Critical Thinking Applications

Sleep is the brain’s most powerful performance tool, and most people treat it like a negotiable expense. Neuroscience is blunt: when you cut sleep, the brain shifts into survival mode. Astrocytes prune more synapses. Microglia stay activated. The glymphatic “night shift” that clears waste runs poorly. You don’t just feel tired. You lose clarity, memory consolidation, and emotional control. Decisions get riskier. Empathy gets thinner. Creativity shrinks. It’s not hours you’re sacrificing. It’s executive function. High performance isn’t willpower, it’s architecture. The brain thrives in rhythm, not chaos. Try this for 7 days: • Wake at the same time daily (weekends too). Let bedtime adjust earlier. • Light before phone: 5–10 minutes of outdoor light upon waking. • Caffeine curfew: none after 2 PM. • Protect one 90-minute deep-work block after your best sleep. • Swap micro-scrolls for a 10–20 minute early-afternoon nap. • Dim lights and screens 60–90 minutes before bed. • Run a 10–15 minute wind-down ritual (shower/stretch/paper journal, same order every night). Small rituals, massive neurological returns. Leaders don’t optimize sleep because it’s soft; they optimize it because it’s leverage. Start tonight. ♻️ Kindly repost to share with others Follow Benjamin B. Bargetzi for more on Neuroscience, Psychology & Future Tech

I’ve never had two editorials in top-tier journals focused on the same paper. It’s flattering, of course — even a pig blushes when praised, as Yattaman once wrote. But what really struck me about the PNAS commentary is something else: it got the point. Not the easy one. Not the marketable one. Not the usual talk about “how good” or “how human” or “how enabling” these systems are. The real question is more uncomfortable: if the promise is delegation, how do LLMs actually construct a judgment? Our work is not about accuracy. It is about architecture. Not what they answer, but how answers are produced. And when you look at that closely, the illusion of equivalence collapses. Humans and models may produce similar sentences, similar ratings, similar decisions — but they do not get there through the same cognitive structure. And this is not a technical detail. It’s an ontological fracture. Human judgment is embodied. It emerges from experience, memory, emotion, context, intention. It is grounded in a life. LLM “judgment” is not. It has no experience, no time, no world. It operates on statistical regularities among symbols, not on events in reality. And yet — this is the trap — the outputs can look the same. When radically different processes generate indistinguishable language, the problem is no longer technological. It becomes epistemological. This is what we call Epistemia: the moment when linguistic plausibility starts replacing verification, and the form of knowledge substitutes for the labor of knowing. Not because models lie — but because they simulate judgment so well that we forget what judgment actually is. https://lnkd.in/dcu7cuZm

One of the single most important issues is the impact of AI on human thought. This extensive and very interesting paper dives deep. I fully agree with its thesis that “Ultimately, harmonious coexistence with AIs will depend on revaluing cognitive diversity, designing interfaces that foster reflection, and making AI an augmentative partner of human thought, not its replacement.” Some key insights: ⚠️ Cognitive shortcuts weaken reasoning. Heavy reliance on AI showed a strong negative correlation with critical thinking, with cognitive offloading as the key driver. 🌍 Standardization narrows cultural and cognitive horizons. Generative systems trained on Anglo-American corpora nudged writers worldwide toward Western norms, reducing local nuance and expression. Algorithmic personalization reinforced echo chambers, creating “closed-circuit thinking” where diversity of perspective is dulled. 🎭 Manipulation risks bypass human reasoning. AI systems can exploit biases, tailor hypernudges, and generate synthetic personas—shaping decisions without awareness or consent. 🛡️ Safeguards must protect autonomy. The paper highlights transparency through internal logs, bans on subliminal techniques, neurorights for cognitive privacy, and “cognitive hygiene” education. These measures aim to secure epistemic plurality before opacity and automation erode mental sovereignty. 🚀 Design AI as a copilot, not a pilot. Positive potential emerges when AI is built to extend human cognition rather than replace it. Keeping humans “in the loop” ensures that AI serves as an augmentation tool instead of a substitute for thought. 🧑🏫 Pedagogy keeps humans thinking. Thoughtful integration in education—where AI outputs are paired with active reasoning exercises—preserves critical faculties. Training users to engage, verify, and question helps prevent erosion of independent judgment. 🤝 Interfaces should invite reflection. Instead of providing instant answers, AI can be designed to pose questions back to the user, prompting active engagement. This preserves cognitive effort while still supporting exploration and discovery. 🌱 Flourishing requires cognitive diversity. A healthy AI–human partnership means valuing diverse perspectives, fostering reflection, and designing systems that amplify—not homogenize—human creativity and judgment. ⚖️ Human–AI balance redefines collaboration. Individuals using AI performed at the same level as human-only teams, but AI-enabled teams dramatically outperformed both—showing that the deepest gains come from synergy, not substitution. 🌟 Augmentation as the true measure of success. The future of AI will not be decided by raw efficiency but by whether it strengthens or weakens human autonomy. Systems that expand reasoning, preserve diversity, and nurture reflection will be the ones that truly advance human flourishing.

