The EU AI Act has emerged as the cornerstone of EU policy on the deployment and adoption of artificial intelligence (AI) by enterprises, where it attempts to mitigate potential risks, safeguard human rights, and build trust in AI development and deployment across the EU. This groundbreaking legislation not only sets rigorous standards for AI development but also champions responsible data governance, data quality, and transparency.
In recent years, the landscape of AI technology has undergone remarkable evolution, presenting organisations with unprecedented opportunities and challenges.
For organisations venturing into AI initiatives, compliance with the EU AI Act isn’t merely a legal obligation; it’s a strategic imperative, especially when dealing with sensitive data.
In this blog, we explore the pivotal highlights of this regulation, its implications and the steps organisation can take to achieve full compliance.
Understanding the EU AI Act
The EU AI Act stands as a pioneering regulation designed to govern artificial intelligence systems, placing a strong emphasis on upholding fundamental rights, and preventing potential AI-induced harm.
Notably, the Act classified AI systems into four risk levels, with the highest category banning systems like mass social scoring and real-time biometric surveillance. It also mandates transparency obligations on AI models, including clear labelling of AI-generated content.
While its immediate impact is felt within the European market, the influence of the EU AI Act extends globally, representing a significant milestone in AI regulation.
Key Provisions and Their Impact
The Act's provisions span various facets of AI development and deployment, each with implications for the AI landscape:
Banning Threatening AI Systems:
The legislation prohibits AI systems deemed to pose a clear threat to human safety, livelihoods, and rights. This includes imposing stringent regulations on high-risk programs employed in critical infrastructure, law enforcement, and elections.
Regulating Government Surveillance:
Acknowledging the potential misuse of AI in biometric surveillance and social scoring, the EU AI Act imposes restrictions on intrusive applications. Specifically, real-time facial recognition in public spaces is constrained, with exceptions granted for specific law enforcement purposes.
Transparency Requirements:
The Act mandates transparency obligations for AI models prior to market entry, particularly focusing on foundation models like ChatGPT. AI-generated content, including manipulated images and videos (such as deepfakes), must be clearly identified as AI-generated, thus mitigating the potential spread of misinformation and manipulation.
Risk-Based Approach:
One of the core principles of the EU AI Act is its adoption of a risk-based approach to AI regulation. This means that AI systems are classified into four risk levels: unacceptable, high, limited and minimal/none, based on the degree of threat they pose. High-risk AI systems face specific legal requirements that includes:
Registering with an EU database
Implementing a compliant quality management system
Undergoing conformity assessments.
Implications and Enforcement
The EU AI Act is poised to become law soon, with phased rollout planned across member states over the next three years. Its reach extends beyond European boarders, meaning that AI providers accessing the European market must adhere to its provisions to protect European citizens' rights.
While the formal adoption is set for April 2024, businesses are granted a 24-month grace period to achieve full compliance. Non-compliance with the Act can result in hefty penalties, ranging from €35 million or 7% of global revenue to €7.5 million or 1.5% of revenue, depending on the infringement.
Impact on the Banking Sector
As the EU AI Act lays down the groundwork for responsible AI governance, its implications are expected to transcend mere compliance, gradually evolving into a de facto standard across various sectors, including banking.
Institutions operating within this realm, especially those leveraging general-purpose AI system like LLMs, are urged to carefully assess the Act’s key provisions. Whether explicitly for regulatory compliance purposes or implicitly to enhance data governance, systems, process and reporting capabilities.
For banks aligning closely with the Act’s directives, the benefits are manifold. They become better equipped to adapt to future changes, more agile in responding to threats and opportunities, and may face less regulatory scrutiny due to higher confidence.
Achieving the Full AI Compliance
Full AI compliance demands a shift from a fragmented approach to strong integration and cooperation, particularly between the Risk, Governance and Data departments. If any warning signs appear in current data access control system, it's time to take decisive action.
Here are some steps to achieve full compliance:
Perform a comprehensive compliance health check assessment to identify vulnerabilities and gaps in your existing controls and knowledge base, while identifying clearly the risk levels you are undertaking on your AI projects.
Choose an automated data governance engine with patented security feature that seamlessly integrates with data catalogs like Collibra, Atlas, Alation or Informatica.
Implement data quality policies and automate the tokenization of PII data for all data sets that are used to train and run AI Models.
Get an auditable query log allowing organisation to validate the effectiveness of the data controls. This log should provide insights into general and sensitive data access.
Design your engineering environment so that compliance with the AI Act is an output of the process (i.e. logs, audit records, documentation, etc.), which will expedite the compliant usage of AI within your organization.
From the design stage of your AI project, ensure that Human oversight is designed into the complete process.
Remain updated on emerging threats and regulatory changes to adjust access controls and address new risks and compliance mandates.
Bonus Tip: Start with Automation
As technological advancements transform our world, navigating the evolving EU AI regulation requires collaborative efforts and ongoing vigilance.
Bluemetrix brings deep regulatory expertise and proven solutions that help banks and modern companies build the vision, strategies, and data capabilities needed for compliance. Our AI/Gen AI Health Check approach, complemented by NIST FIPS 140-3 compatible ETL solution, enables organisations to drive more visibility, trust, and automation into their data and AI practices.
Discover how Bluemetrix can help your organization chart a successful path forward in the era of responsible AI. Request a free data consultation today and take the first step towards building a future-ready, compliant data ecosystem.