try out ideas as actual working pieces. When something felt clunky, I could tweak it right away while I still remembered exactly what bugged me about it.
Using my own creation taught me things I never anticipated. Living with the extension daily while building it showed me tiny moments of user frustration and delight that I probably would have missed otherwise. Like how grateful I felt when it quietly caught something risky, or how annoying it was when alerts popped up at the wrong moment.
AI became this amazing creative partner. I could focus on the feelings and interactions I wanted to create while AI helped with the technical stuff I was still learning. It felt like having a really patient coding buddy who never made me feel silly for not knowing something.
The best part has been reading reviews from friends who find Privacy Guard genuinely helpful! It makes me want to keep exploring what else might be possible when you combine thoughtful design with AI assistance. There's something magical about turning "wouldn't it be nice if..." into something real that people actually use.
Li-Yuan Chiou
All rights reserved
Li-Yuan Chiou
Interaction Designer
Based in Seattle
Published researcher on Designer-AI Collaboration.
Former UI/UX Intern worked on AI product design at Logitech and ASUS.
Master of Interaction Design at the University of Washington.
2025
Context
Problem
USER INTERVIEWS
Design Principles
KEy functions
Customer Journey Map
Ideation
Prototyping
Solution
Reflection
Role
Product Designer
Developer
Skills
UIUX Design
Prototyping
Coding
Collaborators
Me
Myself
and I
Duration
14 Days
Context
Ever caught yourself oversharing with AI?
Major companies, government agencies, and millions of users have already paid the price for AI oversharing.
Problem
Users frequently overshare sensitive information with AI without realizing it.
In the flow of chatting with AI, sharing sensitive details feels natural and harmless.
Data Leaks
Personal details, work secrets, financial info slip into conversations
Trust Gap
High user trust in AI creates blind spots for data privacy
No Protection
No built-in privacy protection in popular AI tools
Missing Privacy Tools
No convenient way to de-identify sensitive information before sharing
USER INTERVIEWS
Convenience leads to unintentional privacy risks.
In the flow of chatting with AI, sharing sensitive details feels natural and harmless.
Users want AI help that feels seamless and invisible. They value being fast, simple, and uninterrupted while staying “in flow.” At the same time, this desire for smooth interaction creates blind spots where oversharing occurs without awareness.
Design Principles
User insights guided us in defining four key design principles.
Instead of blocking users outright, small contextual cues can make them aware while maintaining trust and productivity.
Design Principles:
Protect user privacy while preserving their flow state.
Provide contextual nudges that educate rather than block user actions.
Offer flexible sensitivity controls that scale from novice to expert privacy needs.
Ensure all privacy detection happens locally with zero data transmission or storage.
KEy functions
Real-time Privacy Nudges for AI Chats
Based on the design principles, we came up with four key functions.
Real-time Detection
Instantly alerts you when sensitive data is detected as you type
Built-in Protection Rules
Automatically identifies multiple data types without configuration
Custom Rules
Create your own privacy rules without writing code
100% Local Processing
Your data never leaves your device. Complete privacy guaranteed.
Customer Journey Map
How Privacy Guard AI Should Transform User Experience
This journey map represents the design vision for how Privacy Guard AI should integrate into users' natural workflow.
•
AI platform homepage
•
Chat interface
•
Extension icon (subtle)
•
Opens AI chat platform
•
Thinks about question
•
Prepares to ask for help
•
Types detailed content
•
Shares sensitive information
•
Focuses on articulating the problem clearly
•
Prepares to click send button
•
Text input field
•
Real-time text analysis
•
Text input interface
•
Typing indicator/cursor
•
Send button
•
Notices privacy warning popup
•
Stops to read the alert
•
Evaluates the warning message
•
Privacy alert modal
•
Warning message text
•
Action buttons
•
Reviews privacy explanation
•
Chooses to modify content
•
Adjusts future sharing behavior
•
Decision options
•
Settings panel
•
Feedback system
Privacy Warning
Ready to Send
Seeking Help
Sharing Context
Making Choice
Actions
Touchpoints
Value Created
High Confidence
Mid Confidence
Low Confidence
•
Feels confident about AI safety
•
Has clear privacy expectations
•
Receives intelligent protection
•
Maintains productive flow
•
Gets just-in-time education
•
Feels empowered to make informed choices
•
Learns without disruption
•
Builds trust in protection system
•
Gains long-term privacy awareness
•
Feels secure in AI interactions
“I need ChatGPT to help me with this work problem. It's so much faster than figuring it out myself.”
