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AI Use Policy

Effective: June 11, 2025

Last updated: March 11, 2026

1. Introduction

Genuinelink B.V. ("Company," "we," "us," or "our") is committed to the responsible development and use of artificial intelligence ("AI") technologies. This AI Use and Ethics Policy ("Policy") outlines our principles, practices, and commitments regarding AI use in our LinkedIn outreach platform.

2. AI Principles

2.1 Human-Centered AI

  • Human Oversight: AI systems are designed to augment human capabilities, not replace human judgment
  • Human-in-the-Loop: Critical decisions involving AI maintain human oversight and control
  • Transparency: AI decision-making processes are explainable and understandable
  • Accountability: Clear responsibility for AI-generated outputs and decisions

2.2 Fairness and Non-Discrimination

  • Bias Mitigation: We actively work to identify and reduce bias in our AI systems
  • Equal Treatment: AI systems treat all users and data subjects fairly and equally
  • Diverse Training Data: We use diverse, representative datasets for AI training
  • Regular Auditing: We regularly audit AI systems for fairness and bias

2.3 Privacy and Data Protection

  • Data Minimization: We collect and use only the minimum data necessary for AI processing
  • Purpose Limitation: AI processing is limited to specified, legitimate purposes
  • Consent: We obtain appropriate consent for AI processing of personal data
  • Data Security: AI systems implement robust security measures to protect data

2.4 Transparency and Explainability

  • Clear Communication: We clearly communicate when AI is being used
  • Explainable AI: We provide explanations for AI-generated content and decisions
  • User Control: Users have control over AI-generated content and can modify or reject it
  • Openness: We are transparent about our AI capabilities and limitations

3. AI Use Cases

3.1 Message Generation

Our AI generates personalized LinkedIn messages based on:

  • Profile Analysis: Analysis of LinkedIn profiles and professional information
  • Context Understanding: Understanding of industry, role, and company context
  • Personalization: Customization based on user preferences and campaign goals
  • Tone Matching: Matching appropriate professional tone and style

3.2 Content Optimization

Our AI optimizes content for:

  • Engagement: Improving message open rates and response rates
  • Relevance: Ensuring content is relevant to recipients
  • Compliance: Maintaining compliance with LinkedIn's terms and policies
  • Effectiveness: Maximizing campaign performance and results

3.3 Analytics and Insights

Our AI provides insights through:

  • Performance Analysis: Analysis of campaign performance and metrics
  • Trend Identification: Identification of trends and patterns in data
  • Recommendation Engine: Recommendations for campaign improvements
  • Predictive Analytics: Predictive insights for future campaign success

4. AI Governance

4.1 AI Ethics Committee

We maintain an AI Ethics Committee responsible for:

  • Policy Development: Developing and updating AI policies and guidelines
  • Risk Assessment: Assessing AI risks and implementing mitigation measures
  • Compliance Monitoring: Monitoring compliance with AI ethics principles
  • Stakeholder Engagement: Engaging with stakeholders on AI-related issues

4.2 AI Risk Management

We implement comprehensive risk management for AI systems:

  • Risk Identification: Regular identification of AI-related risks
  • Risk Assessment: Assessment of risk likelihood and impact
  • Risk Mitigation: Implementation of appropriate risk mitigation measures
  • Risk Monitoring: Continuous monitoring of AI system performance and risks

4.3 AI Quality Assurance

We maintain rigorous quality assurance processes:

  • Testing: Comprehensive testing of AI systems before deployment
  • Validation: Validation of AI outputs and decision-making processes
  • Monitoring: Continuous monitoring of AI system performance
  • Improvement: Regular improvement and updating of AI systems

5. Data Handling and Privacy

5.1 Data Collection

We collect data for AI processing in accordance with our Privacy Policy:

  • LinkedIn Data: Professional information from LinkedIn profiles
  • User Data: User preferences, settings, and campaign data
  • Interaction Data: Data about user interactions with our platform
  • Performance Data: Data about campaign performance and outcomes

5.2 Data Processing

AI data processing follows these principles:

  • Lawful Basis: All AI processing has a lawful basis under applicable data protection laws
  • Purpose Limitation: Data is processed only for specified, legitimate purposes
  • Data Minimization: We process only the minimum data necessary for AI functionality
  • Accuracy: We maintain accurate and up-to-date data for AI processing

5.3 Data Security

We implement robust security measures for AI data:

  • Encryption: All data is encrypted in transit and at rest
  • Access Controls: Strict access controls limit who can access AI data
  • Anonymization: Personal data is anonymized or pseudonymized when possible
  • Regular Audits: Regular security audits of AI data handling processes

6. User Rights and Controls

6.1 User Control

Users have the following controls over AI use:

  • Opt-Out: Users can opt out of AI-generated content
  • Modification: Users can modify or reject AI-generated content
  • Transparency: Users can understand how AI is being used
  • Data Access: Users can access their data used for AI processing

6.2 Data Subject Rights

Data subjects have the following rights regarding AI processing:

