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AI Data Processing Compliance

Can I use customer data to train my AI?

Generally, no, unless you have explicit consent or legitimate interest, and the data is anonymized. Repurposing data without notice is a violation.

What is Privacy by Design in AI?

It means embedding privacy protections (like data minimization and encryption) into the AI system's architecture during the development phase, not as an afterthought.

Is DPIA mandatory for AI projects?

Yes, for any processing likely to result in a high risk to rights and freedoms (e.g., systematic monitoring, sensitive data), a DPIA is required by law.

How to handle the "Right to be Forgotten" in AI?

This is challenging. Strategies include retraining the model without the specific data or using "machine unlearning" techniques to remove the data's influence.

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AI Data Processing Compliance is a critical service, as AI models "feed" on data, often personal data. When a company uses AI to analyze client data, train a chatbot, or recognize faces, it is obligated to adhere to the strict requirements of the "Law on Personal Data Protection" of Georgia. Data processing by AI entails specific risks: data leaks, "black box" opacity, and purpose limitation violations (e.g., using marketing data for credit scoring). Violating the law leads to severe fines and reputational damage.

Our service ensures your AI systems are fully compliant with data protection standards. The service includes:

  • DPIA (Data Protection Impact Assessment): A mandatory procedure for high-risk processing. Risks are assessed, and mitigation measures are planned.
  • Privacy by Design: Building system architecture to ensure confidentiality from the start (e.g., data minimization, anonymization).
  • Anonymization and Pseudonymization: Implementing technical methods to ensure specific individuals cannot be identified during AI model training.
  • Transparency Notices: Explaining to users in plain language how AI processes their data and for what purpose.
  • Data Subject Rights: Creating mechanisms for users to request the deletion ("right to be forgotten") or correction of their data from the AI system.

Let's consider risks. A clinic uses AI to analyze patient diagnoses. If data is not properly anonymized and a leak occurs, this is a violation of special category data. Second example: A fintech company uses AI for transaction monitoring. The system collects more data than necessary (violation of Data Minimization principle). Third case: A user requests deletion of chatbot history, but the company technically cannot remove specific data from the trained model (Model Unlearning problem). This is a violation of the law.

In Georgia, this field is regulated by the Law on Personal Data Protection. The law states that automated processing, including profiling, requires special protection. Recommendations from the Personal Data Protection Service and international standards (GDPR), which Georgia follows, are also important.

As part of the audit, specialists check Data Mapping: where data comes from, where it is processed, and where it is stored. A "Record of Processing Activities" is developed, and security protocols are implemented. Special attention is paid to "Machine Unlearning" strategy—how the model should "forget" specific data upon request.

Legal.ge is the platform where you will find Data Protection Officers (DPOs) and technology lawyers. The power of AI lies in data, but data is a responsibility. Ensure your innovation does not infringe on others' privacy.

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