EU AI ACT – AI System Classification

According to the European Commission’s guidelines, “The AI Act lays down harmonised rules for the placing on the market, putting into service, and use of artificial intelligence (‘AI’) in the Union.2 Its aim is to promote  innovation in and the uptake of AI, while ensuring a high level of protection of health, safety and fundamental rights in the Union, including democracy and the rule of law.”

Risk-Based Approach to AI Systems Classification

The AI Act follows a risk-based approach, classifying AI systems into four different risk categories:

(i) Unacceptable risk: AI systems posing unacceptable risks to fundamental rights and Union values are prohibited under Article 5 AI Act.

(ii) High risk: AI systems posing high risks to health, safety and fundamental rights are subject to a set of requirements and obligations. These systems are classified as ‘high-risk’ in accordance with Article 6 AI Act in conjunction with Annexes I and III AI Act.

(iii) Transparency risk: AI systems posing limited transparency risk are subject to transparency obligations under Article 50 AI Act.

(iv) Minimal to no risk: AI systems posing minimal to no risk are not regulated, but providers and deployers may voluntarily adhere to voluntary codes of conduct.

Pursuant to Article 96(1)(b) AI Act, the Commission is to adopt guidelines on the practical implementation of the practices prohibited under Article 5 AI Act.

Next Steps

• If you’re interested in bespoke training or design solutions on AI fairness, feel free to reach out for a consultation.

• Check out our the following resources and upcoming workshops to equip your teams with the tools and knowledge to implement fair AI systems.

Free Resources for Individual Fairness Design Considerations

Data Bias

Sampling Bias in Machine Learning

Social Bias in Machine Learning

Representation Bias in Machine Learning

 

Conditional Demographic Parity Guidance – £99

Empower your team to drive Responsible AI by fostering alignment with compliance needs and best practices.

Practical, easy-to-use guidance from problem definition to model monitoring
Checklists for every phase in the AI/ ML pipeline

Get Conditional Demographic Parity  – (Delivery within 2-3 days)

 

 

AI Fairness Mitigation Package – £999

The ultimate resource for organisations ready to tackle bias at scale starting from problem definition through to model monitoring to drive responsible AI practices.

Mitigate and resolve 15 Types of Fairness specific to your project with detailed guidance from problem definition to model monitoring.

Packed with practical methods, research-based strategies, and critical questions to guide your team.

Comprehensive checklists for every phase in the AI/ ML pipeline

Get Fairness Mitigation Package– (Delivery within 2-3 days)

 

Customised AI Fairness Mitigation Package – £2499

We’ll customise the design cards and checklists to meet your specific use case and compliance requirements—ensuring the toolkit aligns perfectly with your goals and industry standards.

Mitigate and resolve 15 Types of Fairness specific to your project with detailed guidance from problem definition to model monitoring.

Packed with practical methods, research-based strategies, and critical questions specific to your use case.

Customised checklists for every phase in the AI/ ML pipeline

Get Customised AI Fairness Mitigation Package– (Delivery within 7 days)