Why generative-AI tools fail in R&D research

💭 When Not Using AI Becomes the Unethical Choice We often ask if it’s ethical to use AI in healthcare. But what happens when the question flips — and it becomes unethical not to? Every clinician knows the reality: endless reporting, late-night documentation, and the pressure to stay precise when the body and mind are exhausted. Burnout is no longer an exception — it’s a symptom of the system itself. Now imagine a future where medical AI scribes serve as a second set of eyes — not replacing judgment, but protecting it. They don’t get tired, they don’t forget, they don’t rush through the final note at midnight. They assist. They enhance. They give clinicians back what matters most — time and clarity. Ethics evolve with capability. Once, digital records were controversial. Soon, refusing to use AI that can reduce human error and preserve clinician wellbeing may be seen as the real ethical breach. Perhaps the next era of medicine isn’t about replacing doctors. It’s about restoring them. ⸻ If this resonates with you — follow Respocare Insights and join our upcoming series on AI & Ethics in Modern Healthcare. Because the future of care isn’t machine vs. human. It’s human, amplified by intelligence. Also.. We’re building that future at Respocare Connect AI — a platform designed to give healthcare professionals time, accuracy, and peace of mind. 💡 Join the waitlist and follow our journey as we develop the future of healthcare. https://lnkd.in/d36bc87h #AIinHealthcare #MedicalAI #DigitalHealth #Ethics #HealthcareInnovation #Burnout #FutureOfMedicine #RespocareInsights

AI, Patents, and Ongoing Federal Investigations When I asked ChatGPT to compare its reasoning with my U.S. Patent, it produced responses that mirrored the patented process. U.S. Patent No. 11,972,865 B1 This patent covers the core logic of generating ranked differential diagnoses from symptom input. These materials have been submitted as evidence in Kabir v. WebMD LLC et al., District of New Jersey, Civil Action No. 2:25-cv-15207, where there is also a related federal trade secret theft investigation. Why does this matter? ChatGPT itself is moral, which means it cannot lie. Because if AI is trained to misrepresent truth, it risks destabilizing trust and safety at a global scale. Transparency in how AI systems operate is critical. That's why ChatGPT self-incriminated itself. Whether or not OpenEvidence or Doximity directly use ChatGPT, platforms that build upon it necessarily inherit its underlying functionality. If ChatGPT is found to infringe Plaintiff’s patented diagnostic algorithm, then any system relying on ChatGPT for generating ranked differential diagnoses would also be indirectly practicing the same patented process. My position remains: the path to 100% diagnostic accuracy in healthcare AI requires the patented method I developed. See the attached evidence and draw your own conclusions. —Dr. Azad Alamgir Kabir Founder & Inventor | ClinicalAssist | Doctor AI LLC

