MeetingHand’s Post

Polished writing should not be dismissed as machine-made just because it looks refined. Yet AI detection tools are increasingly treated as ultimate judges, boosting what could be called “the AI Ego.” When detectors are applauded for flagging work as “AI-written,” the human effort and creativity behind the text risk being overlooked. A tool created to assist is suddenly elevated to the role of arbiter deciding the fate of writers and students alike. The reminder is clear: the tool should never overshadow human voices. Technology is not flawless, and academic thinking must always keep the human at the center. this is what I explore in my new article. #AI #Education #HumanCreativity #MEER #Academia

Artificial intelligence is transforming research writing in profound ways. Tools like ChatGPT and SciSpace are streamlining the process, making it easier than ever to draft and structure compelling academic papers. As these technologies evolve, we need to be aware of their ethical implications and the challenges they present, such as ensuring originality and accurate referencing. Using AI for academic work can save time and enhance productivity, but it’s crucial for writers to maintain control over their content. AI should complement human input, not replace it completely. This approach promotes high-quality research while respecting academic integrity. What are your thoughts on using AI in academic writing? Have you tried any AI tools for your research? Share your experiences and insights. https://lnkd.in/epnaSr_X Brain Pod AI

🔍 𝗔𝗜 𝗶𝗻 𝗠𝗮𝗻𝘂𝘀𝗰𝗿𝗶𝗽𝘁 𝗣𝗿𝗲𝗽 + 𝗣𝗲𝗲𝗿 𝗥𝗲𝘃𝗶𝗲𝘄: 𝗔 𝗧𝘂𝗿𝗻𝗶𝗻𝗴 𝗣𝗼𝗶𝗻𝘁 𝗳𝗼𝗿 𝗧𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝗰𝘆 This year’s Peer Review Week couldn’t have come at a better time. With the theme “Rethinking Peer Review in the AI Era,” the community has been buzzing with questions about how AI is reshaping research workflows and how we keep peer review credible in the process. That’s why the new STM recommendation on classifying AI use in manuscript preparation is so timely. It offers a practical framework for:  • Defining specific AI-assisted activities,  • Clarifying what needs to be disclosed (and to whom),  • Supporting publishers in tailoring policies to their communities. 📌 Until now, AI use was often vaguely declared if at all. This new structure helps authors, reviewers, and readers navigate the gray areas with more confidence. 💬 I see this as a critical step toward restoring trust in the research ecosystem. But it’s also a call to action: we need to align editorial workflows, peer review practices, and author guidelines with these evolving norms. 🔗 Read the full STM post via The Scholarly Kitchen: https://lnkd.in/dJVZhuvd And if you haven’t yet, check out the #PeerReviewWeek discussions. There are some great insights on how AI is reshaping not just writing, but reviewing too. #PeerReviewWeek #AIinResearch #AcademicPublishing #STM #ResearchIntegrity #ScholarlyCommunication #GenerativeAI #PublishingEthics

Very useful and practical summary, especially the emphasis on maintaining academic integrity while integrating these powerful tools. Great resource!" This is a fantastic and highly practical list for any researcher. It clearly emphasizes the right approach: AI as an assistant, not a replacement for original work and critical thinking.

🌐 ✍️ Authorship in the Age of AI: A Scientific Revolution is Happening 🚨 Can a researcher be considered an author if they use large language models (LLMs) like ChatGPT, Claude, or Gemini to draft their scientific papers? This is not just a technical question — it’s a profound challenge to the very foundations of academic authorship. 📄 A new preprint published in September 2025 (arXiv: 2509.05390) argues that the answer is YES — under critical human supervision. 🔸 Key insight: Scientific authorship has never been limited to “manual writing.” International standards (e.g., ICMJE) define authorship through: 🧠 Intellectual contribution 📝 Critical review ✅ Final approval 🧍 Accountability If a researcher: Provides clear and structured prompts, Critically revises and validates the AI-generated text, Approves the final manuscript, and Takes full responsibility for the content, then their role is analogous to that of a “senior author” — someone who guides and intellectually shapes the work, even if they do not physically write every word. ⚖️ Rejecting this view would also exclude many human researchers who play crucial conceptual roles without direct writing — a stance that risks being both unfair and outdated. --- ❗ Common Objections & Responses “But they didn’t write!” 👉 Modern authorship already includes many non-writing contributions (design, analysis, supervision). “AI replaces mentorship.” 👉 That’s an ethical usage issue, not an authorship criterion. “LLMs hallucinate.” 👉 Precisely why human oversight is indispensable. “AI has no intention.” 👉 Correct — the human provides intent; AI is just a sophisticated tool. 🔍 Why this matters: This debate isn’t about glorifying AI. It’s about updating our concept of authorship in a research ecosystem where intellectual work is increasingly mediated by powerful tools. Ignoring this shift could marginalize real human contributions and slow scientific innovation. --- 📢 Let’s discuss: Should AI-assisted drafting count as legitimate authorship? How should journals and institutions adapt authorship policies in the AI era? Where should we draw ethical and professional boundaries? 👇 Share your thoughts — this is a conversation the global research community cannot afford to ignore. 💬 As a researcher working with advanced nanomaterials and AI tools, I find this debate both timely and essential for shaping the future of science. #AIinScience #ResearchEthics #AcademicPublishing #LLMs #ChatGPT #Authorship #ArtificialIntelligence #FutureOfResearch #SciencePolicy #OpenScience #Innovation #PhilosophyOfScience #AIandEthics #AcademicWriting #LinkedInScienceCommunity