I’ve put together 100 ideas for using GenAI in teacher education - and I’d love to share them with you. Whether you’re just starting to explore AI or you’re already experimenting with new approaches, these ideas are designed to spark practical, thoughtful, and sometimes playful uses of GenAI in teacher training. They’re not about replacing expertise - they’re about deepening professional thinking, supporting inclusive practice, and helping us prepare future teachers for an AI-enabled world. ✨ What’s inside? * Lesson planning experiments (generate, evaluate, and adapt AI-made plans) * Assessment challenges (critique model answers, refine questioning sequences) * SEND and inclusion tasks (design differentiated activities, adapt resources) * Reflective practice prompts (simulate trainee reflections, unpack emotional literacy) * Critical thinking activities (spot AI inaccuracies, uncover hidden biases) * Professional dialogue simulations (mentor feedback, parental conversations, safeguarding cases) * Curriculum and culture critiques (analyse policy writing, inclusivity, cultural assumptions) Each idea is ready to try, tweak, and discuss - whether you’re introducing AI for the first time or pushing your practice further. 🎯 How you might use it: Pick one idea that fits your course, session, or mentoring goal. Test it out - with your trainees, your mentors, your colleagues, or even in your own CPD. Reflect and discuss: What worked? What surprised you? What would you change? There’s no ‘perfect’ way - it’s about starting conversations, building confidence, and staying critical. 🤔 I’d love to hear from you: Which idea are you tempted to try first? What excites you most - or worries you most - about bringing GenAI into teacher education? 📅 And if you’d like to share how it went, we’ll be discussing ways we’re using GenAI in our next TeacherEd AI Network (TEAN) meeting on 16th May, 10-11am. Everyone is welcome - whether you’ve tried one idea, adapted it, or even completely disagreed with it! Drop your thoughts below ⬇️ - let’s learn from each other.

Stop loading data into ChatGPT and asking for insights. It is lying to you. An LLM cannot find "truth." It does not know your business context. It does not understand your data. It fabricates plausible narratives and reinforces your confirmation bias. You don't need an insight generator. You need a sparring partner. The LLM's true power is in stress-testing your ideas. This is how you shatter bias. This is how you find the real insight, not just the one you were looking for. Use the "Challenge-Code-Verify" cycle. - The Challenge: State your hypothesis. Command the LLM to act as a skeptical statistician and find 3 ways you are wrong. - The Code: Direct the LLM to produce the exact code (Python/R) or formula (Excel/Sheets) to test its counter-argument. - The Verification: Run the code. Look at the chart. Make the call. This is how you partner with the LLM to sharpen your human abilities -- intuition, creativity, novelty. Asking your LLM for insights is like asking your sparring partner to fight for you. It will get knocked out. Its job isn't to win the match. Its job is to reveal your weaknesses, sharpen your skills, perfect your form, and force you to be better. Spar with your LLM so that when its showtime, you are the one who lands the knockout. Art+Science Analytics Institute | University of Notre Dame | University of Notre Dame - Mendoza College of Business | University of Illinois Urbana-Champaign | University of Chicago | D'Amore-McKim School of Business at Northeastern University | ELVTR | Grow with Google - Data Analytics #Analytics #DataStorytelling

