About this guide
This guide presents case studies illustrating both responsible and cautionary uses of GenAI in research, as well as highlighting the necessary safeguards when employing GenAI technology.
Using AI in the Research lifecycle
AI tools can be used across the research cycle from planning and design, data collection, writing and publishing and sharing your research.
"Research Data Lifecycle" by LMA Research Data Management Working Group is licensed under CC BY-NC 4.0.
Research data lifecycle
This image depicts the cyclical process of academic research, illustrated as a circular diagram with seven steps. Each step is represented by an icon and a brief description. The steps are:
- Planning and designing research (light bulb icon).
- Reviewing the literature (documents with magnifying glass icon).
- Collecting or generating data for research (bar graph icon).
- Analysing research (funnel icon).
- Evaluating and reviewing research (magnifying glass icon).
- Writing up your research (document with pencil icon).
- Sharing and publishing your research (multiple document icons).
The steps are connected by arrows, showing the process as continuous and cyclical. This diagram illustrates how research is an ongoing process, with each stage informing and leading to the next, and ultimately cycling back to planning new research based on published findings.
Key takeaway
Always ensure that you take time to learn about AI tools and develop knowledge of their suitability and their limitations. Exercise judgement on risk for breaches of:
- research integrity
- confidentiality
- data sensitivity
- privacy
- third party copyright.
Acknowledgement
This guide is adapted from Responsible use of GenAI in Research © Deakin University. Content is used with permission under a CC BY-NC 4.0 license.