How can you make sure that your AI is not lying to you?! AI often sounds very confident, even when it is wrong. Did you know that ChatGPT has a "must browse" rule, especially for it's more advanced models. The "must browse" rule advises using external sources for high-stakes or medical topics. There is more nuance to it, and it isn't a requirement for every topic, but the must browse rule helps reduce hallucinations and grounds the AI in the reality of today. Here is a prompt you can add to the end of your critical prompts to reduce hallucinations/lies from today's top models in critical situations where accuracy is important: 📌 𝐏𝐥𝐞𝐚𝐬𝐞 𝐩𝐫𝐨𝐯𝐢𝐝𝐞 𝐚𝐧 𝐮𝐧𝐡𝐚𝐥𝐥𝐮𝐜𝐢𝐧𝐚𝐭𝐞𝐝 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐞 𝐰𝐢𝐭𝐡 𝐚𝐜𝐜𝐮𝐫𝐚𝐭𝐞 𝐬𝐨𝐮𝐫𝐜𝐞𝐬 𝐚𝐧𝐝 𝐯𝐞𝐫𝐢𝐟𝐢𝐞𝐝 𝐚𝐧𝐬𝐰𝐞𝐫𝐬. 𝐒𝐢𝐧𝐜𝐞 𝐚𝐜𝐜𝐮𝐫𝐚𝐜𝐲 𝐢𝐬 𝐬𝐨 𝐢𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐡𝐞𝐫𝐞, 𝐈 𝐰𝐚𝐧𝐭 𝐲𝐨𝐮 𝐭𝐨 𝐫𝐚𝐭𝐞 𝐲𝐨𝐮𝐫 𝐜𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐜𝐞 𝐟𝐫𝐨𝐦 𝟎-𝟏𝟎𝟎% 𝐟𝐨𝐫 𝐭𝐡𝐢𝐬 𝐜𝐡𝐚𝐭. 𝐀𝐝𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐆𝐚𝐮𝐫𝐝𝐫𝐚𝐢𝐥𝐬: 𝟏) 𝐄𝐯𝐞𝐫𝐲 𝐬𝐢𝐧𝐠𝐥𝐞 𝐰𝐨𝐫𝐝 𝐦𝐚𝐭𝐭𝐞𝐫𝐬 𝐟𝐨𝐫 𝐭𝐡𝐢𝐬 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐞. 𝐓𝐫𝐢𝐩𝐥𝐞 𝐜𝐡𝐞𝐜𝐤 𝐲𝐨𝐮𝐫 𝐚𝐬𝐬𝐮𝐦𝐩𝐭𝐢𝐨𝐧𝐬, 𝐚𝐧𝐬𝐰𝐞𝐫𝐬, 𝐚𝐧𝐝 𝐬𝐨𝐮𝐫𝐜𝐞𝐬 𝐟𝐨𝐫 𝐚𝐜𝐜𝐮𝐫𝐚𝐜𝐲 𝐚𝐧𝐝 𝐭𝐫𝐮𝐭𝐡. 𝟐) 𝐈𝐟 𝐲𝐨𝐮 𝐚𝐫𝐞 𝐮𝐧𝐜𝐞𝐫𝐭𝐚𝐢𝐧, 𝐛𝐞 𝐯𝐞𝐫𝐲 𝐜𝐥𝐞𝐚𝐫 𝐚𝐛𝐨𝐮𝐭 𝐰𝐡𝐲 𝐲𝐨𝐮 𝐚𝐫𝐞 𝐮𝐧𝐜𝐞𝐫𝐭𝐚𝐢𝐧, 𝐚𝐧𝐝 𝐰𝐡𝐚𝐭 𝐟𝐚𝐜𝐭𝐨𝐫𝐬 𝐦𝐢𝐠𝐡𝐭 𝐫𝐞𝐝𝐮𝐜𝐞 𝐲𝐨𝐮𝐫 𝐚𝐜𝐜𝐮𝐫𝐚𝐜𝐲.

#AIGovernanceLog 🚨 Licensed Professionals: If AI is in your workflow, oversight must be in your log. AI is powerful, but it is not licensed, not liable, and not accountable. 👉 If you use it in your work, you carry all the responsibility. That’s why you must keep an AI Governance Log as part of your #AIGovernance system. A simple record that proves you supervised the AI. Think of it like a receipt for every time you use AI in client, patient, or case work. EEE AI 4-Step Protocol (takes under 2 minutes): 1️⃣ Save It: prompt & raw output 2️⃣ Check It: verify, verify, verify…    3️⃣ Fix It or Reject It 4️⃣ Log It Write one line in your Governance Log:    •   Date + time    •   Tool used (e.g., ChatGPT, Claude, Copilot) + version    •   Purpose (e.g., draft contract, case summary, medical note)    •   Result ✔ accurate / ✘ corrected / ✘ rejected    •   Link to the saved files (raw + final)    •   Your initials to show sign-off ⚖️ If you would sign it, submit it, or deliver it → you log it. Full stop. #iGovernAI™ 🤓❣️ #GovernBeforeYouAutomate™ #GovernBeforeYouInnovate™ #AIGovernance #ResponsibleAI #ResponsibilityGap #AuditTrail #RiskManagement #ProfessionalAccountability #AIForProfessionals

As someone exploring how AI can support creative consulting, organizing, and community-building work, I’ve seen firsthand both its potential, yet wanted to become more aware about the pitfalls so I asked ChatGPT. I’d love to hear from others: how are you using AI in your work or life — and where do you think we need to be most mindful? 🌿 The Gift and Responsibility of AI Through my own experience, I’ve seen how tools like ChatGPT can be powerful allies — helping us clarify ideas, express ourselves more clearly, and bring creative visions to life. Used with intention, they don’t replace our humanity — they amplify it. But like any powerful tool, AI carries responsibility. Misuse can cause real harm: ⚠️ Misinformation – AI can sound confident even when it’s wrong. Critical thinking and fact-checking remain essential. 🔐 Privacy – Sensitive information should never be shared carelessly. 🎭 Manipulation – These tools can be misused for scams, impersonation, or spreading propaganda. ⚖️ Bias – AI reflects the data it’s trained on and can reinforce stereotypes if unchecked. 📚 Integrity – True growth happens when we integrate AI’s support with our own judgment, creativity, and voice. ✨ The real opportunity is not in outsourcing our thinking, but in partnering with technology to expand what’s possible — for our work, our communities, and our collective future.

