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Why U.S. companies should care about the EU AI Act

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Category: AI Legal Compliance

What is the Objective of the EU AI act?

The AI Act aims to establish a comprehensive legal framework on AI worldwide for fostering trustworthy AI in Europe and beyond, by ensuring that AI systems respect fundamental rights, safety, and ethical principles by addressing the risks of very powerful and impactful AI models. The Act aims to ensure AI is developed and used responsibly.

The European Union's AI regulations have significant implications for tech developers at U.S. companies, even those operating outside of Europe. The EU's regulations, such as the proposed Artificial Intelligence Act, aims to establish a comprehensive framework for the development and deployment of artificial intelligence systems with a focus on ethics, transparency, and accountability. 

Given the global nature of many U.S. firms compliance with these International standards is essential. Aligning with EU regulations requires U.S. companies to adopt ethical AI practices and integrate privacy preserving Technologies into their development processes. This shift involves not only adhering to legal requirements but also embracing a broader commitment to responsible AI.

The Categorization of AI Systems

The four levels of risk for AI systems as defined by the regulatory framework.

The High-Risk AI Systems

  • Biometric Identification
  • Law Enforcement
  • Migration, asylum, and border Control management
  • Education Employment
  • Medical AI
  • Life and Health Insurance 
  • Creditworthiness Check

The Specific Exemptions in the AI Act.

The regulation has also included specific exemptions.

Which U.S. entities will be affected by the act? 

Providers.

This applies to U.S. providers of AI Systems who have their place of establishment or are located outside the EU but where the output produced by the AI System is used in the EU. This means that Most Businesses that develop AI Systems are likely to be affected as well as those deploying them or merely using them in certain circumstances. Major Tech Companies are set to be affected.

Deployers.

This applies to U.S. deployers of AI Systems who have their place of establishment or are located outside the EU but where the output produced by the AI system is used in the EU.

Importers.

U.S. entities that make the AI system available on the EU market. According to the AI Act, an organization which is based in the EU and which markets an AI system that is named after, or has the trademark of, a foreign entity shall be classified as the importer.

Product Manufacturers.

U.S. product manufacturers who place or put into service an AI system in the EU with their product and under their name or trademark Act. The scope of the AI Act will include AI providers who, on the market and under their name or trademark, offer a product and its AI system integrated with the product.

 

Adherence Standards for US Firms.

Penalties for Non-Compliance

The losses resulting from violations of the provision of the AI Act are severe. These range between € 750.000 to € 35.000.000 or 3% to 7 % of the annual worldwide revenue of the company and these will be based on the extent of the offense committed. Subsequently, it is important for enterprises to make sure that all the provisions of the AI Act are clear to them and comply with the requirements of the law to avoid such penalties.

AI Regulatory Compliance & Governance Frameworks

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Category: AI Legal Compliance

 

Ai Governance Frameworks

The development of AI governance frameworks involves creating comprehensive policies, procedures, and guidelines to ensure the ethical, legal, and effective use of AI technologies within an organization. This process typically includes the following components:

  1. Ethical Guidelines: Establishing principles that guide the ethical use of AI, such as fairness, transparency, accountability, and respect for privacy and human rights.

  2. Compliance Policies: Ensuring that AI systems adhere to relevant laws and regulations, including data protection laws, industry standards, and sector-specific regulations.

  3. Risk Management: Identifying and mitigating risks associated with AI deployment, including potential biases, security vulnerabilities, and operational risks.

  4. Operational Procedures: Developing standard operating procedures (SOPs) for the development, deployment, and monitoring of AI systems to ensure they function as intended and remain compliant over time.

  5. Data Management: Implementing policies for data collection, storage, usage, and sharing to ensure data quality, security, and privacy.

  6. Transparency and Explainability: Creating mechanisms to ensure AI decisions are transparent and explainable to stakeholders, including users, regulators, and impacted individuals.

  7. Accountability Structures: Defining roles and responsibilities for AI governance within the organization, including the establishment of AI ethics boards or committees.

  8. Continuous Monitoring and Auditing: Setting up systems for ongoing monitoring and periodic auditing of AI systems to ensure they continue to meet governance standards and adapt to new challenges.

  9. Stakeholder Engagement: Involving relevant stakeholders in the development and review of AI policies and frameworks to ensure broad support and address diverse perspectives.

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