“More context means better help, right? Let me add our internal strategy details too.”
“Perfect, this explanation should give me exactly what I need. Time to hit send.”
“Oh wow, I didn't realize those details could be risky to share.”
“I feel much more confident now that I understand what to share and what not to share.”
The temporary confidence dip during Privacy Warning stage is crucial. It represents the moment users gain true privacy awareness. The final high confidence level is more valuable than initial confidence because it's based on understanding, not ignorance.
Ideation & Concept Development
Exploring Notification Patterns
During the ideation phase, I explored multiple approaches to privacy notifications, balancing user awareness with workflow preservation.
A: Minimal popup with basic privacy warning (doesn’t have enough room for further actions)
B: Enhanced popup with actionable buttons and clear "sensitive data" labeling
C: Corner-positioned notification for less intrusive experience
D: Center-screen modal (too proactive, would heavily disrupt user flow)
Prototyped
Prototyped
Smart Detection Interface Design
Warning triangle with specific data type identification
Action Options:
Replace with placeholder text
Replace with fake data
Keep origin
Settings
Multi-Item: When multiple sensitive elements are found, users can review and act all at once
Settings & Control
Built-in Rules
Pre-configured: SSN, email addresses, phone numbers, IDs...etc.
Rule Cards: Visual representation of each privacy rule
Custom Rule Creation
Users can define their own sensitive patterns with:
Rule naming
Regular expression patterns
Custom replacement text
Test field for validation
Prototyping
Vibe-Coded interfaces to test the usability
Pattern B
The centered popup forces an immediate decision, completely breaking the user's writing flow. When users are in a creative mindset, this interruption can cause them to lose their train of thought entirely.
Pattern C (Decision)
The corner-positioned notification maintains peripheral awareness without demanding immediate attention.
Pattern B feels like the system is "taking control" away from the user. Pattern C feels like the system is "offering helpful information" , a crucial psychological difference that reduces user frustration and increases long-term adoption.
Solution
Real-time Detection
Get instant alerts the moment you're about to share sensitive information, before you hit send.
Built-in Protection Rules
Comes preloaded with common privacy rules for US and global identifiers—SSNs, phone numbers, credit cards, passports, and more.
Custom Rules for Any Data Type
Easily define your own detection patterns with regex, example data, and optional replacement text—no coding expertise required.
Quick Templates for Fast Setup
Start with ready-made templates for IDs, license plates, medical records, product serials, and other frequent formats.
Seeing real people download and use something I built feels like a dream. What started as me worrying about accidentally sharing work details with ChatGPT somehow turned into a little tool that might help others too.
What I Learned:
With AI helping me code, I could try out ideas as actual working pieces. When something felt clunky, I could tweak it right away while I still remembered exactly what bugged me about it.
Using my own creation taught me things I never anticipated. Living with the extension daily while building it showed me tiny moments of user frustration and delight that I probably would have missed otherwise. Like how grateful I felt when it quietly caught something risky, or how annoying it was when alerts popped up at the wrong moment.
AI became this amazing creative partner. I could focus on the feelings and interactions I wanted to create while AI helped with the technical stuff I was still learning. It felt like having a really patient coding buddy who never made me feel silly for not knowing something.
The best part has been reading reviews from friends who find Privacy Guard genuinely helpful! It makes me want to keep exploring what else might be possible when you combine thoughtful design with AI assistance. There's something magical about turning "wouldn't it be nice if..." into something real that people actually use.
Li-Yuan Chiou
All rights reserved
Li-Yuan Chiou
Interaction Designer
Based in Seattle
Published researcher on Designer-AI Collaboration.
Former UI/UX Intern worked on AI product design at Logitech and ASUS.
Master of Interaction Design at the University of Washington.
2025
Context
Problem
USER INTERVIEWS
Design Principles
KEy functions
Customer Journey Map
Ideation
Prototyping
Solution
Reflection
Role
Product Designer
Developer
Skills
UIUX Design
Prototyping
Coding
Collaborators
Me
Myself
and I
Duration
14 Days
Context
Ever caught yourself oversharing with AI?
Major companies, government agencies, and millions of users have already paid the price for AI oversharing.
Problem
Users frequently overshare sensitive information with AI without realizing it.
In the flow of chatting with AI, sharing sensitive details feels natural and harmless.