  • Right to Information: Information about AI processing of their data
  • Right to Access: Access to their data used for AI processing
  • Right to Rectification: Correction of inaccurate data used for AI processing
  • Right to Erasure: Deletion of their data from AI systems
  • Right to Object: Objection to AI processing of their data

6.3 Human Review

We provide human review processes for:

  • AI-Generated Content: All AI-generated content can be reviewed and modified by users
  • Automated Decisions: Users can request human review of automated decisions
  • Appeals Process: Users can appeal AI-generated decisions or recommendations
  • Quality Assurance: Human review of AI outputs for quality and accuracy

7. Compliance and Legal Requirements

7.1 Data Protection Compliance

Our AI systems comply with:

  • GDPR: General Data Protection Regulation (EU) 2016/679
  • CCPA: California Consumer Privacy Act
  • UK GDPR: UK General Data Protection Regulation
  • Other Applicable Laws: All other applicable data protection laws

7.2 AI-Specific Regulations

We comply with AI-specific regulations including:

  • EU AI Act: European Union Artificial Intelligence Act
  • Algorithmic Accountability: US Algorithmic Accountability Act
  • AI Ethics Guidelines: Industry and government AI ethics guidelines
  • Professional Standards: Professional standards for AI use

7.3 Regular Compliance Audits

We conduct regular compliance audits to ensure:

  • Legal Compliance: Compliance with all applicable laws and regulations
  • Ethical Compliance: Adherence to AI ethics principles and guidelines
  • Technical Compliance: Technical compliance with AI standards and best practices
  • Operational Compliance: Operational compliance with internal policies and procedures

8. Continuous Improvement

8.1 AI System Updates

We continuously improve our AI systems through:

  • Regular Updates: Regular updates to AI models and algorithms
  • Performance Monitoring: Continuous monitoring of AI system performance
  • User Feedback: Incorporation of user feedback into AI improvements
  • Research and Development: Ongoing research and development of AI capabilities

8.2 Bias Detection and Mitigation

We actively work to detect and mitigate bias through:

  • Bias Audits: Regular audits of AI systems for bias and discrimination
  • Diverse Training Data: Use of diverse, representative training datasets
  • Bias Testing: Testing of AI systems for bias in different scenarios
  • Bias Mitigation: Implementation of bias mitigation techniques and strategies

8.3 Performance Monitoring

We monitor AI system performance through:

  • Key Performance Indicators: Regular monitoring of AI performance metrics
  • User Satisfaction: Monitoring of user satisfaction with AI-generated content
  • Accuracy Metrics: Tracking of AI accuracy and reliability
  • Error Analysis: Analysis of AI errors and implementation of improvements

9. Incident Response

9.1 AI Incident Response Plan

We maintain an AI incident response plan for:

  • Bias Incidents: Response to incidents involving AI bias or discrimination
  • Privacy Breaches: Response to AI-related privacy breaches
  • System Failures: Response to AI system failures or malfunctions
  • Security Incidents: Response to AI-related security incidents

9.2 Incident Reporting

We have procedures for:

  • Internal Reporting: Internal reporting of AI incidents and issues
  • External Reporting: External reporting to relevant authorities when required
  • User Notification: Notification of users affected by AI incidents
  • Remediation: Implementation of remediation measures for AI incidents

10. Training and Awareness

10.1 Staff Training

We provide training to our staff on:

  • AI Ethics: AI ethics principles and best practices
  • Data Protection: Data protection requirements for AI systems
  • Bias Awareness: Awareness of bias and discrimination in AI systems
  • Compliance: Compliance with AI-related laws and regulations

10.2 User Education

We educate users about:

  • AI Capabilities: What our AI can and cannot do
  • AI Limitations: Limitations and potential risks of AI use
  • User Controls: How users can control AI use and outputs
  • Best Practices: Best practices for using AI-generated content

11. Third-Party AI Services

11.1 Third-Party AI Providers

When using third-party AI services, we ensure:

  • Due Diligence: Thorough due diligence of third-party AI providers
  • Contractual Protections: Appropriate contractual protections for AI use
  • Compliance: Third-party compliance with our AI ethics principles
  • Monitoring: Regular monitoring of third-party AI service performance

11.2 AI Service Integration

We integrate third-party AI services with:

  • Data Protection: Appropriate data protection measures
  • Security Controls: Robust security controls for AI data
  • Compliance: Compliance with applicable laws and regulations
  • Quality Assurance: Quality assurance processes for AI outputs

12. Contact Information

For questions about this AI Use and Ethics Policy, contact us at [email protected].

13. Updates to This Policy

We may update this Policy periodically to reflect:

  • Changes in AI technology and capabilities
  • Updates to applicable laws and regulations
  • Improvements to our AI ethics practices
  • Feedback from stakeholders and users

We will notify users of material changes through:

  • Email notifications
  • Service announcements
  • Website updates
  • Account notifications

This AI Use and Ethics Policy is effective as of June 11, 2025 and was last updated on March 11, 2026.