AI Compliance Checklist

AI Compliance Checklist

Navigating the complex legal and regulatory landscape surrounding artificial intelligence (AI) can be challenging for software companies. Use this AI compliance checklist to help your organization stay up-to-date with relevant requirements and maintain a responsible approach to AI development and deployment:

1. Data Protection and Privacy

   • Comply with data protection regulations such as GDPR, CCPA, and other relevant regional laws.

   • Implement privacy-by-design principles during AI development.

   • Ensure proper data anonymization and pseudonymization techniques are in place.

   • Obtain explicit consent from users for data collection and processing, where required.

2. Algorithmic Fairness and Bias

   • Assess and monitor AI algorithms for potential bias and discrimination.

   • Implement measures to mitigate algorithmic bias, such as re-sampling, re-weighting, or adversarial training.

   • Ensure AI models are trained on representative and diverse datasets.

   • Document the steps taken to address bias and promote fairness in AI systems.

3. Transparency and Explainability

   • Adopt techniques to enhance the explainability of AI models, such as model interpretability and feature importance analysis.

   • Maintain a centralized system for AI governance and compliance efforts (‘AI System of Record’) that provides comprehensive transparency across the organization of proposed and active AI efforts.

   • Ensure that the organization is trained and has the necessary access to the AI System of Record for their ongoing work and reporting.

   • Provide clear documentation on AI system functionality and decision-making processes.

   • Communicate transparently with users about the use of AI and its potential impact on their experience.

4. AI Ethics and Governance

   • Develop and implement a comprehensive AI ethics policy.

   • Establish a multidisciplinary AI risk management team. (‘AI Governance Board’)

   • Regularly review and update AI policies and guidelines to align with industry best practices and evolving standards.

   • Foster a culture of responsible AI use within the organization through training and employee engagement.

5. Security and Cybersecurity

   • Implement robust security measures to protect AI infrastructure and data.

   • Conduct regular vulnerability assessments and penetration testing.

   • Train employees on AI-related security risks and best practices.

   • Develop an incident response plan to address potential AI-related security breaches.

6. Intellectual Property (IP) Rights

   • Understand and comply with IP laws related to AI, including copyright, patents, and trade secrets.

   • Secure necessary licenses for third-party software, data, and algorithms used in AI development.

   • Ensure that all 3rd party AI partners operate according to the AI policies of the organization.

   • Protect your organization's AI-related IP assets through appropriate legal mechanisms.

7. Legal and Regulatory Compliance

   • Stay informed about evolving AI-related legal and regulatory requirements.

   • Conduct regular compliance audits to ensure adherence to relevant laws and regulations.

   • Collaborate with legal and compliance experts to navigate the complex AI regulatory landscape.

8. Accessibility and Inclusivity

   • Design AI systems to be accessible and inclusive for users with diverse abilities and backgrounds.

   • Comply with accessibility standards such as the Web Content Accessibility Guidelines (WCAG) and the Americans with Disabilities Act (ADA).

   • Regularly test AI systems for accessibility and inclusivity, incorporating user feedback for improvements.