The Impact of EU AI Act on High-Risk Systems
The newly introduced EU Artificial Intelligence regulations mark a substantial step forward in safeguarding data privacy, building upon the robust framework established by the General Data Protection Regulation (GDPR). As the digital world continues to evolve, AI systems play an increasingly pivotal role in shaping decisions that affect individuals’ lives, from finance and healthcare to employment and social services. In this context, the new regulations have introduced key measures to ensure that data privacy remains at the forefront of AI development and deployment.
The impact of these regulations is broad and deep, influencing not only how organisations develop and deploy AI but also how they manage, process, and protect personal data. The following discussion will explore the key areas where data privacy is affected and must be carefully considered under these new regulations.
TL;DR: the new EU AI Act is of pivotal importance and as the scope is extra-territorial meaning that UK businesses that develop or deploy AI systems for the EU market fall under its regulation. Now skip to the conclusions to figure out what you need to do!
Data Governance for High-Risk AI
One of the most significant aspects of the new EU AI regulations is the introduction of stringent data governance standards for high-risk AI systems. These are systems that have the potential to impact fundamental rights and freedoms, particularly in sectors like healthcare, law enforcement, education, and employment.
High-risk AI systems must now use datasets that are accurate, relevant, and free from bias. This is critical, as biased or inaccurate data can lead to harmful decisions that disproportionately affect vulnerable groups or individuals. For example, in the hiring process, biased datasets could result in discriminatory outcomes, undermining the fairness and integrity of AI-driven decision-making.
To comply with the new regulations, organisations deploying high-risk AI systems must ensure that personal data is handled lawfully, in adherence to GDPR principles. These principles include data minimisation (only collecting data that is necessary for the intended purpose), accuracy (ensuring that data is kept up to date), and purpose limitation (using data only for the specific reasons for which it was collected). Failure to uphold these principles can result in significant legal consequences and reputational damage.
Upholding Data Subject Rights
Under the new AI regulations, systems that process personal data are required to uphold the rights guaranteed to individuals under the GDPR. This includes ensuring that individuals have the right to access their data, request corrections to inaccurate information, or request the deletion of their data if it is no longer needed for the purposes for which it was collected.
This right to access and control one’s personal data is fundamental to data privacy, as it provides individuals with the means to protect themselves from misuse or abuse of their personal information. For example, if an individual discovers that their data has been used by an AI system to make a decision that adversely affects them—such as being denied a loan or a job—they can request an explanation of how the data was used and demand corrective action if necessary.
Increased Transparency in Data Processing
Transparency is a cornerstone of both the GDPR and the new EU AI regulations. AI systems that interact with people or use personal data in decision-making processes must now clearly explain how that data is being processed. This is particularly important in situations where AI is used to make decisions that have a significant impact on individuals, such as in hiring, lending, or healthcare.
The AI Act mandates that organisations provide clear explanations about when and how AI systems use personal data, and how decisions are reached. This is designed to foster trust in AI technologies by ensuring that people understand the role of AI in decision-making processes. In addition, this transparency helps to mitigate the risks of opaque decision-making, where individuals may not fully understand why or how an AI system reached a particular conclusion.
Enhanced Accountability
The new regulations also place a strong emphasis on accountability. Organisations that use high-risk AI systems must implement robust risk management processes that cover how personal data is processed, stored, and protected. These risk management processes are designed to ensure that organisations take proactive steps to prevent data breaches, misuse, or accidental exposure of personal data.
In the event of improper data handling, the consequences can be severe. Under both the AI Act and the GDPR, organisations can face substantial fines and penalties for failing to adequately protect personal data. This serves as a powerful incentive for organisations to prioritise data privacy in their AI deployments and to adopt comprehensive safeguards to prevent data breaches.
Regular Audits of AI Systems
To further ensure compliance with the new regulations, high-risk AI systems are required to undergo regular audits. These audits are intended to assess how personal data is handled throughout the lifecycle of an AI system, from initial data collection to final decision-making.
Audits also play a critical role in ensuring that organisations are maintaining detailed records of their data processing activities. This includes tracking how consent is managed, how long data is retained, and what protective measures are in place to prevent data breaches. In the event of an audit, organisations must be able to demonstrate that they have taken all necessary steps to comply with data privacy regulations.
