Using AI in Your Research Without Risking Your Career
A hands-on workshop on using AI tools well, and ethically, at every stage of research
At a glance
What this workshop is about
Every scholar is now using AI somewhere in their research.
Almost nobody has been taught how to use it well – or told what they are required to declare. This workshop fixes both in one morning.
AI tools are already part of how research gets done. Scholars use them to search literature, sharpen research questions, summarise what they have read, structure arguments and tidy their prose. Most are doing this without training, without knowing where these tools fail, and without knowing what must be disclosed.
This workshop closes both gaps in one session. The first part is skill: how to prompt these systems, so they produce something a researcher can actually use, how to build a research assistant tuned to your own field and your own reading, and where in the research process these tools genuinely save time. The second part is judgement: what current policy requires, where the line between legitimate assistance and misconduct falls, and how to keep a record of your own work that can answer any question about it.
It is a working session, not a lecture. Participants prompt, test and build during the workshop using their own research material, and leave with templates they can use the same week.
Who it is for
- ✓ Research scholars and PhD students across the humanities and social sciences
- ✓ Postgraduate and MPhil students working on dissertations
- ✓ Early-career researchers, postdoctoral fellows and project staff
- ✓ Faculty members – both for their own research and for supervising students
- ✓ Journal reviewers, editors and members of research committees
- ✓ Independent researchers, policy researchers and think-tank staff
No technical background is assumed. Participants do not need prior experience with any AI tool, and the session does not require the purchase of paid software – free versions are sufficient to follow along, and where a paid feature matters, this is stated plainly.
What participants will take away
✓ Write prompts that produce genuinely useful academic output, rather than generic text – and recognise why most prompts fail
✓ Use these tools productively at each stage of research: refining a research question, searching and mapping literature, building a review, interrogating a text, analysing data, and drafting
✓ Set up a personalised research assistant – a working setup tuned to their own reading, field vocabulary and writing conventions
✓ Understand what current UGC, COPE and publisher policy expects of researchers using AI, and where those expectations are still unsettled
✓ Judge for themselves where legitimate assistance ends and misconduct begins, in the situations they actually face
✓ Write a disclosure statement for a thesis, a chapter or a journal submission
✓ Detect fabricated citations, invented sources and mis-attributed quotations before a reviewer does
✓ Keep a record of their research process that can answer any challenge with evidence
✓ Recognise where these tools flatten argument and voice, and protect their own scholarly writing from it
What the session covers
Three hours in four modules with one break. Each module combines demonstration with hands-on work on the participant's own material.
Module 1. Getting real work out of these tools
- How these systems actually produce text, in plain terms – and what follows for the researcher
- Prompting for academic work: structure, context, role, constraint and iteration
- Why most academic prompts fail, shown through examples participants will recognise
- Refining a research question and testing whether it holds
Module 2. AI across the research process
- Literature search and mapping: what works, what is unreliable, and how to verify
- Reading and interrogating texts you have already read, without outsourcing your judgement
- Building a literature review: where these tools help and where they quietly damage the argument
- Support for qualitative and quantitative analysis, and its limits
- Drafting and revision that keeps your own argument and voice intact
- Building a personalised research assistant on your own corpus, field vocabulary and writing conventions
Module 3. Ethics, policy and the line you must not cross
- Where the lines currently are: UGC's position, COPE guidance and what major journals and publishers now require
- Legitimate assistance and misconduct, worked through real cases – what was accepted, what was challenged, and why
- Authorship, disclosure and consent: what must be declared and in what words
- Fabricated citations and invented sources: how they are produced, and how to catch them
- Similarity and AI-detection reports: how to read them, what they cannot tell you, and what to do about a false flag
- Confidentiality: unpublished data, interview transcripts, student work and peer-review material
Module 4. Defensible practice
- Keeping an AI-use log that stands up to scrutiny
- Writing a disclosure statement for a thesis chapter or a journal submission
- What to do if your work is questioned
- Open questions from participants
One-to-one review – first 20 registrations
The first 20 registrants get a private 30-minute one-to-one session with the facilitator on their own manuscript, thesis chapter or paper.
Bring a draft you are worried about. We go through it together: how your AI use should be declared, whether your citations hold up, how to read a similarity or AI-detection report on your work, and what to do if a reviewer or committee questions it.
You leave with a disclosure statement written for that specific manuscript and a clear account of where you actually stand.
Conditions of the one-to-one review
- Available to the first 20 registrations only, in order of payment received.
- Sessions are scheduled between 5th November to 20th November 2026, by mutual convenience.
- Participants bring their own document. If they wish to discuss a similarity or AI-detection report, they should bring a report generated by their own institution – the facilitator reads and interprets it, and does not generate similarity or AI-detection reports on participants' behalf.
- The review is advisory. It is not a certification, a clearance, or a guarantee of any outcome with a journal, examiner or committee.
- Documents shared are treated as confidential and are deleted after the session.
What is included
- Live participation in the full three-hour hands-on session
- Recording of the session, available for 14 days
- A prompt template pack for research: refining research questions, literature search, literature review, reading and summarising, data analysis support, drafting and revision
- Setup guide for building a personalised research assistant
- AI-use log template
- Disclosure statement templates for theses and journal submissions
- Reference sheet of current policy sources, with links
- Certificate of completion, issued by AIRnD Lab and signed by the facilitator
- One-to-one manuscript defensibility review, 30 minutes – first 20 registrations only
How to come prepared
- Join from a laptop or desktop computer, not a phone or tablet.
- Have one research topic, question or draft of your own open and ready to work on.
- Have a free account on at least one AI assistant already created and signed in.
- Use a stable internet connection, and keep a notebook or document open for your own prompts.
Participants who come prepared with live research material leave with work actually done. Those who come to listen leave with notes.
Registration and fees
Until 20th October, 2026
28th October, 2026
Refund and rescheduling
Full refund if cancellation is requested at least 72 hours before the session. No refund within 72 hours of the session, as the seat cannot be reallocated at that point.
If the session is postponed by the organisers, registrants may either transfer to the new date or take a full refund.
To be confirmed with AIRnD Lab before publication.
About the facilitator
Dr. Akhil K Singh
Dr. Akhil K Singh is an Assistant Professor of Social Sciences at M. S. Ramaiah University of Applied Sciences, Bengaluru. He works in the broader domain of education and public policy.
He began in computer science before moving to the social sciences, and holds a PhD from the Indian Institute of Technology Jodhpur. That combination – technical training first, social science training after – is what shapes how this workshop is taught: neither uncritical enthusiasm about these systems nor a refusal to engage with how they actually work.
He is a published author in journals of international repute, and his monograph Education for the Embodied Human was published by Brill in 2025. He has lectured and presented research in China, Italy, Denmark, Japan and Ukraine, and has completed a training Programme on the use of AI in research and scholarship at the Indian Institute of Management Bangalore.
He supervises students across all levels, and reviews and edits for national and international journals – which means he sees both sides of this question: what scholars are submitting, and how it is being judged.
He teaches research methodology at postgraduate level and has led workshops and sessions on research methods and academic writing for scholars and faculty. The questions in this workshop are the ones his own students and colleagues have been bringing to him.
Contact: mail@akhilksingh.com
Website: Akhilksingh.com