Do:
Clearly indicate where and how you have used AI tools in your work (see below).
Verify AI-generated information using reliable resources or tools, such as NELSON.
Familiarise yourself with how AI tools function to understand their strengths and limitations.
Follow the University guidance and your assignment guidelines on AI use.
Remember that university study is about developing your own knowledge and skills.
Don’t:
Submit AI-generated work as your own—this constitutes academic misconduct under the University policy.
Don’t upload personal data, research data, copyrighted materials (journal articles), or University intellectual property (e.g., lecture slides) to the AI tool.
Upload your own materials unless you are fully aware of how the AI tool may use them.
Note: you do not reference the AI tools you have used, only genuine sources that you have found through using them. In your work, you should include an acknowledgement of any AI tools you have used, where you have used them and a description of how you have used them.
The university has guidance on good academic practice. If you haven’t already, it’s worth going through the University of Northampton Plagiarism Avoidance Course. It is your responsibility to understand the guidance in the use of GenAI and AI tools in academic assignments.
As AI tools become more integrated into academic research, it is essential to consider the ethical implications of their use. While these technologies can enhance efficiency and discovery, researchers must remain critical and responsible in how they engage with AI-generated content.
Key ethical concerns include:
Academic Integrity: AI tools can assist with research, but they should not be used in ways that compromise originality, critical thinking, or proper attribution of sources. Always verify AI-generated outputs against primary literature.
Data Privacy & Security: Many AI-powered research tools require sign-ups and may collect or store user data. Be mindful of personal and institutional privacy policies before uploading materials or entering queries. Please refer to our Data protection page.
Transparency & Bias: AI models are trained on specific datasets, which means their recommendations may reflect inherent biases or exclude important perspectives. Researchers should cross-check results against multiple sources.
Access & Equity: Some AI-enhanced tools are behind paywalls or offer limited free access, which can create barriers for researchers without institutional funding. Open-access alternatives should be considered when possible.
By using AI responsibly—understanding its strengths, limitations, and ethical implications—researchers can harness its benefits while maintaining academic rigor and integrity.
While artificial intelligence has enormous potential for monitoring and tracking climate change activity around the world, there are environmental challenges to be aware of.
The main challenge is the scale of resources that are needed to power AI. Using Large Language Models (LLMs), such as ChatGPT, or image-producing AI versions require a vast amount of energy, and they emit more carbon emissions than your standard internet search tools. The amount of water needed to cool the giant servers of AI machines is also a concern where climate change is potentially leading to future shortages. In terms of the hardware, AI is built using rare materials that often need to be mined, which also carries environmental risks.
Unless AI developers are completely transparent about their environmental impacts, we can only be mindful of these issues when we use AI. Always think critically about how you use AI tools and use them responsibly. To minimise your own environmental impact, you may feel more comfortable using AI assistants within existing databases, like the ones mentioned within this guide. Where possible, opt for small language models or AI tools that are underpinned with an environmental sustainability plan.
Read more: McDonald, C. (2025)
In general, where an AI tool is being used to find literature, then it can be used without acknowledgment or a citation (in much the same way as a library catalogue or a search engine like Google Scholar). However, you should always check and follow your assessment brief and your tutor's guidance.
For any other use of these tools, follow university guidance on acknowledging the use of AI in your work.
When signing up and using AI tools it’s important to consider what data you’re entering into the tool and how this data will be used. When we talk about data – we're thinking about your personal information, email address as well as data belonging to others.
It’s best to assume that anything you put into an AI or GenAI tool will be used by the company to improve their product (to train the AI) and share with others.
On our University website we advise that the following should not be submitted to a GenAI tool: confidential data; data belonging to other people or organisations, i.e. the intellectual property of other people or third-party copyrighted material, unless permission has been granted or is licensed; your own personal data, unless you are prepared for it to surface in GenAI output.
Protect your personal data by not giving it to the tool. For example, if you upload any of part of your CV you are giving all of that information to the tool for it to be re-used in someone else’s prompt result.
Create a separate email account just for the purpose of using the AI tools.
Don’t upload any research data to AI tools, your research data is subject to ethical approval and your participants may not have agreed to have their information shared in that way. Please see The Use of AI in Academic Work
Have a look at the privacy settings – do they tell you how they use your data and how long they will store it for? If it’s not clear, don’t use it.