Ai Detection Assessment 2025

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This blog post is an update to two previous entries that focused on AI detection tools: _‘ [AI Detection: Latest Recommendation](https://nationalcentreforai.jiscinvolve.org/wp/2023/09/18/ai-detection-latest-recommendations/) s’_ (September 2023) and _‘ [AI Writing Detectors – Concepts and Considerations](http://xn--ai%20writing%20detectors%20%20concepts%20and%20considerations-ie32b/)’_ (March 2023). As we look ahead to the next academic year, this feels like an opportune moment to revisit the topic.

The core concepts and conclusions from those earlier posts still stand, but much has changed. There have been significant advances in AI tools since I last wrote on the subject. We now have more evidence of AI’s capability to complete coursework and on the difficulty humans face in detecting its use. However, there have been no major developments in AI detection technology itself.

This update is partly prompted by the rise of AI assessment scales, traffic-light systems and similar tools. These approaches are undoubtedly helpful in supporting students to understand how AI can be used appropriately. Yet, they also present challenges. I’ll use the [assessment scale proposed by Mike Perkins, Leon Furze, Jasper Roe, and Jason MacVaugh](https://aiassessmentscale.com/) as an example, although the same challenges apply to many other approaches, such as ‘amber’ traffic light indicators. In this scale, we have these two levels amongst the five:

- **AI Planning:** _You may use AI for planning, idea development, and research. Your final submission should show how you have developed and refined these ideas._
- **AI Collaboration:** _You may use AI to assist with specific tasks such as drafting text, refining and evaluating your work. You must critically evaluate and modify any AI-generated content you use._

This then leads to the question: how do we ensure integrity in assessments that fall into these categories?

The general mood has shifted decisively away from automated AI detection. However, for many assignments, this leaves us relying solely on human detection – unless the assessment is substantially redesigned.

It’s also worth noting that whilst perhaps AI detection has very limited use in colleges and universities, the [JCQ guidance for colleges](https://www.jcq.org.uk/wp-content/uploads/2025/04/AI-Use-in-Assessments_Apr25_FINAL.pdf) makes several references to AI detection and note:

> _“The use of detection tools, where used, should form part of a holistic approach to considering the authenticity of students’ work; all available information must be considered when reviewing any malpractice concerns.”_

It’s also notable that many of the examples cited by JCQ include the use 

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