I've noticed a major uptick in conspiracy theories. Is it because it's an election year? I have always felt that these theories were best captured in the famous X-Files poster: 'I want to believe.' The theories stick because people want to believe them, not because they have any semblance of truth. But then I read this paper: 'Durably reducing conspiracy beliefs through dialogues with AI'—and was startled by the results. (link: https://lnkd.in/eSqRgk5y) The research paper in question presents an innovative study exploring how generative artificial intelligence, specifically a model like GPT-4 Turbo, can play a crucial role in reducing belief in conspiracy theories. This study engaged 2,190 participants who held beliefs in various conspiracy theories. These participants were involved in personalized, AI-driven dialogues that challenged their beliefs. Remarkably, these conversations led to a roughly 20% reduction in these beliefs, with effects persisting over two months. This finding is significant because it contradicts the often-held notion that once someone adopts a conspiracy theory, it is almost impossible to change their mind. The AI's approach was to provide compelling, tailored counterarguments, which proved effective across a wide array of conspiracy topics. Furthermore, this debunking also had a spillover effect, diminishing belief in unrelated conspiracies and increasing participants' intentions to challenge conspiracy-spreading individuals. This study not only challenges the understanding of conspiracy belief as immovable but also illuminates the potential of AI in psychological and informational interventions, offering a new tool against misinformation and irrational beliefs.

If there's one piece of advice I'd give to a student, it's this: pack your bags and get out of your hometown! "Ghar ki murgi dal barabar" isn't just a saying—it's a mindset that limits your growth. Leaving Calcutta, I shed the label of someone's daughter or a product of family expectations. ~ Bangalore, during my college years, taught me survival. ~ Mumbai, with my first venture, revealed the true value of building relationships ~ Working at Dubai, New York, Boston, San Francisco, showed me a global perspective, and how there are more than one right ways to approach a problem These experiences have shaped me into a leader who understands and values diversity. Leading 1000+ people over the years, from different backgrounds and cultures requires empathy, adaptability, and the ability to see through various lenses. I would not have developed any of this if I had never pushed myself to get out of my room. Things you learn when you move to new places: 1/ Developing adaptability: Every new city throws curveballs. You learn to hit them out of the park. 2/ Broadening your worldview: You'll meet people who couldn't care less about your "Sharma ji ka beta" status. They'll challenge you, push you, and blow your mind with new ideas. 3/ Building resilience: Overcoming homesickness and cultural barriers strengthens your problem-solving skills. 4/ Enhancing communication: Interacting with people from different backgrounds hones your ability to connect across cultures. To grow in your career, push for that chance to spread your wings. Your comfort zone might feel safe, but true growth—and leadership skills—are forged in new experiences.

As an early career software engineer, it’s tempting to rush through tasks to check them off your list. While efficiency is important, don’t miss out on a crucial part of your growth: asking questions and digging deeper. When working on a task, even if it seems straightforward, take a moment to understand why you’re doing it and how it fits into the bigger picture. Explore beyond your immediate task to see how other parts of the codebase work. Why was this approach chosen? Could there be a better way? This is the time when you're expected to ask anything that will help you learn. Don’t be afraid to push your boundaries!

