#  Community Insights: Analysing and Interpreting Your Research Data with AI 

 



    ![researchers](/sites/g/files/omnuum1751/files/styles/hwp_5_4__480x385/public/2026-08/Picture1.jpg?itok=dSRET3IF) 

 



 

####  calendar\_today Date and Time 

 **September 15, 2026** 

 12:00PM - 01:00PM EDT 

 [ REGISTER HERE arrow\_circle\_right ](https://events.zoom.us/ev/AnIJr5JX2XKsuerXlqEAboKLvuq-U_YcAu_ti_7RMi0hKpELQMnu~AkObjqwcAs6PN1XVPa_Pa05o9aB6I_JfBEoxBJA56UuM-4VwW2N8OQODCA) 

 



 

This Nature Masterclasses webinar explores:

- How can AI help me design or automate the data collection process?
- How can I critically assess the outputs of AI-generated code?
- How can I protect sensitive or unpublished data when using AI?

Artificial intelligence can support researchers at many stages of experimentation, from collecting data to developing models, recognising patterns and troubleshooting problems. Used well, it can save time and open up new ways of working. However, reliable analysis still depends on sound research design, well-managed data and a clear analytical plan. AI cannot compensate for fundamental flaws in a study or turn poor-quality data into reliable evidence.

The challenge for researchers is knowing where AI adds genuine value and how to use it responsibly. How can they verify its outputs and manage risks such as bias, data privacy and security, and conclusions that go beyond the evidence?

In this webinar, you’ll learn from distinguished panellists with expertise in AI research, editorial practice and policy. They will examine the role of AI across data preparation, analyses, interpretation and visualisation. They will offer practical guidance and explain where human judgement and subject expertise remain essential. Whether you are new to AI or already using it in your work, the webinar will help you make more informed decisions about its role in your research.

You will have the opportunity to submit your own questions when you register. Please keep them relevant to analysing and interpreting research data with assistance from AI. Covered topics will help you to:

- Understand how AI can support different stages of data analysis, from planning and preparation to coding, troubleshooting and interpreting scientific results.
- Evaluate where AI adds value while recognising when subject expertise, robust research methods and human oversight remain essential.
- Manage research data responsibly by validating AI outputs, protecting sensitive information, documenting AI use and following institutional, funder and publisher guidance.
- Apply AI in ways to strengthen, rather than replace, your own analytical thinking and research expertise.

[See this flier for more details and a list of presenters](/sites/g/files/omnuum1751/files/2026-08/Community%20Insights%20-%20Analysing%20and%20Interpreting%20Your%20Research%20Data%20with%20AI%20-%20EDT.docx "Flier - Community Insights: Analysing and Interpreting Your Research Data with AI").



 

 



 

 

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