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Google x BrainStation

A 24hr Hackathon

Overview

Hackathon Details

I collaborated with a team of three data scientists and two software engineers to develop a solution for an AI-related problem space presented by Google to BrainStation diploma candidates. Out of seven teams, our team came in second place.

My Role

UX Researcher, UI Designer

Timeline

24 hours

Tools

Figma

Type

Android App | Academic

Introducing New AI-related Technologies While Maintaining User Trust

The Problem

Lack of transparency and concerns about privacy and data security are two of the leading causes of American mistrust in AI technologies. While incorporating AI into Google products can enhance user experiences, the misconceptions about this technology can alienate users, decreasing return rates.

78% of Americans

believe generative AI can be used for malicious intent.

53% of women

in the US do not trust AI technologies.

Digging Deeper

Narrowing the Scope

After our team discovered that adult women are the demographic least likely to trust AI, we decided to design our solution for the Google Fit app, as further researched revealed that the majority of users are adult women.

How might we educate American women about new Google AI-related features in order to establish user trust while avoiding misunderstandings about AI when using the Google Fit app?

Designing for User Needs

The Solution

Our team incorporated multiple touch points throughout the Google Fit app to help users progressively learn more about Bard AI technologies, without obstructing the overall user experience. Our solution builds trust with user by providing them with proactive and transparent communication, while also giving them the freedom to tap into, or dismiss, the information.

Major Features

Information Modal

The modal informs the user how Bard AI can enhance their experience while using the Google Fit app. This modal also gives the user the choice to allow Bard AI to track their data, postpone usage of Bard AI, or learn more about how Bard AI technology works.

Design Development

Mapping Out an Efficient Solution
The task flow diagram proved to be a beneficial tool across the team. The diagram allowed us to visualize the user journey from the home screen to the Bard AI information hub, and iterate our design solution to achieve greater efficiency while still meeting the user needs.

Google Fit Home Screen

Bard AI Permission Modal

User taps "yes"

Google Fit

Home Screen

User taps "Learn More" on health recomendation

Bard AI for Google Fit Screen

User updates data preferences and taps "Learn More"

Google AI Information Page

Visual Design
Due to the time constraints, I jumped straight into hi-fi wire-framing using the Google's Material 3 Design Kit.

Looking Back

Key Learnings

01. Remember the HMW

Scope Creep

The biggest challenge our team faced was scope creep. To keep ourselves on track, we repeatedly revisited the How Might We question, reminded ourselves of the time constraint, and referred back to our persona to make sure our solution aligned with the target user’s needs.

02. Communication

Cross-Team Collaboration

As the only UX designer on the team, I learned to advocate for our user persona and to stay firm in my research and design process. To maintain open channels of communication for feedback and transparency, I also quickly learned to regularly invite team members to view my work. I found that this then encouraged other members to include me in their process, creating an increasingly collaborative environment.