A friend of mine recently went to a business conference where the presenter asked who had an AI policy in place. The entire audience admitted they wanted to adopt AI in their business, but no one had a policy or was sure how to start.
The early stages of information security and GDPR share many similarities. They are governed by a comprehensive policy, detailed functional policies, and Standard Operating Procedures (SOPs). Everything begins with a high-level policy that can effectively focus your objectives, offer guidance, and safeguard your business from a variety of significant risks.
Developing an AI policy is helpful & essential for ethical and successful implementation. Having recently been involved with a similar exercise at Correla, here are my thoughts on the main areas you need to cover:
- Define the Purpose and Scope of using AI: Clearly outline your AI goals and specific areas of focus (e.g., customer service, data analysis).
- Establish Strong AI Principles: Align your values with AI ethics. Fairness, transparency, accountability, privacy, and safety should be at the centre of your policy.
- Identify and Mitigate AI Risks: Look for potential challenges such as bias, security threats, and unintended consequences. Implement robust risk management strategies.
- Emphasise Data Governance: AI only works with access to your data. It is critical to tag the nature of your data and who can access it. You don't want to be training ChatGPT or giving away your IPR. Protect your sensitive information, ensure data quality, and clarify and obtain any necessary consents for data usage (Think GDPR).
- Build and Deploy AI Responsibly: Establish clear guidelines for the development of your AI models, their testing, and their deployment. Consider using pre-trained models or building custom solutions.
- Value for Money: Be very clear about your costs and ROI. Solutions such as Copilots and prebuilt models can be much faster to deliver and more cost effective. It takes a long time to train your own models.
- Embed AI Traceability: Make AI decisions understandable, particularly for high-stakes and critical applications.
- You need Human Oversight: Don’t let AI mark its own homework. Define roles and responsibilities for clear AI oversight. GDPR restricts automatic decision making and segmentation, make sure there is human involvement.
- Define Ethical Boundaries: Clearly show acceptable and unacceptable AI use cases. Support your teams by having experts who can provide friendly advice and support.
- Empower your SMEs and interested employees with tools they can use. They will find the best applications!
- Invest in AI Education: Enable your employees to get the AI knowledge they need and help them understand your ethical guidelines through comprehensive training.
- Be Compliant and Adaptable: Stay up to date with evolving regulations and industry standards. Regularly monitor and refine your AI policy.
Like all policies, your AI policy is a living document. Work with the legal, IT, and HR teams to create a robust framework that supports innovation while also safeguarding your reputation.
