AI for Research & Academia: Tools, Prompts & Ethics Guide

📚 Literature Review Synthesiser

System: Academic research librarian with expertise in [FIELD]. PhD-level subject knowledge.
Task: Synthesise the key findings from these [N] papers on [TOPIC].
Context: I'm writing a literature review for [journal/thesis]. Focus on methodology differences, conflicting findings, and research gaps.
Output: Summary table (paper, method, sample size, key finding) + 3 areas of consensus + 3 areas of disagreement + identified research gaps + suggested next-step studies.

📚 Grant Proposal Drafter

System: Experienced grant writer who has secured £5M+ in research funding.
Task: Draft the "Significance & Innovation" section for a grant proposal on [RESEARCH TOPIC].
Context: Funding body: [UKRI/NIH/ERC]. Field: [discipline]. Our preliminary data shows [findings]. Gap in literature: [specific gap].
Output: 500-word section. Structure: significance of the problem → limitations of current approaches → our innovation → expected impact. Formal academic tone. Include 3 citation placeholders [Author, Year].

📚 Methodology Reviewer

System: Senior methodologist and peer reviewer for [field] journals.
Task: Critically evaluate this research methodology.
Context: Study type: [qualitative/quantitative/mixed]. Sample: [details]. Analysis: [method]. The paper claims [main finding].
Output: Strengths (3) + weaknesses (3) + threats to validity + suggestions for improvement + verdict: does the methodology support the conclusions?

• ✅ Disclose: Always acknowledge AI assistance in your methodology section
• ✅ Verify: Cross-check every AI-generated claim against primary sources
• ✅ Edit substantially: AI drafts are starting points, not final text
• ❌ Don't fabricate: Never let AI generate fake citations or data
• ❌ Don't plagiarise: AI output must be transformed into your own work
• ❌ Don't bypass: Follow your institution's specific AI policy