Using AI Responsibly
15 min read
AI tools offer powerful capabilities. But they also create new responsibilities around privacy, transparency, and accountability. Understanding these obligations helps you use AI appropriately in government work.
What are the privacy implications of using AI?
When you use AI tools, you typically send data to external systems. This data gets processed, and in some cases, may be used to train or improve the AI.
This creates immediate concerns for government work. Policy drafts, internal discussions, and consultation responses are often confidential. Sending them to external AI systems may breach confidentiality obligations. Information about citizens, service users, or employees is protected by data protection law. Processing this data through AI tools may require specific legal grounds and safeguards.
Security-related content, commercial information, or anything covered by official secrets legislation requires careful handling. Information shared by other organisations, stakeholders, or partners may also come with restrictions on how it can be used or shared.
How can you protect privacy when using AI?
Different AI tools have different data policies. Some retain data to improve their systems. Others offer enterprise versions with stricter privacy protections. You need to understand what happens to data you input.
Before using AI tools, strip out names, addresses, case references, or other identifiers. Work with anonymised or synthetic examples where possible. Many government organisations have specific guidance on approved AI tools and what data can be processed through them. Follow these policies.
On-premise deployment provides enterprise-level security and keeps data within your organisation's infrastructure. This is often necessary for sensitive work. Whatever approach you take, keep records of what tools you used, what data you processed, and why you determined this was appropriate.
Who is accountable for AI outputs?
When you use AI-generated content in your work, accountability doesn't transfer to the AI system. It remains with you.
If you use AI-generated text in a briefing, policy document, or public communication, you're responsible for its accuracy and appropriateness. Factual claims, legal interpretations, and statistical information all require verification against authoritative sources.
If challenged on a decision informed by AI analysis, you need to explain your reasoning. "The AI said so" isn't sufficient. Content you publish must meet your organisation's quality standards, regardless of how it was produced.
How do you maintain accountability?
Record what you asked the AI, what it provided, how you reviewed the output, and what changes you made. Treat AI outputs as drafts or inputs, not finished work. Your expertise and judgment shape the final product.
If AI assists with significant decisions or public-facing content, ensure proper review and sign-off processes. When appropriate, acknowledge that AI tools contributed to your work. This maintains trust and allows others to apply appropriate scrutiny.
When should you not use AI?
Understanding where AI doesn't belong is as important as knowing where it helps.
AI cannot provide authoritative legal advice or determine how legislation applies to specific circumstances. Decisions about benefits, services, enforcement, or individual rights require human judgment and accountability.
Unless using approved secure systems, don't process sensitive information through AI tools. If you cannot verify AI outputs and accuracy is essential, don't use AI. If you need to explain how you reached a conclusion and can't do this with AI-assisted work, don't use AI.
How do you make ethical decisions about AI use?
Start by considering the stakes. What happens if the AI output is wrong? Who is affected? How serious are the consequences?
Evaluate whether this task could be done another way. Is AI the most appropriate tool? Do you have the time, expertise, and resources to properly check AI outputs?
Think about trust. How would stakeholders react if they knew AI contributed to this work? Does that affect whether you should use it? Would you be comfortable defending this use of AI if questioned? Does it align with your professional obligations?
What principles guide AI use in government?
AI use in the public sector
The UK government has established clear guidance for AI use in the public sector. The AI Playbook for the UK Government sets out ten principles for safe, responsible, and effective use of AI in government organisations.
Principle 1: You know what AI is and what its limitations are
Principle 2: You use AI lawfully, ethically and responsibly
Principle 3: You know how to use AI securely
Principle 4: You have meaningful human control at the right stage
Principle 5: You understand how to manage the AI life cycle
Principle 6: You use the right tool for the job
Principle 7: You are open and collaborative
Principle 8: You work with commercial colleagues from the start
Principle 9: You have the skills and expertise needed to implement and use AI
Principle 10: You use these principles alongside your organisation’s policies and have the right assurance in place
Regulatory Principles
For regulators and those developing AI systems, the government's pro-innovation approach to AI regulation sets out five additional principles:
Principle 1: Safety, security and robustness
Principle 2: Appropriate transparency and explainability
Principle 3: Fairness
Principle 4: Accountability and governance
Principle 5: Contestability and redress
Whether you're using existing AI tools or developing new systems, these frameworks provide clear guidance. They aren't abstract ideals. They're practical requirements for working responsibly with AI in government.
These principles work together. Understanding AI's limitations helps you determine where human control is needed. Working securely and lawfully protects the data you process. Transparency and accountability reinforce each other. Each principle strengthens the others.
What does responsible AI use look like?
Responsible AI use isn't about avoiding these tools entirely. It's about deploying them appropriately.
You might use AI to draft initial versions of routine communications, then review and refine them. To summarise lengthy documents, then verify the summary captures key points accurately. To generate options for consideration, then apply your judgment to select and develop the best approach.
You wouldn't use AI to make decisions about individual cases without human review. To process confidential information without appropriate safeguards. To generate final versions of legal advice or policy interpretation.
The distinction matters. AI augments your work when used appropriately. It creates risks when used beyond its appropriate scope.
Your professional judgment determines where that line sits. These principles help you draw it clearly.