AI and data privacy: Balancing innovation and protection

As businesses of all sizes race to adopt AI, both in their customer facing and back-office functions, it’s important we stop to think about data protection considerations and compliance obligations.

AI and data privacy: Balancing innovation and protection

As businesses of all sizes race to adopt AI, both in their customer facing and back-office functions, it’s important we stop to think about data protection considerations and compliance obligations. These requirements need not be a barrier to innovation and improvement, but it’s vital they are considered as we adopt this new technology.

Like most jurisdictions, the UK has little legislation around data protection specific to the use of AI. This means we’re left without a clear checklist for implementation. Instead, we need to rely on an ever-evolving interpretation of existing laws and regulations.

Privacy policy & data processors

In the context of AI adoption, it’s crucial to ensure that your privacy policies are updated to reflect your use of AI. Regular audits of your privacy policy are paramount, ensuring users are correctly notified of how AI providers may process their data and where their data is sent. During these audits, it’s important to communicate transparently how user data will be processed in the context of AI, fostering trust and compliance.

When collaborating with new data processors, particularly AI companies, swift updates to your privacy policy are essential. Whether it’s for natural language processing, machine learning, or other AI-driven functionalities, your privacy policy should be promptly revised to reflect these collaborations. It’s key to outline the specific AI applications involved and the purpose of data usage, reinforcing your commitment to user privacy.

AI collaborations often transcend borders, making it crucial to be mindful of international data transfer regulations. It’s important to thoroughly assess the data handling practices of AI companies located outside the UK, ensuring they adhere to GDPR standards.

In communicating these changes, it’s important to prioritize user-friendly language to make the updates accessible to your audience. Emphasize the benefits and safeguards implemented to maintain transparency and user trust. By incorporating these proactive measures, your privacy policy becomes more than a legal necessity – it becomes a opportunity to show customers your commitment to responsible and compliant AI practices, safeguarding both user privacy and trust in your business.

Automated decision making

Automated decision-making is a key use case of AI that can significantly impact individuals. Under the General Data Protection Regulation (GDPR), individuals have the right not to be subject to a decision based solely on automated processing, including profiling, which produces legal effects concerning them or similarly significantly affects them. This means that if an AI system makes a decision that has a significant impact on an individual, such as denying them a loan or a job, the individual has the right to challenge this decision and request human intervention.

Therefore, businesses must ensure that they have appropriate measures in place to safeguard individuals’ rights and freedoms and legitimate interests when implementing AI systems that involve automated decision-making. This could include providing individuals with the option to opt-out of automated decision-making, implementing robust mechanisms for individuals to challenge decisions made by AI, and ensuring that there is always a human in the loop who can review and override decisions made by AI.

Data minimization and purpose limitation

The principles of data minimization and purpose limitation are fundamental to GDPR. Data minimization requires that personal data collected should be adequate, relevant, and limited to what is necessary for the purposes for which they are processed. This means that businesses should only collect the personal data that they actually need to provide their services or carry out their activities, and they should not retain this data for longer than necessary.

Purpose limitation mandates that personal data should be collected for specified, explicit, and legitimate purposes and not further processed in a manner incompatible with those purposes. This means that businesses should clearly define the purposes for which they are collecting personal data at the time of collection, and they should not use this data for other purposes without the individual’s consent.

These principles should guide the design and implementation of AI systems, ensuring that only necessary data is collected and used for legitimate purposes, and that individuals are informed about how their data will be used.

Transparency and customer understanding

Transparency and understanding are crucial when using AI systems. Individuals have the right to be informed about the processing of their personal data, the logic involved in automated decision-making, and the significance and consequences of such processing. This means that businesses should strive to make their AI systems as transparent and explainable as possible, providing clear and understandable information about how personal data is used, how decisions are made, and how to challenge decisions made by AI.

This could involve providing individuals with detailed information about the algorithms used by the AI system, the data that the system uses to make decisions, and the reasoning behind these decisions. Businesses should also provide individuals with clear instructions on how to challenge decisions made by AI and how to request human intervention.

Data security and accountability of AI providers

Data security is paramount in the use of AI. Businesses must implement appropriate technical and organizational measures to ensure a level of security appropriate to the risk. This could include the pseudonymization and encryption of personal data, the ability to ensure the ongoing confidentiality, integrity, availability, and resilience of processing systems and services, and the ability to restore the availability and access to personal data in a timely manner in the event of a physical or technical incident.

Furthermore, businesses must ensure that AI providers are accountable for their systems. This includes ensuring that providers comply with data protection laws, that they can demonstrate compliance, and that they are responsible for any data breaches or non-compliance with data protection laws. This accountability extends to all aspects of the AI lifecycle, from design and development to deployment and use. Businesses should carefully vet AI providers to ensure that they have robust data protection measures in place and that they are committed to maintaining the security and privacy of personal data.

As we forge ahead with the integration of AI, vigilance in data protection and compliance remains paramount. The lack of specific AI-related legislation does not exempt us from interpreting and applying existing laws like the GDPR.

As lawyers that specialise in emerging technology, we recognise how challenging it can be to keep up with the latest requirements. A lack of clear-cut regulations shouldn’t stop you from proactively protecting yourself and your customers. We take a futuristic approach in how we protect companies and its founders by anticipating eventualities and laws that may or may not quite exist at this stage. The founders & companies we work with are confident in their ability to scale using a variety of novel technology while knowing the have strong legal foundations in place. Ultimately, the journey towards AI integration is not solely about technological innovation, but also about building trust and ensuring the ethical use of data.

Karen Holden
Karen Holden

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