Ethical AI: How We Ensure Bias-Free Hiring at Daily Liv India

Our Ethical AI Principle

Skills‑first matching
The AI matches candidates to roles using job‑related data such as skills, assessments, and experience. It does not use personal or demographic traits.

Transparent logic
For each recommendation, recruiters see why a profile ranks well, for example skills match, test scores, or experience. This keeps decisions clear and open to review.

Human in the loop
AI suggests and humans decide. Recruiters check AI shortlists, change them when needed, and share feedback to improve fairness over time.

Tackling the “Black Box” Problem

Explainable scoring
Instead of one hidden score, hiring teams see which factors drive each recommendation, such as communication tests, domain quizzes, or project history.

Documented models and data
Teams record data sources, cleaning steps, and evaluation methods. This allows stakeholders to audit how the AI works and where its limits are.​

Regular bias checks
Teams track selection rates and performance across groups. When they see unfair patterns, they fix them early.​

How We Screen Without Bias

Blind screening by design
The system hides non‑essential fields like name, photo, and gender during AI screening. As a result, the focus stays on competence.

Structured evaluations
Standardised assessments and shared question sets apply the same criteria to every candidate. This leaves less room for subjective “gut feeling.”

Diversity‑aware analytics
Funnel data shows if any group drops out more at a certain stage. Then, teams review rules, job ads, or process steps and adjust them if needed.

Diversity by Default, Not an Add‑On

Inclusive job content
AI‑based text checks remove biased or exclusionary words from job descriptions. This helps more diverse talent feel welcome to apply.

Fair, consistent shortlisting
Every applicant follows the same rules and standards. This supports diversity and keeps hiring aligned with fair‑practice norms.​

Continuous improvement loop
Feedback from recruiters, candidates, and audits feeds into regular model updates. Over time, the system becomes more fair instead of staying fixed.​

What This Means for Candidates and Employers

For candidates
The process rates you on what you can do, not who you are or where you come from. This opens more paths for students and early‑career talent across India.

For employers
You gain wider, more diverse, and more merit‑based talent pipelines. These pipelines are backed by AI that is explainable and auditable, not a black box.

For everyone
Ethical, transparent AI builds trust in hiring. It also supports Daily Liv India’s mission to make quality employment more accessible and inclusive.

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