Best AI Practices to Comply with GDPR

Best AI Practices to Comply with GDPR

The GDPR is the EU’s law that protects the privacy and the rights of individuals in relation to their personal data. The GDPR also applies to the use of AI systems that process personal data, and sets out specific rules and obligations for the providers and users of such systems (let’s get more information with ours articles: ai and gdpr, ai in data protection law and eu ai act)

 

In this article, we will present some of the best AI practices to comply with the GDPR, based on the guidance and recommendations of the EDPB, the European Commission, and the ICO.

 

 

What does Privacy by Design mean?

Privacy by design is the principle that requires organizations to integrate data protection considerations into the design and development of their products, services and processes, from the earliest stage and throughout their life cycle. Privacy by design is a legal obligation under the GDPR, and it applies to the use of AI systems that process personal data. Privacy by design means that organizations should adopt a proactive and preventive approach to data protection, and implement appropriate technical and organizational measures to ensure that the AI systems comply with the GDPR and protect the rights of the data subjects.

 

 

 

 

Transparent Data Processing

Transparency in AI data processing is the principle that requires organizations to provide clear and accessible information to the data subjects about the processing of their personal data, and to obtain their consent or another lawful basis for the processing.

 

Transparent data processing means that organizations should inform the data subjects about the existence, the purpose, the functioning, and the impact of the AI system, and that they should respect the data subject’s rights and choices regarding the processing of their personal data.

 

 

Data Minimisation and Purpose Limitation

Data minimisation and purpose limitation are the principles that require organizations to collect and process only the personal data that is necessary and relevant for the specific and legitimate purpose of the data processing, and to not use the personal data for other purposes that are incompatible with the original purpose, unless there is a valid legal basis for doing so.

 

Data minimisation and purpose limitation mean that organizations should limit the amount and the scope of the personal data that they collect and process for the purpose of the AI system, and that they should delete or anonymise the personal data when it is no longer needed.

 

 

Data Security

Data security is the principle that requires organizations to ensure the confidentiality, integrity and availability of the personal data that they process, and to protect the personal data from unauthorized or unlawful access, use, modification, disclosure, loss, destruction or damage.

 

Data security (learn more about ai cybersecurity) means that organizations should implement appropriate technical and organizational measures to prevent and mitigate the risks and threats to the personal data and to the data subjects, and to ensure the resilience and the recovery of the data processing in case of a breach or an incident.

 

 

Data Protection Impact Assessment (DPIAs)

A data protection impact assessment (DPIA) is a process that helps organizations to identify and assess the potential risks and impacts of the data processing on the rights and freedoms of the data subjects, and to implement measures to mitigate or eliminate those risks and impacts. A DPIA is a legal obligation under the GDPR, and it is required for the use of AI systems that process personal data that are likely to result in a high risk to the data subjects, such as AI systems that involve large-scale or systematic processing of sensitive data, automated decision-making, profiling, biometric identification, or surveillance. A DPIA should be conducted before deploying an AI system, and should be reviewed and updated regularly.

 

 

AI in Consent Management

Consent management is the process that helps organizations to obtain and manage the consent of the data subjects for the processing of their personal data, in accordance with the GDPR. Consent management is required for the use of AI systems that process personal data that do not have another lawful basis for the processing, such as a contract, a legal obligation, a vital interest, a public interest, or a legitimate interest. Consent management means that organizations should provide the data subjects with clear and meaningful information about the data processing, and that they should obtain their consent in a freely given, specific, informed and unambiguous manner, by a clear affirmative action. Consent management also means that organizations should respect the data subject’s preferences and choices, and that they should allow them to withdraw their consent at any time, without detriment or prejudice.

 

 

Right to Information

Right to information is the right that grants the data subjects the access to clear and meaningful information about the processing of their personal data, and the logic, criteria and consequences of the AI system’s decisions and actions.

 

AI in right to information is a legal obligation under the GDPR, and it applies to the use of AI systems that process personal data. Organizations should provide the data subjects with a privacy notice or a privacy policy, that explains the identity and contact details of the data controller and the data processor, the purpose and the legal basis of the data processing, the categories and the sources of the personal data, the recipients and the transfers of the personal data, the retention period and the deletion policy of the personal data, the rights and the remedies of the data subjects, and the contact details of the data protection officer and the supervisory authority.

 

Right to information also means that organizations should provide the data subjects with a specific AI notice or a AI policy, that explains the existence, the purpose, the functioning, and the impact of the AI system, the data sources and the data quality of the AI system, the performance and the accuracy of the AI system, the limitations and the potential risks of the AI system, the human oversight and intervention mechanisms of the AI system, and the logic, criteria and consequences of the AI system’s decisions and actions.

 

 

Training and Awareness

Training and awareness are the activities that help organizations to educate and inform their staff and their stakeholders about the GDPR and the data protection implications of the use of AI systems that process personal data. Training and awareness are good practices under the GDPR, and they are recommended for the use of AI systems that process personal data.

 

 

Monitoring and Accountability

Monitoring and accountability are the processes that help organizations to ensure the compliance and the performance of the AI systems that process personal data, and to demonstrate the responsibility and the liability of the data controller and the data processor for the data processing. Monitoring and accountability are legal obligations under the GDPR, and they apply to the use of AI systems that process personal data. Monitoring and accountability mean that organizations should implement appropriate mechanisms and procedures to monitor and audit the data processing and the AI system, and to report and notify any incidents or breaches to the supervisory authority and to the data subjects. Monitoring and accountability also mean that organizations should establish and document the roles, the responsibilities and the obligations of the data controller and the data processor, and that they should ensure that they have sufficient resources, expertise and authority to carry out the data processing and the AI system.

 

 

 

 

 

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