AI Policy

Introduction

This AI Policy outlines our commitment to responsible, ethical, and transparent use of artificial intelligence in delivering custom AI solutions to our clients. As an AI services consulting agency, we recognize the profound impact AI technologies have on businesses and society, and we are dedicated to deploying these technologies in ways that maximize benefits while minimizing risks.

 

Our AI Principles

Transparency and Explainability

We maintain transparency about our AI capabilities, limitations, and methodologies. We provide clear documentation about how our AI solutions work, including the types of models used, data requirements, and decision-making processes. Where possible, we prioritize explainable AI approaches that allow stakeholders to understand how conclusions are reached.

Human Oversight and Control

All AI systems we develop or deploy include appropriate human oversight mechanisms. We believe AI should augment human decision-making, not replace it entirely. Critical decisions, particularly those affecting individuals’ rights or wellbeing, maintain meaningful human review and intervention capabilities.

Fairness and Non-Discrimination

We actively work to identify and mitigate bias in AI systems. Our development process includes testing for discriminatory outcomes across different demographic groups and use cases. We do not knowingly develop AI solutions that discriminate based on protected characteristics or perpetuate unfair treatment.

Privacy and Data Protection

We implement privacy-by-design principles in all our AI solutions. Client data and end-user information are handled with strict confidentiality and security measures. We comply with applicable data protection regulations including GDPR, CCPA, and other relevant frameworks.

Safety and Security

We build robust, secure AI systems designed to operate reliably within their intended scope. Our solutions include safeguards against misuse, adversarial attacks, and unintended harmful outcomes. We conduct thorough testing before deployment and maintain ongoing monitoring post-launch.

 

Data Handling Practices

Client Data

Collection and Use: We collect only the data necessary to deliver our services effectively. Client data is used exclusively for the purposes agreed upon in our service agreements.
Storage and Security: All client data is encrypted in transit and at rest. We maintain industry-standard security practices including access controls, regular security audits, and incident response procedures.
Data Retention: Client data is retained only as long as necessary to fulfill contractual obligations or as required by law. Upon project completion or contract termination, data is securely deleted or returned to the client as specified in our agreements.
Third-Party Processing: When we use third-party AI services or APIs, we ensure these providers meet our privacy and security standards. We maintain data processing agreements with all subprocessors and limit data sharing to what is strictly necessary.

Training Data

When developing custom AI models, we ensure training data is:

  • Obtained legally and ethically with appropriate rights and consents
  • Representative and diverse to minimize bias
  • Properly documented with clear data lineage
  • Regularly reviewed for quality and appropriateness

We do not use client proprietary data to train models for other clients without explicit written consent.

 

AI Solution Development

Quality Assurance

Our AI solutions undergo rigorous testing including:

  • Functional testing to verify intended performance
  • Adversarial testing to identify vulnerabilities
  • Bias testing across relevant demographic groups
  • Performance validation on real-world scenarios
  • Edge case analysis to understand limitations

Limitations and Risks

We clearly communicate the limitations of our AI solutions, including:

  • Accuracy rates and confidence intervals
  • Known edge cases or failure modes
  • Data requirements and dependencies
  • Computational resource needs
  • Regulatory or ethical constraints

Documentation and Support

Every AI solution we deliver includes comprehensive documentation covering architecture, capabilities, limitations, maintenance requirements, and best practices for responsible use. We provide ongoing support to ensure proper implementation and operation.

 

Ethical Guidelines

 

Prohibited Use Cases

We do not develop AI solutions for:

  • Surveillance or monitoring that violates privacy rights or civil liberties
  • Autonomous weapons or systems designed to cause harm
  • Manipulation or deception at scale
  • Credit scoring or hiring decisions without human oversight and appeal mechanisms
  • Any purpose that violates applicable laws or regulations

Client Responsibility

While we build responsible AI solutions, we recognize that deployment context matters significantly. We require clients to:

  • Use our AI solutions only for their intended purpose
  • Maintain appropriate human oversight
  • Comply with all applicable laws and regulations
  • Implement our recommended safeguards and monitoring
  • Disclose to end-users when AI is being used in consequential decisions

 

 

Regulatory Compliance

We stay current with evolving AI regulations globally and ensure our solutions comply with:

  • Data protection laws (GDPR, CCPA, etc.)
  • Industry-specific regulations (financial services, healthcare, etc.)
  • Emerging AI-specific legislation (EU AI Act, algorithmic accountability laws)
  • Export controls and cross-border data transfer rules

Our compliance approach is proactive, and we work with clients to navigate regulatory requirements in their specific jurisdictions and sectors.

 

Continuous Improvement

AI technology and best practices evolve rapidly. We commit to:

  • Regular training for our team on AI ethics, security, and emerging techniques
  • Staying informed about AI research, regulations, and industry standards
  • Updating our methodologies based on new insights and lessons learned
  • Soliciting feedback from clients and stakeholders
  • Conducting periodic reviews of deployed AI systems for performance and fairness

Model Governance

For AI models we develop or customize:
Version Control: We maintain detailed version history, allowing rollback if issues arise.
Performance Monitoring: We implement monitoring systems to detect degradation, drift, or anomalous behavior over time.
Update Procedures: Model updates follow controlled processes with testing and validation before deployment.
Incident Response: We maintain procedures for rapidly addressing AI system failures or unintended behaviors.

Transparency with End Users

We advocate that our clients inform end users when they interact with AI systems, particularly when:

  • AI makes or significantly influences consequential decisions
  • Personal data is processed by AI
  • Content is AI-generated

We provide guidance and tools to help clients implement appropriate disclosure mechanisms.

Accountability

We take responsibility for the AI solutions we deliver. Our accountability framework includes:

    • Clear contracts defining responsibilities and liabilities
    • Designated points of contact for AI-related concerns
    • Processes for investigating and addressing complaints
    • Insurance coverage for professional liability
    • Commitment to correcting issues promptly when identified

 

Reporting Concerns

If you have concerns about our AI practices or a solution we’ve delivered, please contact us at [your contact email/form]. We take all concerns seriously and investigate them thoroughly. We protect whistleblowers and those who report concerns in good faith.

Policy Updates

This AI Policy is reviewed and updated regularly to reflect technological advances, regulatory changes, and evolving best practices. Material changes will be communicated to active clients and posted on our website.

For questions about this AI Policy or how it applies to your project, please contact our team.