This focus on regular audits is particularly important in industries such as finance and healthcare, where the handling of personal data is both highly sensitive and highly regulated. By requiring organisations to keep detailed records and conduct regular reviews, the new regulations help to ensure that personal data is treated with the utmost care and responsibility.
Impact on Profiling and Automated Decision-Making
Profiling and automated decision-making are two areas where AI is having a particularly significant impact, and the new EU regulations have introduced specific measures to protect individuals in these contexts. Profiling involves using personal data to assess certain aspects of an individual’s behaviour, performance, or characteristics, while automated decision-making refers to decisions made solely by an AI system, without human intervention.
The new regulations require that AI systems involved in profiling or automated decision-making—particularly in high-stakes areas like finance, healthcare, and employment—must comply with strict privacy standards. Under GDPR, individuals are protected from being subject to decisions based solely on automated processing, including profiling, if those decisions have legal or similarly significant effects on them.
For example, an AI system used by a bank to determine creditworthiness must ensure that its decisions are not based solely on automated profiling, and that individuals have the opportunity to contest or appeal decisions made by the AI system. This is a crucial safeguard to prevent discrimination and to ensure that individuals are not unfairly disadvantaged by AI-driven decisions.
Responsibility for Third-Party Data
Many AI systems rely on third-party data to function effectively. For example, AI systems used in marketing, finance, or healthcare may incorporate data from external sources to enhance their decision-making capabilities. However, this reliance on third-party data introduces additional risks to data privacy, as organisations must ensure that any external datasets they use comply with privacy regulations.
The new EU AI regulations place collective responsibility on all parties involved in the use of third-party data. This means that organisations cannot simply rely on the assurances of their data providers; they must take proactive steps to verify that the data they are using has been legally sourced and that any personal data has been anonymised or pseudonymised as necessary.
This requirement for due diligence is particularly important in industries where third-party data plays a significant role, such as digital marketing or financial services. By ensuring that all data sources comply with privacy standards, organisations can reduce the risk of privacy breaches and build greater trust with their customers.
Conclusion: UK Organisational Response to the EU AI Act
UK organisations must act swiftly to ensure compliance with the EU AI Act’s requirements. Although many of the obligations, particularly for high-risk AI systems, will come into effect in 24 months, some provisions will take effect earlier.. For example, prohibitions on certain AI systems will be enforced by the end of 2024, while requirements for general-purpose AI will apply from mid-2025. So what do you need to do?
Evaluate Compliance Impact
Begin by assessing how the AI Act (AIA) affects your current compliance frameworks, especially for cross-border functions. This is crucial for firms operating across different regulatory environments.
Classify AI Systems
Categorise your AI systems based on the risk levels defined in the Act. Develop and maintain a dynamic inventory of AI assets, following the EU’s taxonomy. This inventory will help manage compliance and ensure that all systems are accurately classified.
Identify Prohibited AI Systems
Take immediate steps to identify AI systems that will be prohibited by the end of 2024. Ensure that these are either modified or phased out to avoid regulatory breaches.
Update AI Governance Model
Review and update your existing governance frameworks to ensure alignment with the AIA. This should include defining roles and responsibilities for managing AI systems and ensuring ongoing compliance.
Strengthen Risk Management Framework
Develop and implement a robust risk management strategy, incorporating comprehensive testing and validation procedures for AI systems. This will ensure that risks are mitigated effectively, particularly for high-risk AI applications.
Enhance Data Governance
Ensure that your organisation’s data management practices are rigorous and align with the requirements of the AIA. This includes maintaining accurate, reliable, and bias-free datasets to support AI development and deployment.
Implement Adequate Controls
Review and confirm that appropriate controls are in place, particularly for advanced AI systems. These controls should cover areas like data security, system performance, and compliance monitoring.
Map Interdependencies
Understand the internal and external dependencies associated with your AI systems. Establish strong partnerships with cloud providers and third-party platforms to ensure aligned responsibilities and the implementation of necessary safeguards.
While the AI Act introduces new compliance challenges, it also offers UK firms an opportunity to align AI development with strategic goals. Addressing these challenges proactively can enhance innovation, promote ethical AI practices and strengthen an organisation’s competitive advantage globally.
Need help?
Want to know more about what you can do to ensure your AI initiatives are ethical and operate an enhanced trust model? Or looking to improve your enterprise trust, privacy and security, reach out here.