I’ve placed 50,000+ candidates using these exact frameworks my students use to land offer letters at top firms. Here are the 5 most common stress-problem interview questions you must prepare, with expert-backed frameworks & concrete examples for each: 1️⃣ “Describe a time you had to make a decision with incomplete information.” Framework: Clarify → Assumptions → Evaluate Options → Choose & Explain Trade-Offs → Validate & Reflect. (Rooted in decision science) Example: As a product analyst, I had 2 days to decide product pricing without regional cost data. I clarified what data I had, stated assumptions about logistics costs, evaluated three pricing models, chose one with buffer margin, and after launch validated real costs. Result: pricing was off by <5%, reducing potential loss by ₹2 lakhs. 2️⃣ “Tell me about when multiple priorities clashed and what did you do first?” Framework: Urgency vs Impact Matrix + Stakeholder Negotiation + Clear Plan. Example: As marketing lead, campaign, content creation, and vendor approvals all due in the same week. I mapped urgency/impact, did vendor first (high impact, low effort), deferred some content with stakeholders, delegated minor tasks. We met major deadlines, revenue targets, without burnout. 3️⃣ “Give an example of when someone challenged your solution. How did you respond?” Framework: Present Solution → Invite Criticism → Adjust with Data & Listening → Finalize. Example: In an analytics project, I proposed using one statistical model. A peer challenged my assumptions about data distribution. I rechecked, collected extra data, and adjusted model inputs. Presentation showed both versions; the final version improved prediction accuracy by 12%. Stakeholders accepted an adjusted one. 4️⃣ “When have you had to think on your feet/sudden change?” Framework: Pause → Clarify scope → Rapid Ideation of alternatives → Choose best → Communicate. Example: During presentation, client asked for metrics by region not prepared. I paused, clarified whether broad region suffice, improvised splits based on last quarter with disclaimers, and focused the rest of the deck on what I had strong data for. The client was impressed by composure; I received follow-up work. 5️⃣ “Describe a time you prevented a problem before it became big.” Framework: Early Diagnosis (monitoring) → Root Cause Analysis (5 Whys / issue tree) → Low-effort Action → Monitor Change. Example: In operations, I noticed error rates slowly rising. Used root cause analysis to find misconfiguration in automation script. Fixed script, added automated alert. Errors dropped by 80%. Saved team 10 hours/week in fixes. If this helped you, repost this post with one of your own answers to any of the above 5 questions using one of these frameworks. Tag me and I’ll pick 5 replies and give feedback on structure & clarity so you can sharpen them before your next interview. #interviewtips #stressinterview #behavioralquestions #careergrowth #dreamjob #interviewcoach

The World as My Classroom: Lessons Learned Through Travel Travel isn't just about collecting souvenirs; it's about collecting experiences that shape you. Every journey becomes a learning experience, honing valuable skills that translate into the workplace. Here are just a few takeaways from my recent travels: - Adaptability: Imagine this: you miss your train in a bustling foreign city with no wifi. Sound stressful? Travel teaches you to navigate unfamiliar situations, think on your feet, and problem-solve creatively.  (Think of it as real-world project management, but way more exciting!) As travel writer Pico Iyer beautifully said, "One's destination is never a place, but a new way of seeing things." - Communication: Even with limited vocabulary, you learn to connect with people through gestures, smiles, and a genuine desire to understand. This strengthens your ability to build rapport and bridge cultural divides.  (Remember the saying, "It's not what you say, it's how you say it?" Travel makes you a master of that!) - Empathy: Witnessing different ways of life fosters a deeper appreciation for the diversity of human experience. It challenges your assumptions and broadens your perspective, making you a more empathetic leader and collaborator.  (As Maya Angelou put it, "Travel, understood as a journey, not a destination, allows us to experience the entire spectrum of one's humanity.") What are some of the biggest lessons you've learned from your travels? Share your experiences in the comments! PS - Clicked this pic on my 3rd work anniversary. These boarding passes aren't just mementos; they represent a constant reminder that anything is possible when you set your sights on the sky. I'm happy I living my dream - 7+ years and traveled 15+ countries and boarding 700+ flights still feels like dream. #travel #culturallearning #globalmindset #lifelonglearning #learning #positivepsychology #globalmindset #careerdevelopment #neverstoplearning