Data Leaks
Personal details, work secrets, financial info slip into conversations
Trust Gap
High user trust in AI creates blind spots for data privacy
No Protection
No built-in privacy protection in popular AI tools
Missing Privacy Tools
No convenient way to de-identify sensitive information before sharing
USER INTERVIEWS
Convenience leads to unintentional privacy risks.
In the flow of chatting with AI, sharing sensitive details feels natural and harmless.
Users want AI help that feels seamless and invisible. They value being fast, simple, and uninterrupted while staying “in flow.” At the same time, this desire for smooth interaction creates blind spots where oversharing occurs without awareness.
Design Principles
User insights guided us in defining four key design principles.
Instead of blocking users outright, small contextual cues can make them aware while maintaining trust and productivity.
Design Principles:
Protect user privacy while preserving their flow state.
Provide contextual nudges that educate rather than block user actions.
Offer flexible sensitivity controls that scale from novice to expert privacy needs.
Ensure all privacy detection happens locally with zero data transmission or storage.
KEy functions
Real-time Privacy Nudges for AI Chats
Based on the design principles, we came up with four key functions.
Real-time Detection
Instantly alerts you when sensitive data is detected as you type
Built-in Protection Rules
Automatically identifies multiple data types without configuration
Custom Rules
Create your own privacy rules without writing code
100% Local Processing
Your data never leaves your device. Complete privacy guaranteed.
Customer Journey Map
How Privacy Guard AI Should Transform User Experience
This journey map represents the design vision for how Privacy Guard AI should integrate into users' natural workflow.
•
AI platform homepage
•
Chat interface
•
Extension icon (subtle)
•
Opens AI chat platform
•
Thinks about question
•
Prepares to ask for help
•
Types detailed content
•
Shares sensitive information
•
Focuses on articulating the problem clearly
•
Prepares to click send button
•
Text input field
•
Real-time text analysis
•
Text input interface
•
Typing indicator/cursor
•
Send button
•
Notices privacy warning popup
•
Stops to read the alert
•
Evaluates the warning message
•
Privacy alert modal
•
Warning message text
•
Action buttons
•
Reviews privacy explanation
•
Chooses to modify content
•
Adjusts future sharing behavior
•
Decision options
•
Settings panel
•
Feedback system
Privacy Warning
Ready to Send
Seeking Help
Sharing Context
Making Choice
Actions
Touchpoints
Value Created
High Confidence
Mid Confidence
Low Confidence
•
Feels confident about AI safety
•
Has clear privacy expectations
•
Receives intelligent protection
•
Maintains productive flow
•
Gets just-in-time education
•
Feels empowered to make informed choices
•
Learns without disruption
•
Builds trust in protection system
•
Gains long-term privacy awareness
•
Feels secure in AI interactions
“I need ChatGPT to help me with this work problem. It's so much faster than figuring it out myself.”
“More context means better help, right? Let me add our internal strategy details too.”
“Perfect, this explanation should give me exactly what I need. Time to hit send.”
“Oh wow, I didn't realize those details could be risky to share.”
“I feel much more confident now that I understand what to share and what not to share.”
The temporary confidence dip during Privacy Warning stage is crucial. It represents the moment users gain true privacy awareness. The final high confidence level is more valuable than initial confidence because it's based on understanding, not ignorance.
Ideation & Concept Development
Exploring Notification Patterns
During the ideation phase, I explored multiple approaches to privacy notifications, balancing user awareness with workflow preservation.
A: Minimal popup with basic privacy warning (doesn’t have enough room for further actions)
B: Enhanced popup with actionable buttons and clear "sensitive data" labeling
C: Corner-positioned notification for less intrusive experience
D: Center-screen modal (too proactive, would heavily disrupt user flow)
Prototyped
Prototyped
Smart Detection Interface Design
Warning triangle with specific data type identification
Action Options:
Replace with placeholder text
Replace with fake data
Keep origin
Settings
Multi-Item: When multiple sensitive elements are found, users can review and act all at once
Settings & Control
Built-in Rules
Pre-configured: SSN, email addresses, phone numbers, IDs...etc.
Rule Cards: Visual representation of each privacy rule
Custom Rule Creation
Users can define their own sensitive patterns with:
Rule naming
Regular expression patterns
Custom replacement text
Test field for validation
Prototyping
Vibe-Coded interfaces to test the usability
Pattern B
The centered popup forces an immediate decision, completely breaking the user's writing flow. When users are in a creative mindset, this interruption can cause them to lose their train of thought entirely.
Pattern C (Decision)
The corner-positioned notification maintains peripheral awareness without demanding immediate attention.
