AI Acceptable Use Policy (SEC-POL-007)

1. Objective

This policy establishes requirements for the responsible development, deployment, and use of artificial intelligence systems within [Company Name]’s video streaming platform. The framework ensures AI technologies are used ethically, securely, and in compliance with applicable regulations while maintaining user trust and platform integrity. This comprehensive approach promotes innovation while mitigating risks associated with automated decision-making systems that impact millions of users globally.

2. Scope

This policy applies to all AI and machine learning systems used by [Company Name], including content recommendation algorithms, content moderation systems, user behavior analysis tools, and any AI-powered features accessible to users. Coverage extends to all employees, contractors, and third parties involved in AI development, deployment, or operation across development, testing, and production environments.

3. Policy

3.1 AI Governance and Oversight

The Company must maintain [AI Governance Body Name] with diverse stakeholder representation and implement risk assessment requirements for all AI system deployments. The Company must conduct regular audits of AI system performance and bias metrics and establish clear accountability and decision-making frameworks. The Company must integrate AI governance with overall risk management and compliance programs.

3.2 Content Moderation AI Systems

AI systems used for content moderation must conduct regular bias testing across demographic groups and content types. The Company must implement human review requirements for high-impact moderation decisions and provide transparency reporting on automated content actions. The Company must establish user appeal mechanisms for AI-driven content decisions and ensure compliance with EU Digital Services Act algorithmic accountability requirements. The Company must perform regular retraining to address emerging content threats and reduce false positives.

3.3 Recommendation Algorithm Governance

Content recommendation systems must conduct regular assessment of algorithmic amplification effects and perform bias testing to prevent discriminatory content promotion. The Company must implement user control mechanisms for recommendation preferences and provide transparency regarding recommendation factors and data usage. The Company must maintain protection against manipulation and coordinated inauthentic behavior and ensure compliance with DSA requirements for recommender system transparency.

3.4 AI System Security

All AI systems must implement secure development lifecycle practices for AI/ML models and maintain protection against adversarial attacks and model poisoning. The Company must ensure secure model storage and version control and implement access controls for training data and model parameters. The Company must monitor for unauthorized model access or extraction and conduct regular security testing specific to AI/ML vulnerabilities.

3.5 Data Privacy and AI

AI systems must implement privacy-by-design principles in AI system development and ensure data minimization for AI training and inference. The Company must establish user consent mechanisms for AI-driven features and maintain compliance with GDPR automated decision-making requirements. The Company must ensure COPPA compliance for AI systems affecting children and conduct regular privacy impact assessments for AI deployments.

Enhanced COPPA Protections for Children:

  • Recommendation algorithms are specifically designed to prevent profiling of users known to be under 13 for advertising purposes
  • Children’s data is not used to train models for features that are not directed at children or age-appropriate
  • AI-driven content moderation systems include enhanced protections for child safety and age-appropriate content filtering
  • Behavioral advertising algorithms are completely disabled for users under 13 years of age
  • Machine learning models processing children’s data undergo additional bias testing for age-appropriate content recommendations
  • AI systems affecting children undergo enhanced privacy impact assessments with specific COPPA compliance verification

3.6 AI Transparency and Explainability

AI systems must provide documentation of AI system purpose, capabilities, and limitations and implement explainable AI techniques for high-impact decisions. The Company must notify users when AI systems significantly affect their experience and provide public reporting on AI system performance and bias metrics with clear communication about AI capabilities and limitations to users.

3.7 Third-Party AI Services

Use of external AI services must include security and privacy assessments of AI service providers and establish contractual requirements for bias testing and transparency. The Company must implement data protection agreements covering AI training and inference data and conduct regular monitoring of third-party AI service performance. The Company must maintain contingency planning for AI service disruptions or terminations.

3.8 Prohibited AI Uses

The Company prohibits discriminatory profiling based on protected characteristics and manipulation of user behavior for harmful purposes. The Company prohibits surveillance systems that violate user privacy expectations and AI systems that lack appropriate human oversight for high-risk decisions. The Company prohibits deep fake or synthetic media creation without clear disclosure.

4. Standards Compliance

Policy Section Standard/Framework Control Reference
3.1 EU Digital Services Act Art. 27
3.1 PCI DSS v4.0 Req. 12.1
3.2 EU Digital Services Act Art. 16
3.2 PCI DSS v4.0 Req. 12.10.7
3.3 EU Digital Services Act Art. 27
3.4 PCI DSS v4.0 Req. 6.1, 6.2
3.5 GDPR Art. 22
3.5 COPPA § 312.2
3.5 PCI DSS v4.0 Req. 3.1, 7.1
3.6 ISO/IEC 23053:2022 Framework for AI Risk Management
3.6 PCI DSS v4.0 Req. 12.1
3.8 EU AI Act Art. 5

5. Definitions

Artificial Intelligence (AI): Systems that display intelligent behavior by analyzing their environment and taking actions to achieve specific goals.

Algorithmic Bias: Systematic and unfair discrimination in automated decision-making systems that affects certain groups disproportionately.

Content Moderation AI: Automated systems used to detect, classify, and take action on user-generated content that may violate platform policies.

Recommendation Algorithm: AI systems that select and personalize content shown to users based on their preferences and behavior.

Explainable AI: AI systems designed to provide understandable explanations for their decisions and recommendations.

Adversarial Attack: Intentional manipulation of AI system inputs designed to cause incorrect or harmful outputs.

Deep Fake: Synthetic media created using AI techniques to replace a person’s likeness with someone else’s.

6. Responsibilities

Role Responsibility
[AI Governance Body Name] Provide governance oversight for AI systems, review high-risk AI deployments, and ensure compliance with ethical AI principles.
Data Science Teams Develop and maintain AI systems following responsible AI practices, conduct bias testing, and implement transparency measures.
[Trust & Safety Department/Team Name] Monitor AI system performance for content moderation, investigate bias reports, and ensure DSA compliance for automated content decisions.
[Privacy Department/Team Name] Conduct privacy impact assessments for AI systems, ensure GDPR compliance for automated decision-making, and protect user data in AI systems.
[Legal Department/Team Name] Ensure AI systems comply with applicable laws and regulations, review AI vendor contracts, and provide guidance on emerging AI regulations.
[Security Department/Team Name] Implement security controls for AI systems, monitor for AI-specific threats, and conduct security assessments of AI deployments.

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