AI Ethics for Researchers and Evaluators

Artificial intelligence is evolving rapidly. New tools, updates and capabilities appear almost daily, and for researchers and evaluators, it can feel difficult to keep up.

AI Ethics - Why it matters

Many conversations about AI focus on productivity or innovation. But one of the most important discussions is about ethics. I deliberately say AI ethics rather than ethical AI, because the technology itself is not ethical. What matters is how we choose to use it.

Researchers and evaluators are well placed to contribute to these discussions. Our work already involves thinking carefully about evidence, bias, transparency and accountability.

In this article, I explore why conversations about AI ethics matter for researchers and evaluators, and how existing research principles can help guide responsible use.

Applying Existing Ethics Frameworks

Rather than treating AI as something entirely new, it can be helpful to start with the frameworks we already use.

Research and evaluation practice is built around principles such as:

• integrity

• transparency

• consent

• confidentiality

• accountability

When we apply these principles to AI use, the conversation becomes clearer. Instead of asking whether AI is good or bad, we can ask more practical questions.

For example:

• Should AI be used for this task?

• What are the risks to data privacy?

• How will outputs be checked and verified?

• What level of human oversight is needed?

These are familiar questions for researchers and evaluators.

AI Tools and Data Governance

Another area that deserves attention is data governance.

Many organisations encourage staff to use AI tools but have not fully explored how data is processed once it enters those systems.

Even within platforms such as Microsoft Copilot, different AI models may introduce different data handling arrangements. Organisations need to understand where their data is going and what contractual terms apply.

Checking privacy settings and reviewing policies may not be the most exciting task, but it is an important one.

The Role of Researchers and Evaluators

Researchers and evaluators bring valuable expertise to AI conversations. We are used to thinking critically about evidence and methodology, and those skills are increasingly relevant in the AI era.

Rather than stepping back from the debate, our sector can help shape responsible approaches to AI use.

Exploring AI & AI Ethics in Research and Evaluation

If you are thinking about how AI might support research or evaluation work, my AI training workshops explore practical and responsible ways to use these tools.

Takeaway: AI is most valuable when it supports human judgement rather than replacing it.

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