The Data Privacy Challenges of AI
The data privacy issues associated with AI are well-documented. These include:
- Bias and Discrimination: AI models can inadvertently perpetuate biases present in the data they are trained on, leading to discriminatory outcomes.
- Data Minimisation: Organisations must ensure they collect only the necessary data for AI applications, adhering to principles of data minimisation.
- Compliance Throughout the AI Lifecycle: From data collection to model deployment, it’s crucial to manage data compliantly at every stage of the AI lifecycle.
- Explainability and Accuracy: AI systems often operate as “black boxes,” making it difficult to explain their decisions. Ensuring AI models are both accurate and explainable is vital for maintaining trust and meeting regulatory requirements.
The Importance of Addressing AI’s Legal and Practical Challenges
For businesses, addressing the legal and practical challenges posed by AI is not just about compliance—it makes good business sense. In the UK, the Information Commissioner’s Office (ICO) has published guidance on AI, but these guidelines must be interpreted and applied to each organisation’s specific use cases. This is where privacy professionals, such as Data Protection Officers (DPOs), play a crucial role.
Role of Privacy Professionals in AI Governance
Privacy professionals are uniquely positioned to help organisations navigate the complexities of AI. They are well-versed in compliance principles, policies, and processes, and their experience with GDPR and other regulations is highly relevant when it comes to managing the data privacy risks associated with AI.
By leveraging existing compliance frameworks, DPOs can support the deployment and use of AI in ways that align with business objectives without becoming a roadblock to innovation. However, DPOs alone cannot address all the challenges posed by AI. Effective AI governance requires collaboration across various functions within the organization.
The Need for Cross-Functional Collaboration
To successfully integrate AI into business operations while managing risks, organisations must adopt a cross-team approach. Privacy professionals should work closely with legal, IT, compliance, and marketing teams to ensure that AI initiatives are thoroughly vetted and aligned with the organisation’s risk appetite.
This collaborative approach was echoed by the ICO in its response to ChatGPT in April 2023, where it emphasised the need for privacy teams to work alongside technical specialists to tackle the data security risks posed by genAI.
Getting to Grips with AI Governance
All organisations that use AI will need to develop robust AI governance frameworks. Here are some top tips to get started:
- Set Up Collaborative Cross-Functional Working Groups on AI: Establish teams that bring together different expertise to address AI-related challenges holistically.
- Create an AI Governance Framework: Develop a structured approach to managing AI risks and ensuring compliance across the organisation.
- Consider Supplier Onboarding Questionnaires: Use these to assess how suppliers’ use of AI might impact your business and to ensure they meet your AI governance standards.
- Conduct Data Protection Impact Assessments (DPIAs): Use DPIAs to identify and mitigate the risks associated with AI usage.
- Produce an AI Inventory: Maintain a comprehensive overview of all AI tools and systems currently in use within the organisation.
- Establish Risk Thresholds: Determine acceptable risk levels for AI applications, drawing inspiration from frameworks like the EU AI Act.
- Expand Data Protection Policies: Adapt existing data protection policies, processes, and documentation to address the specific challenges of AI.
- Amend Privacy Notices: Update privacy notices to transparently communicate how, when, and why AI is used, especially when it processes personal data.
Conclusion
As AI continues to shape the future of business, organisations must proactively address the data privacy and governance challenges it presents. By setting up robust AI governance frameworks and fostering cross-functional collaboration, businesses can harness the power of AI while safeguarding their reputation, maintaining customer trust, and ensuring compliance with regulatory requirements.
Getting AI governance right is not just a strategic advantage—it’s essential for long-term success.
Written by Robert Wassall
Robert Wassall is a solicitor, expert in data protection law and practice and a Data Protection Officer. As Head of Legal Services at NormCyber Robert heads up its Data Protection as a Service (DPaaS) solution and advises organisations across a variety of industries. Robert and his team support them in all matters relating to data protection and its role in fostering trusted, sustainable relationships with their clients, partners and stakeholders.
