Undoubtedly, using Artificial Intelligence (AI) in business processes brings exciting opportunities for innovation and efficiency. However, it also comes with important legal and ethical responsibilities. Businesses operating in the European Union (EU) or handling data from EU residents must follow strict rules like the General Data Protection Regulation (GDPR) and the upcoming AI Act. Understanding how to use AI while staying within the law is essential for building trust. It also helps reduce risks, and unlock AI’s full potential.
GDPR and its implications for AI
Primarily, the GDPR provides rules to protect the personal data of people in the EU. It applies to any company handling data of EU residents, no matter where the company is located. The guideline also has important rules for AI, including the need for a valid reason to use data, protecting people’s rights over their data, and special rules for decisions made automatically by AI systems.
According to a report by the European Parliamentary Research Service, GDPR plays a crucial role in building trust by ensuring transparency and accountability in AI systems.
Lawful basis for data processing
Under GDPR, organizations need a valid reason to process personal data, called a “lawful basis”. There are six lawful bases:
- consent
- contract performance
- legal obligation
- vital interests
- public interest
- legitimate interests
Because AI systems often rely on large datasets containing personal data, choosing the right lawful basis is essential. For AI, the most common bases are consent and legitimate interests. Consent must be clear, informed, and freely given. Legitimate interests involve balancing the needs of the organization with the rights and privacy of individuals.
Automated decision-making and profiling
Article 22 of the GDPR gives individuals the right to avoid decisions made only by automated systems, such as profiling. This right applies if these decisions have legal effects or significantly impact them. For instance, this rule is especially important for AI systems that automate decision-making. Companies must explain how these systems work, why they are used, and what potential impact on individuals.
Best practices for AI compliance with GDPR
To address these challenges, companies should adopt a strategic approach to use AI and stay in compliance with GDPR.
Data minimization and purpose limitation
AI systems should process only necessary personal data and ensure it’s used solely for specific, legitimate purposes. This requires clearly defining the goals of data processing and regularly reviewing activities to avoid unnecessary data use or “data creep.”
Additionally, consentless data tracking is a way to collect, store, and process users’ data without their consent. Learn more about privacy-friendly data collection technique.
Data Protection Impact Assessments (DPIAs)
When using AI systems for high-risk data processing, conducting DPIAs is essential. DPIAs help identify risks to individuals’ rights and freedoms and ensure that proper safeguards are in place.
Transparency and accountability
Companies must clearly explain how AI systems process personal data, including details about data collection, usage, and sharing. Organizations should also establish accountability measures, like appointing a Data Protection Officer (DPO) and keeping detailed records of data activities.
Having a consent management platform is essential to ensure transparency and compliance with GDPR. Read to learn how to choose one.
Regular audits and monitoring
Frequent audits and monitoring of AI systems ensure they stay compliant with GDPR. This involves reviewing data practices, checking the effectiveness of safeguards, and updating policies and procedures as needed.
PPC and digital marketing use cases impacted by GDPR
AI-powered audience targeting
Example: AI tools like Google Ads’ Smart Bidding use personal data (e.g., search history, location) to optimize ad delivery.
Compliance Requirement: Get user consent for data collection through cookies or tracking pixels. Clearly explain how data is used and provide an opt-out option.
To learn more about how Chrome’s third-party cookie restrictions impact data collection and compliance efforts, read this detailed guide. Besides, using tools like Walker.js can help businesses efficiently gather first-party data while complying with GDPR.
Predictive analytics for ad campaigns
Example: AI predicts campaign success using historical data, including identifiable customer information like purchase patterns.
Compliance Requirement: Aggregate or anonymize data used for training AI models. Be transparent about how predictions are generated.
Chatbots and conversational AI in lead generation
Example: AI chatbots gather visitor data (e.g., names, email addresses, browsing history) to qualify leads for retargeting.
Compliance Requirement: Collect only essential data. Clearly disclose data usage and obtain consent before storing information.
Ad copy personalization
Example: Generative AI creates personalized ad content based on user behavior or past interactions.
Compliance Requirement: Follow GDPR rules by limiting how long data is kept and ensuring users can withdraw their consent.
Checklist for AI Privacy Compliance
What to expect
The European Union’s AI Act creates rules based on how risky an AI system is. The Regulatory Framework defines four levels of risk for AI systems: minimal, limited, high, and unacceptable. These rules make sure AI is used responsibly, especially in areas where it could seriously affect people’s lives.
