MSN, recently known as Microsoft Start, is a news and content platform that provides users with news articles, entertainment, lifestyle content, and more.

organization

Microsoft AI  

(Windows, Bing, Copilot, MSN)

role

Design, Development,

Research

collaborators

Developers, Project managers,

UX researcher

timeline

2 months

MSN, recently known as Microsoft Start, is a news and content platform that provides users with news articles, entertainment, lifestyle content, and more.

organization

Microsoft AI  

(Windows, Bing, Copilot, MSN)

role

Design, Development,

Research

collaborators

Developers, Project managers,

UX researcher

timeline

2 months

MSN, recently known as Microsoft Start, is a news and content platform that provides users with news articles, entertainment, lifestyle content, and more.

organization

Microsoft AI  

(Windows, Bing, Copilot, MSN)

role

Design, Development,

Research

collaborators

Developers, Project managers,

UX researcher

timeline

3 weeks

overview

Building Trust and Engagement in an AI-Powered Commenting Experience

I redesigned with product and engineering to redesign the commenting experience on MSN, aiming to boost participation and build trust around AI-generated content (AIGC). Our goal was to make AIGC feel more reliable and engaging by rethinking how information, polls, and discussions surfaced, through clearer signals, more visible activity, and lower-friction entry points. This included new features like contexual AI generated poll questions, AI generated summaries and quick comments.

The challenge

Users are reading news, but skipping the conversation

The challenge was to create a commenting experience that felt natural and worth joining. Instead of static reading, I wanted to encourage dynamic discussion by rethinking information hierarchy, surfacing polls and discussions more intuitively, and reducing friction to comment through features like quick comments, pop-up cards, and better visual cues.

The opportunity was to redesign the discussion and pop-up card experience to feel more interactive, credible, and participatory, especially in a space where users may feel uncertain about AI-generated content.

Pain Points:

Passive consumption of content without engaging with the comment panel

Skepticism toward AI-generated content and insights

Low participation in user discussions

There is currently no seamless experience for renting electric vehicles via an app.

solution

The outcome

I led the end-to-end re-design across four core initiatives:

As the UX designer, I led the end-to-end re-design across four core initiatives:

Discussion Page and Pop-up Card Enhancements: Introducing a clearer hierarchy with AI insights, poll data, and discussion stats to drive transparency and encourage exploration.

Discussion Page and Pop-up Card Enhancements:
Introducing a clearer hierarchy with AI insights, poll data, and discussion stats to drive transparency and encourage exploration.

AI-Generated Comment Suggestions:
Integrated GPT-powered comment prompts aligned with user poll answer to reduce friction on commenting. Built safety mechanisms for human review to ensure trustworthy, bias-mitigated suggestions.

Design and Research Study on AI Labeling:
Designed and conducted a study on label placement and wording to improve user understanding and trust in AI-generated content. Insights directly informed key design decisions.

Information Density & Discoverability:
Balanced readability and depth by truncating and expanding content with contextual interactions.

to microsoft notifications case study

solution

The outcome

I led the end-to-end re-design across four core initiatives:

Discussion Page and Pop-up Card Enhancements:
Introducing a clearer hierarchy with AI insights, poll data, and discussion stats to drive transparency and encourage exploration.

AI-Generated Comment Suggestions:
Integrated GPT-powered comment prompts aligned with user poll answer to reduce friction on commenting. Built safety mechanisms for human review to ensure trustworthy, bias-mitigated suggestions.

Design and Research Study on AI Labeling:
Designed and conducted a study on label placement and wording to improve user understanding and trust in AI-generated content. Insights directly informed key design decisions.

Information Density & Discoverability:
Balanced readability and depth by truncating and expanding content with contextual interactions.