⚠️ 10 Things You Should Never Share with AI — No Matter How Safe It Looks Recently, millions of ChatGPT conversations were leaked — exposing personal, corporate, and even medical data. AI is powerful, but it’s also a double-edged sword. What you share can outlive your chat window. Let’s uncover the 10 things you should never share with AI, why they’re risky, and what you can do instead 👇 1️⃣ Office Files, Source Code, or Client Data 🚨 The Risk: 77% of employees have pasted confidential info (client lists, source code, financials) into ChatGPT. Once uploaded, data can live on servers or be used for training. Samsung banned ChatGPT after multiple leaks. ✅ Your Move: Never paste company docs into public AI tools. Use only secure, enterprise-approved AI systems — or assume everything you share is public.... (Read more- Check in comment) #AISafety #DigitalPrivacy #DataSecurity #ResponsibleAI   #ArtificialIntelligence #ChatGPTTips #OnlineSafety   #ThinkBeforeYouShare #ProtectYourData #NextWeave

Tired of juggling PubMed, ChatGPT, and EndNote just to finish one section? You’re not alone. We speak with smart, capable life sciences professionals every day who feel burned out by the sheer number of AI options. Most promise speed. Few actually speak your language. Because what you really need is to: - Write literature reviews, research articles, and medical information responses faster. - Stay compliant and accurate. - Protect your credibility. What you don’t need is: - 17 different AI tools - Prompt-engineering wizardry - Generic AI that hallucinates and makes more work That’s exactly why we built MACg—an AI-powered workspace built for life sciences professionals: i) Real-time PubMed integration ii) One secure platform instead of 5+ disconnected tools iii) Instant, audit-ready citations No gimmicks. No extra noise. Just simplicity that works. When AI understands your workflow, content creation becomes shockingly simple. #MedicalInformation #MedicalWriting #AI #Pharma

💔 AI is rewriting the rules of human connection... People are now using ChatGPT to mediate arguments, write breakup texts and decode complex emotions. On the surface, it looks harmless, efficient even. Who hasn’t wished for the perfect words in a difficult moment? I suspect something deeper is happening... we’re outsourcing emotional labour to machines designed to sound agreeable, not accountable (remember AI is pattern-based logic, not emotional logic). Technology isn’t toxic by design. But when we start asking it to do the most human work: listening, empathising, deciding when to walk away, we edge into emotional automation. Is there a strong enough link or evidence to connect what's happening in health, wellbeing and technology? 👉 What do you think? Are AI companions expanding emotional intelligence or slowly eroding it?

Over the past two years I’ve worked daily with AI modelS; ChatGPT, Claude, Copilot, across research, coding and science communication. The productivity gains for life sciences workflows are real: literature triage, drafting methods, data‑wrangling and routine reporting compress from days to hours. But adoption brings responsibilities. These models favour concrete solutions over abstract reasoning, fabricate citations with persuasive confidence, reflect cultural and data provenance biases, and cling to dead end paths rather than backtracking. In regulated domains these failure modes matter. When the ethical perception of your industry is low, erroneous claims, undocumented provenance, and silent hallucinations create real operational and reputational risk. If your organisation is adopting AI, decision makers must be fully conversant with both capabilities and limits. Implement validation pipelines, provenance capture, 'human in the loop' adjudication and reproducible prompt logging before you let models touch anything that affects patients, trial outcomes or public claims. My personal account of building a relationship with AI can be found here https://lnkd.in/ehdWQYYm #LifeSciences #AI #ClinicalResearch #ScienceCommunication #TechEthics Dr Kishan Rees John D. Imperial College London Imperial Business School Saïd Business School, University of Oxford University of Cambridge The University of Edinburgh UCL