EvueMe AI Ethical Principles Policy
1. Purpose and Scope
This policy sets out the ethical design, deployment, and governance principles for the artificial intelligence systems used by EvueMe AI. It is intended to:
- Build trust among clients, users, and regulatory stakeholders
- Ensure that AI-led hiring and assessments are fair, transparent, secure, and scientifically valid
- Embed global best practices into EvueMe’s core AI lifecycle — from data sourcing to candidate evaluation
This policy applies to all EvueMe AI systems, employees, contractors, data processors, and client implementations globally.
2. Policy Oversight and Governance
Oversight of AI ethics at EvueMe AI is led by the AI Governance Committee, chaired by the Global Compliance Director, with cross-functional members from Product, Engineering, Legal, and Customer Success. The committee ensures that our ethical principles are operationalized throughout the AI lifecycle.
Responsibilities include:
- Quarterly internal audits of AI model fairness, accuracy, and risk metrics
- Documentation of all changes to model architecture, scoring logic, or competency mappings
- Client-facing model disclosures, available under NDA when requested
- Periodic benchmarking against evolving global best practices in AI ethics
While we do not currently conduct third-party audits, we are committed to evolving our governance model as regulatory norms and client expectations develop.
3. Core Ethical Principles
3.1 Scientific and Evidence-Based Assessment
All AI assessments are rooted in behavioral science, neurolinguistics, and cognitive psychology. Each evaluated competency (e.g., Decision Making, Resilience) is decomposed into observable and measurable behavioral attributes. These are derived from:
- Video (facial cues, gaze, micro-expressions)
- Audio (tonality, pacing, prosody)
- Text (semantic clarity, vocabulary, reasoning)
Each signal is evaluated against a standardized, research-backed rubric to ensure objectivity.
3.2 Fairness, Inclusion, and Bias Mitigation
EvueMe AI enforces a Bias Management Protocol which includes:
- Diverse training datasets to account for gender, ethnicity, language, and cultural variance
- Bias detection metrics (e.g., disparate impact ratio, subgroup fairness checks)
- Explainable AI modules (XAI) that surface reasoning behind outputs
- Human-in-the-loop overrides in cases of uncertainty or low confidence scores
All fairness results are documented, versioned, and available to enterprise clients under NDAs.
3.3 Privacy and Consent by Design
We implement Privacy-by-Design across our AI stack:
- Candidate data is never used for model training without explicit, opt-in consent
- Data minimization ensures we only collect what is needed to evaluate competencies
- Our platform adheres to GDPR, CCPA, India’s IT Rules, and other applicable frameworks
- All video/audio/text is encrypted in transit and at rest, with zero third-party sales or reuse
A Data Protection Impact Assessment (DPIA) is conducted before any new assessment modality is launched.
3.4 Transparency and Explainability
We uphold two-way explainability:
- Clients receive structured scoring logic with weighted competency breakdowns
- Candidates receive clear disclosures on what is being measured and how their data is used
- Explainability tools are built into dashboards for internal TA and InfoSec audits
3.5 Human Judgment and Accountability
EvueMe AI does not autonomously decide hiring outcomes. Instead:
- Final decisions always rest with human recruiters
- AI insights serve as supporting evidence, not sole selectors
- Edge cases, ambiguity, or candidate challenges can trigger a manual re-review
This ensures retention of human accountability, as mandated in OECD and EU frameworks.
3.6 Cultural and Linguistic Adaptability
Recognizing cross-cultural behavioral variations, EvueMe AI is built with:
- Localized language models and regional training data
- Culture-aware interpretations of gestures, expressions, and speech patterns
- Role-specific weighting models that adapt scoring to industry and geography
This ensures candidates are not penalized for expressive or cultural norms.
3.7 Continuous Validation and Feedback Loops
Our AI systems are continuously improved through post-hiring feedback analysis:
- Correlating AI assessments with actual hiring outcomes
- Adjusting weightages for competencies based on real-world success
- Client-led tuning based on performance benchmarking
This guarantees ongoing model relevance, performance, and integrity.
3.8 Auditability and Risk Management
We recognize the importance of auditability and model traceability in building enterprise trust. While we do not currently maintain a full AI audit trail, we are evolving our internal processes to ensure:
- Version control for major model updates and competency frameworks
- Internal documentation of assessment logic and data sources used
- Role-based access to sensitive candidate insights
- Client-side logs (e.g., admin access, evaluation downloads) retained for compliance
As we scale, our roadmap includes building a structured audit log system to support enterprise compliance, client audits, and regulatory alignment.
4. Candidate Dignity and Ethical Experience
- Candidates are informed of AI usage before assessments begin
- No discriminatory scoring based on appearance, accent, disability, or socio-economic markers
- Candidates are never judged for nervousness, silence, or unfamiliar phrasing — unless contextually relevant to the role
Our objective is to respect individuality while recognizing behavioral indicators of job-fit.
5. Alignment to Global AI Ethics Frameworks
EvueMe AI adheres to principles from the following:
- OECD AI Principles
- EU AI Act Risk Framework
- Singapore AI Model Governance Framework
- World Economic Forum HR AI Toolkit
- IEEE Ethically Aligned Design
We also monitor new developments such as the AI Bill of Rights (USA) and adapt compliance accordingly.
6. Policy Review and Compliance Lifecycle
- Review Frequency: Annual minimum, with interim updates for regulatory shifts
- Owner: Global Compliance Director
- Reviewers: AI Governance Committee, Legal Counsel, External Advisors (where applicable)
- Client Access: Upon NDA for audit/review purposes
7. Contact and Escalation
For AI ethics queries, concerns, or complaints, please contact:
EvueMe Technologies Private Limited
1st Floor, Orchid Business Park, Sector 48, Sohna Road, Gurugram
Email: care@evueme.com
Call: +91-9341 555 666
All grievances are acknowledged within 7 business days and closed within regulatory timelines.
Version History
Version | Effective Date | Summary of Changes |
|---|---|---|
v1.0 | Jan 1, 2021 | Initial ethical principles issued for internal guidance |
v1.1 | Jul 12, 2022 | Formalized candidate consent policy; updated fairness metrics |
v1.2 | Oct 10, 2023 | Formalized candidate consent policy; updated fairness metrics |
v1.3 | Mar 6, 2024 | Strengthened oversight, risk scoring, and culture sensitivity layers |
v2.0 | Jun 4, 2025 | Full reissue to align with compliance governance and global AI norms |
