It’s easy to overlook the complex web of regulations that govern artificial intelligence use. Yet, as the European Union’s AI Act and the General Data Protection Regulation (GDPR) set stringent standards, non-compliance can lead to significant penalties and reputational damage. Here are five common AI compliance mistakes and strategies to avoid them.
1. Neglecting AI Risk Classification
The EU AI Act categorises AI systems into risk levels: unacceptable, high, limited, and minimal. Misclassifying your AI system can lead to inadequate compliance measures. Wikipedia
Avoidance Strategy:
Conduct a thorough assessment to determine your AI system’s risk category.
For high-risk systems, ensure compliance with requirements like transparency, data governance, and human oversight.
2. Inadequate Documentation and Transparency
Transparency is a cornerstone of both the AI Act and GDPR. Failing to document AI processes and decisions can hinder compliance and erode user trust.
Avoidance Strategy:
Maintain detailed records of AI system design, data sources, and decision-making processes.
Implement tools like AI Cards to standardise documentation and facilitate transparency.
3. Overlooking Data Protection Principles
AI systems often process personal data, making adherence to GDPR principles essential. Neglecting aspects like data minimisation and user consent can result in violations.
Avoidance Strategy:
Ensure data processing aligns with GDPR principles, including obtaining explicit consent and minimising data collection.
Implement privacy-by-design approaches to embed data protection into AI system development.
4. Insufficient Human Oversight
Relying solely on automated AI decisions without human oversight can lead to non-compliance, especially for high-risk applications.
Avoidance Strategy:
Establish protocols for human review of AI decisions, particularly in critical areas like healthcare or finance.
Train staff to understand and monitor AI system outputs effectively.
5. Failing to Monitor and Update AI Systems
AI systems can evolve over time, potentially altering their risk profiles. Neglecting ongoing monitoring can result in outdated compliance measures.
Avoidance Strategy:
Implement continuous monitoring to detect changes in AI system behaviour.
Regularly review and update compliance strategies to reflect system updates and regulatory changes.
Final Thought
Navigating AI compliance requires a proactive and informed approach. By understanding risk classifications, maintaining transparency, upholding data protection principles, ensuring human oversight, and monitoring system changes, organisations can harness AI’s potential while adhering to regulatory standards.
For further guidance, consider consulting resources like the European Commission’s AI Act documentation and GDPR guidelines to stay abreast of compliance requirements.
Victor A. Lausas
Chief Executive Officer