Important paper, that focus how widely available, LLM-powered generative AI tools (e.g. ChatGPT) can help in the academic writing process, and on the underpinning principles that can help guide researchers simulation scholars to produce high-quality research outputs with the highest of academic integrity ‏دراسة تشرح طريقه الكتابة الاكاديميه للابحاث بواسطة الذكاء الاصطناعي وينصح بقرائتها وفهمها لمعرفة استخدام الذكاء الاصطناعي بطريقه آمنه وأخلاقيه 👇🏼 رابط التحميل https://lnkd.in/dDZtNStj https://lnkd.in/duRwF9Y2

After testing 50+ AI tools, these 8 free options maintain complete academic integrity. Worried that AI tools might put your academic reputation at risk? You are not alone. Many researchers fear that using AI could lead to accusations of misconduct or even paper rejections. But here is what most do not realise: Some AI tools are designed to support rigorous research, not to generate content or cut corners. Used wisely, they can actually strengthen your academic integrity. Imagine this scenario: You spend weeks on a literature review, only to miss a pivotal paper buried deep in the archives. Or you struggle to map the connections between hundreds of studies. This is where the right AI tools become game-changers. After extensive testing, I recommend these 8 free tools that help you work smarter without ever crossing ethical lines: 1. Semantic Scholar - Advanced search uncovers hidden papers and citation contexts 2. Elicit - Streamlines systematic reviews and extracts key findings, saving hours 3. ResearchRabbit - Visualises citation networks so you spot trends and influential work instantly 4. Connected Papers - Maps out research landscapes, revealing gaps and new directions 5. Scite - Analyses citation relationships, distinguishing between supporting and contradicting evidence 6. Litmaps - Tracks how research ideas evolve over time, highlighting opportunities 7. Insiteful - Recommends relevant literature tailored to your interests 8. Consensus - Summarises scientific evidence across studies, clarifying where consensus exists The principle is simple: Let AI help you discover, organise, and analyse. Never let it write or fabricate. These tools amplify your expertise. They do not replace it. They help you uphold the highest standards of academic integrity. Which AI research tool will you try first?

This is a good list of AI research tools. For me the academic integrity always comes with the 'next steps' of what do with the results of any AI tool. Steps like careful checking of original sources, critical analysis of the tool itself, further analytical prompting and cross-referencing against other tools are all key. None of these tools are perfect, just like an academic library search or Google Scholar isn't perfect. But they are useful tools for any researcher to explore in a careful and critical way. #AITools #Research #AcademicIntegrity

After testing 50+ AI tools, these 8 free options maintain complete academic integrity. Worried that AI tools might put your academic reputation at risk? You are not alone. Many researchers fear that using AI could lead to accusations of misconduct or even paper rejections. But here is what most do not realise: Some AI tools are designed to support rigorous research, not to generate content or cut corners. Used wisely, they can actually strengthen your academic integrity. Imagine this scenario: You spend weeks on a literature review, only to miss a pivotal paper buried deep in the archives. Or you struggle to map the connections between hundreds of studies. This is where the right AI tools become game-changers. After extensive testing, I recommend these 8 free tools that help you work smarter without ever crossing ethical lines: 1. Semantic Scholar - Advanced search uncovers hidden papers and citation contexts 2. Elicit - Streamlines systematic reviews and extracts key findings, saving hours 3. ResearchRabbit - Visualises citation networks so you spot trends and influential work instantly 4. Connected Papers - Maps out research landscapes, revealing gaps and new directions 5. Scite - Analyses citation relationships, distinguishing between supporting and contradicting evidence 6. Litmaps - Tracks how research ideas evolve over time, highlighting opportunities 7. Insiteful - Recommends relevant literature tailored to your interests 8. Consensus - Summarises scientific evidence across studies, clarifying where consensus exists The principle is simple: Let AI help you discover, organise, and analyse. Never let it write or fabricate. These tools amplify your expertise. They do not replace it. They help you uphold the highest standards of academic integrity. Which AI research tool will you try first?

Something remarkable just happened in the world of scholarly communication — and it hasn’t received the attention it deserves. *Wiley* has quietly launched its *AI Gateway*, a platform that allows leading AI tools like *Claude, Perplexity,* and *Mistral’s Le Chat* to directly access *peer-reviewed, trusted academic sources* [1]. For those of us working in libraries or research, this is more than a tech announcement — it’s a cultural shift. For years, we’ve watched AI systems summarize knowledge pulled from everywhere (and sometimes nowhere). The results have been dazzling but also dangerous — quick answers without academic grounding. With the *Wiley AI Gateway*, that foundation finally begins to take shape. Through the *Model Context Protocol (MCP)*, AI assistants can now cite, retrieve, and interpret data from verified sources rather than random web pages [2]. It’s currently in *beta*, with publishers like *SAGE* and the *American Society for Microbiology* already on board [3]. For libraries, this could redefine discovery interfaces, improve citation integrity, and restore trust in AI-assisted learning. Students might soon be able to “chat with scholarship,” not just with algorithms. Still, the questions linger. Will access be affordable? Will smaller libraries be left behind? And will commercial control over knowledge deepen as AI platforms converge with publishers? These are the ethical and structural debates we must not ignore. Personally, I find this moment both exciting and sobering. Exciting — because it aligns AI with academic rigor. Sobering — because it reminds us how fragile equitable access remains. For librarians, researchers, and educators, this is our time to shape the dialogue before the systems are built without us. Regards, Sukhdev Singh. https://lnkd.in/g-ZAdBqw *References:* [1] Wiley Newsroom. (2025, October 14). *Wiley Launches Interoperable Platform to Power Scientific Discovery in World's Leading AI Technologies.* Retrieved from https://lnkd.in/gnjPEt5E [2] Ibid. [3] Ibid.