APPLAI| AI求职助手
A Transparent Hiring Platform that Holds Companies Accountable and Exposes Bad Apples
2025.9-12 HCI Studio
A fair and transparent hiring assistant that helps applicants decode AI-driven evaluations and uncover bad apples through clearer signals, documentation, and guidance.
Job seekers often face opaque AI hiring systems. AppIAI brings clarity by revealing how algorithms evaluate applications and by guiding users toward trustworthy opportunities.
Product Pitch
12/05/2025Cornell University CIS Ithaca,NY
User Research
Literature Review
We examined three recurring challenges in AI-mediated hiring: reliance on voluntary employer compliance, limited transparency for applicants, and persistent enforcement gaps in regulatory oversight. We discovered that existing approaches largely prioritize employer needs, leaving applicants with limited visibility into hiring decisions, little avenues for recourse, and minimal voice in the process.
Stakeholder Interview
We conducted nine semi-structured interviews with job seekers (n=2), hiring professionals (n=4), and industry experts (n=3). All participants provided informed consent prior to participation, and identities are anonymized in reporting. Data collection used synchronous video interviews (45-60 minutes) and asynchronous written questionnaires with follow-up clarifications. Sessions through detailed note-taking.
Low-Fi prototype
We conducted a prototype evaluation with 3 job-seeking students actively applying for internships or full-time roles, along with 3 studio classmates who provided peer critique. Participants completed task-based walkthroughs using a paper prototype and a think-aloud protocol.
Expert Consultation
We consulted with two subject matter experts:
- An AI law professor specializing in automated decision-making and employment regulation
- An ILR professor with expertise in hiring practices and labor dynamics
User
Testing
We conducted a 45-minute moderated usability test using a high-fidelity Figma prototype. Participants completed scenario-based tasks aligned with key stages of the hiring journey, including document review, application tracking, company evaluation, and access to support features. Sessions followed a think-aloud protocol, with one moderator and one observer. The notes were later clustered and analyzed through affinity diagram.
Participants (n=6) were all active job seekers, including five international students and one U.S.-based student, selected to reflect users most affected by AI-mediated hiring. All participants were first-time users and received minimal onboarding.
AI
UI Audit
To evaluate the usability, accessibility, and visual consistency, we conducted a structured UI audit supported by ChatGPT as an expert-review aid. The system was prompted to evaluate the main user flows using established frameworks, including Nielsen’s usability heuristics, Material Design 3 guidelines, WCAG 2.2 accessibility standards, and consistency with the ApplAI brand system.
The UI audit shows the design is conceptually strong but needs targeted refinements.