Designing Trust into AI-Assisted Job Search.
Exploring how transparency, explainability, and user control can help job seekers better understand and trust AI-powered recommendations.
02 / The Problem
The trust gap behind AI recommendations
AI-powered job search tools can make the application process faster, but their recommendations often lack transparency. Job seekers may see match scores, suggested roles, or AI-generated advice without understanding how those outputs were created—or what assumptions the system made.
We explored how greater transparency, explainability, and user control could help job seekers better understand AI recommendations and build more appropriate trust in the system.
How might we make AI recommendations easier to understand, question, and trust?
03 / Our Approach
- 01
Analyze
Compared AI experiences across LinkedIn, Glassdoor, Indeed, and Jobright to identify transparency and usability gaps.
- 02
Research
Conducted task-based research with 5 participants, evaluating AI experiences across accuracy, fairness, safety, explainability, and accountability.
- 03
Design & Test
Translated research findings into design recommendations, built an interactive Figma Make prototype, and conducted a second round of testing focused on explanation clarity and trust.
04 / Explore the Project
Dive deeper into the research
Explore our full research, design recommendations, and interactive prototype.