Pattern B feels like the system is "taking control" away from the user. Pattern C feels like the system is "offering helpful information" , a crucial psychological difference that reduces user frustration and increases long-term adoption.
Solution
Real-time Detection
Get instant alerts the moment you're about to share sensitive information, before you hit send.
Built-in Protection Rules
Comes preloaded with common privacy rules for US and global identifiers—SSNs, phone numbers, credit cards, passports, and more.
Custom Rules for Any Data Type
Easily define your own detection patterns with regex, example data, and optional replacement text—no coding expertise required.
Quick Templates for Fast Setup
Start with ready-made templates for IDs, license plates, medical records, product serials, and other frequent formats.
Seeing real people download and use something I built feels like a dream. What started as me worrying about accidentally sharing work details with ChatGPT somehow turned into a little tool that might help others too.
What I Learned:
With AI helping me code, I could try out ideas as actual working pieces. When something felt clunky, I could tweak it right away while I still remembered exactly what bugged me about it.
Using my own creation taught me things I never anticipated. Living with the extension daily while building it showed me tiny moments of user frustration and delight that I probably would have missed otherwise. Like how grateful I felt when it quietly caught something risky, or how annoying it was when alerts popped up at the wrong moment.
AI became this amazing creative partner. I could focus on the feelings and interactions I wanted to create while AI helped with the technical stuff I was still learning. It felt like having a really patient coding buddy who never made me feel silly for not knowing something.
The best part has been reading reviews from friends who find Privacy Guard genuinely helpful! It makes me want to keep exploring what else might be possible when you combine thoughtful design with AI assistance. There's something magical about turning "wouldn't it be nice if..." into something real that people actually use.
Li-Yuan Chiou
All rights reserved
Li-Yuan Chiou
Interaction Designer
Based in Seattle
2025
Published researcher on Designer-AI Collaboration.
Former UI/UX Intern worked on AI product design at Logitech and ASUS.
Master of Interaction Design at the University of Washington.
Role
Product Designer
Developer
Skills
UIUX Design
Prototyping
Coding
Collaborators
Me
Myself
and I
Duration
14 Days
Context
Ever caught yourself oversharing with AI?
Major companies, government agencies, and millions of users have already paid the price for AI oversharing.
Problem
Users frequently overshare sensitive information with AI without realizing it.
In the flow of chatting with AI, sharing sensitive details feels natural and harmless.
Data Leaks
Personal details, work secrets, financial info slip into conversations
No Protection
No built-in privacy protection in popular AI tools
Trust Gap
High user trust in AI creates blind spots for data privacy
Missing Privacy Tools
No convenient way to de-identify sensitive information before sharing
USER INTERVIEWS
Convenience leads to unintentional privacy risks.
In the flow of chatting with AI, sharing sensitive details feels natural and harmless.
Users want AI help that feels seamless and invisible. They value being fast, simple, and uninterrupted while staying “in flow.” At the same time, this desire for smooth interaction creates blind spots where oversharing occurs without awareness.
Design Principles
User insights guided us in defining four key design principles.
Instead of blocking users outright, small contextual cues can make them aware while maintaining trust and productivity.
Design Principles:
Protect user privacy while preserving their flow state.
Provide contextual nudges that educate rather than block user actions.
Offer flexible sensitivity controls that scale from novice to expert privacy needs.
Ensure all privacy detection happens locally with zero data transmission or storage.
Design Principles:
Protect user privacy while preserving their flow state.
Provide contextual nudges that educate rather than block user actions.
Offer flexible sensitivity controls that scale from novice to expert privacy needs.
Ensure all privacy detection happens locally with zero data transmission or storage.
KEy functions
Real-time Privacy Nudges for AI Chats
Based on the design principles, we came up with four key functions.
Real-time Detection
Instantly alerts you when sensitive data is detected as you type
Custom Rules
Create your own privacy rules without writing code
Built-in Protection Rules
Automatically identifies multiple data types without configuration
100% Local Processing
Your data never leaves your device. Complete privacy guaranteed.
Solution
Real-time Detection
Get instant alerts the moment you're about to share sensitive information, before you hit send.
Built-in Protection Rules
Comes preloaded with common privacy rules for US and global identifiers—SSNs, phone numbers, credit cards, passports, and more.
Custom Rules for Any Data Type
Easily define your own detection patterns with regex, example data, and optional replacement text—no coding expertise required.
Quick Templates for Fast Setup
Start with ready-made templates for IDs, license plates, medical records, product serials, and other frequent formats.