There’s no doubt artificial intelligence (AI) brings exciting potential to any organisation. But it’s all about balance.
AI presents a huge opportunity for organisations to re-design their operations. As it becomes increasingly integrated into their business, they face the challenge of implementing the new AI systems while ensuring compliance with existing regulations and ethical standards.
But rather than thinking of effective AI governance as just a regulatory hurdle, we see it as a catalyst for innovation. By building trust, ensuring ethical development, mitigating risks, sharing results and raising awareness of the opportunities, good governance provides a solid foundation from which to grasp the benefits it offers us all.
The UK has adopted a principles-based approach to AI regulation, avoiding blanket statutory requirements that might stand in the way of innovation.
The framework relies on existing legislation such as GDPR. It also follows guidance from regulators like the National Cyber Security Centre (NCSC) and the UK’s AI regulatory principles outlined in the Government’s AI white paper. A UK AI Bill is expected to be published soon.
International standards like ISO 42001 and ISO 42006 also provide valuable frameworks for AI governance. This approach allows AI development to flourish. But it also means maintaining appropriate oversight through sector-specific regulators who enforce guidelines based on established consumer protection and market legislation.
AI governance and oversight – what to consider
Policies and procedures
Effective AI governance begins with robust policy documentation – and this must align with regulatory expectations. Organisations need clear procedures covering data protection and cybersecurity, and continuous monitoring processes.
This includes governance arrangements for effective oversight and risk management that identify both potential risks and benefits of AI implementation. Feedback mechanisms are expected too, so that users can contribute to the continuous improvement of AI systems.
Transparency and accountability
Organisations mustcommunicate clearly about use of AI strategy, explain how data is used, which algorithms are involved, and the purpose of AI operations.
Regular reporting on AI use, data processing practices, and adherence to ethical guidelines, demonstrates accountability and builds trust with stakeholders.
Protecting end user rights
For organisations whose AI systems impact individuals, the priority should be to protect their rights. This means establishing a sound legal basis for data processing. It’s also important to comply with GDPR principles such as access to personal data, rectification of inaccuracies, data erasure, and data portability.
Particularly critical are the need for informed consent and the right to explanation, ensuring users understand the logic and consequences of automated decision-making (where applicable).
Information security
The technical foundation of AI governance includes robust access management controls to prevent unauthorised access and data poisoning attacks. Two requirements are having a specific incident response plan to deal with AI-related breaches and comprehensive third-party management for any outsourced AI services.
When it comes to project management, ‘privacy by design’ principles and data impact assessments should also incorporate the impact of AI on any new or ongoing projects.
User education and awareness
Building AI literacy among users is crucial for successful governance. This means understanding AI technologies, their potential risks and benefits, policy awareness, and recognition of potential bias in AI systems.
Be responsible
Effective AI governance requires a comprehensive approach that balances innovation with responsibility. Organisations must regularly assess whether their risk registers adequately reflect AI-related risks. So it’s important that governance frameworks evolve alongside technological developments.
Properly prepared AI governance frameworks allow organisations to benefit from AI while still complying with existing regulations and ethical standards. Only then can they position themselves for success in an AI-driven future while also protecting the interests of all stakeholders.
Please get in touch with Phil Broadbery if you would like to discuss how we can support you with a tailored AI governance programme to suit your organisation.