AI systems used in important areas like healthcare, law enforcement, education, or critical infrastructure are considered high-risk because they can greatly affect people’s lives. These systems must follow strict rules, including:
- Comprehensive risk assessments
Companies must carefully check for risks that their AI systems might cause. This includes looking for issues like discrimination, privacy problems, or safety risks and finding ways to fix them. - Transparency in decision-making
High-risk AI systems need to explain how they make decisions. This means showing how the algorithms work, where the data comes from, and how the decisions could affect people. - Human oversight
Moreover, these systems must allow humans to step in and take control when needed. This helps prevent harm or bias and ensures that important decisions are not made entirely by machines.
Penalties for non-compliance
If companies fail to follow the AI Act, they can face serious penalties. These penalties are much higher than those under GDPR, showing how serious the EU is about promoting ethical and responsible use of AI. According to Article 99:
Prohibited AI practices: Engaging in AI practices explicitly banned under the AI Act can result in fines up to €35 million or 7% of the company’s total worldwide annual turnover for the preceding financial year, whichever is higher.
Non-Compliance with Obligations: Failing to meet specific obligations outlined in the AI Act, such as those related to high-risk AI systems, may lead to fines up to €15 million or 3% of the total worldwide annual turnover, whichever is higher.
Providing Incorrect or Misleading Information: Supplying false, incomplete, or misleading information to notified bodies or national competent authorities can incur fines up to €7.5 million or 1% of the total worldwide annual turnover, whichever is higher.
If your company collects users’ personal data, you should start preparing by:
- setting up strong systems to manage risks and take responsibility.
- making sure their AI tools are easy to understand and explain.
- regularly checking AI models to find and fix any biases.
- training employees on ethical AI practices and compliance rules.
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FAQ
What is the relationship between GDPR and the AI Act?
While GDPR focuses on data protection, the AI Act addresses broader AI risks, including ethical considerations and safety. Both regulations aim to foster trust and transparency in AI technologies.
Is ChatGPT GDPR-compliant?
OpenAI claims compliance with GDPR by implementing measures to protect data privacy. However, businesses using ChatGPT should perform their due diligence, such as reviewing OpenAI’s data processing practices and conducting DPIAs.
What are CNIL's recommendations for developing AI in compliance with GDPR?
CNIL emphasizes transparency, purpose limitation, and conducting DPIAs. It also recommends specific measures like training data ablation techniques and engaging ethics committees.
What is the purpose of GDPR in Generative AI?
GDPR ensures that generative AI systems process data lawfully and ethically, safeguarding individual rights while promoting trust in AI-driven innovations.
What are the compliance risks of using Google Analytics 4 in the EU?
Google Analytics 4 (GA4) presents compliance challenges in the EU due to strict GDPR rules around data transfer and storage. Businesses must ensure that GA4 configurations meet data protection standards, such as anonymizing IP addresses and limiting data retention periods. Learn more about the risks and potentials of GA4 in Europe.
What is the relationship between the GDPR and the AI Act?
The General Data Protection Regulation (GDPR) and the EU Artificial Intelligence Act (AI Act) are two important rules in Europe for AI. The GDPR protects personal data and privacy, while the AI Act ensures AI is safe and used responsibly. These two laws overlap when AI systems handle personal data, meaning companies must follow both. For example, the AI Act focuses on managing data and being open about how it’s used, which works well with the GDPR’s rules for protecting data and being accountable.
How can AI help in regulatory compliance?
Artificial Intelligence can help follow laws and rules by keeping track of changes automatically. It can process a lot of data quickly to find problems, make reports easier, and reduce mistakes. For example, AI can check for updates to laws and match them to a company’s policies, making sure everything stays on track.
How to use AI and personal data appropriately and lawfully
To use AI and personal data properly and legally, organizations must follow rules like being fair, clear, and only using data for specific purposes. They should have a legal reason to use the data, check for risks, and explain to people how their data is used. It’s also important to manage data carefully and keep humans in control of AI systems to follow data protection laws.
What is a critical component found in both the GDPR and the EU AI Act?
Both the GDPR and the EU AI Act focus on transparency. They require organizations to be clear about how they use data and how their AI systems work. This means giving people easy-to-understand information about their data and making sure AI systems are explainable. Being transparent builds trust and keeps companies accountable.
