Ethical AI Policy

Last Updated: 16 August 2025


Responsible Development Framework

This document outlines our approach to building responsible AI for hiring. As we develop our conversation-based interview platform, we're committed to transparency, fairness, and compliance - while maintaining the agility needed for rapid innovation.


1. What We're Building

Core Purpose: AI-assisted interview system that helps evaluate candidates through structured conversations rather than algorithmic CV screening.

Current Focus:

  • Real-time interview assistance for hiring managers

  • Competency-based assessment tied to job requirements

  • Transparent scoring with clear rationale

  • Human-in-the-loop decision making

What We're NOT Doing:

  • Automated candidate rejection without human review

  • Black-box algorithms that can't explain decisions

  • Analysis of protected characteristics or demographic data

  • Replacing human judgment in hiring decisions


2. Technical Transparency

What We Can Explain:

  • Our interview questions are standardized and job-relevant

  • Scoring is based on demonstrated competencies during conversation

  • Every assessment includes specific examples from the interview

  • Hiring managers can see exactly why we flagged strengths or concerns

Current Documentation:

  • Interview protocols for each role type

  • Scoring methodology based on response quality

  • Clear audit trail from candidate answers to recommendations

Ongoing Development:

  • We're continuously improving our ability to explain AI recommendations

  • Building more detailed technical documentation as we scale

  • Working toward full transparency in our decision-making process


3. Bias Prevention Approach

Design Philosophy: Conversation-based evaluation is inherently less biased than CV screening because candidates demonstrate qualifications directly rather than being filtered by algorithms analyzing resumes.

Current Practices:

  • Standardized questions eliminate subjective interviewer bias

  • Focus exclusively on job-relevant competencies

  • Every candidate gets the same opportunity to demonstrate skills

  • Human oversight required for all hiring recommendations

Monitoring & Improvement:

  • We track hiring outcomes across different candidate populations

  • Regular review of our scoring methodology for potential bias

  • Continuous refinement based on feedback and results

  • Commitment to third-party bias testing as we mature


4. Data Handling

Privacy Principles:

  • We only collect data necessary for job evaluation

  • Interview recordings are encrypted and securely stored

  • Client data is never used to train our general AI models

  • We comply with applicable data protection regulations

Data Rights:

  • Candidates can access their interview recordings and assessments

  • We provide clear explanations of how we evaluated their responses

  • Data deletion available upon request

  • Transparent communication about our data practices

Current Limitations: As an early-stage company, our data governance is evolving. We're building robust systems while maintaining operational flexibility.


5. AI Decision Process

How It Works:

  1. AI analyzes candidate responses during structured interviews

  2. System generates competency scores with specific evidence

  3. Human interviewer reviews AI recommendations

  4. Final hiring decisions always require human approval

What We Provide:

  • Clear scoring breakdown for each competency area

  • Specific examples from the interview supporting our assessment

  • Recommendations (not decisions) for hiring managers

  • Confidence levels indicating certainty of our analysis

Human Oversight:

  • Hiring managers can override any AI recommendation

  • All decisions require human review and approval

  • Appeals process for candidates who want to challenge assessments

  • Escalation procedures for edge cases or concerns


6. Third-Party Technologies

Current Stack: We use industry-standard technologies for:

  • Speech recognition and transcription

  • Natural language processing

  • Data storage and security

  • System hosting and compliance

Vendor Management:

  • We evaluate providers for security and compliance capabilities

  • Contractual requirements for data protection and privacy

  • Regular assessment of third-party performance

  • Migration plans if vendor relationships change


7. Compliance Commitment

Regulatory Alignment:

  • We monitor emerging regulations around AI in hiring

  • Design decisions prioritize compliance with employment law

  • Proactive approach to meeting transparency requirements

  • Regular consultation with legal experts as we grow

Industry Standards:

  • Following best practices for AI ethics and fairness

  • Participating in industry discussions around responsible AI

  • Learning from other companies' compliance approaches

  • Building relationships with compliance and legal experts


8. Accountability & Improvement

What We Track:

  • System performance and accuracy metrics

  • Candidate feedback and satisfaction scores

  • Hiring outcomes and quality measures

  • Potential bias indicators across different populations

How We Improve:

  • Regular review of our processes and outcomes

  • Incorporation of feedback from candidates and clients

  • Continuous learning about AI ethics and compliance

  • Iterative improvement of our technology and processes

Escalation Process:

  • Clear procedures for reporting concerns about our system

  • Investigation and response protocols for potential issues

  • Communication plans for stakeholders affected by problems

  • Commitment to transparency about limitations and failures


Current Status & Roadmap

Where We Are Now:

  • Early-stage system with basic transparency and oversight

  • Focused on core functionality and user experience

  • Building compliance capabilities as we scale

  • Learning from each implementation and customer interaction

Near-Term Priorities:

  • Enhanced documentation and explainability features

  • Improved bias detection and monitoring capabilities

  • Stronger data governance and privacy protections

  • Expanded compliance frameworks as we grow

Long-Term Vision:

  • Industry-leading transparency and explainability

  • Comprehensive bias testing and mitigation

  • Full regulatory compliance across all jurisdictions

  • Gold standard for responsible AI in hiring


Contact & Questions

For questions about our AI practices, compliance approach, or this framework: info@shortlistd.io


Disclaimer

This framework represents our current approach and intentions regarding responsible AI development. As an early-stage company, our practices are evolving rapidly. We commit to transparency about our capabilities and limitations while continuously improving our systems and processes.

This document will be updated regularly to reflect our progress and changing circumstances. We welcome feedback and questions about our approach to building responsible AI for hiring.


Last updated: 16 August 2025