Anthropic's report: AI adoption varies by country, income

Another day, another report on people's views on #AI. This one from Pew Research Center on American's views on AI surveyed 5,023 adults from June 9 to 15, 2025. Key takeaways: ▪ Americans are much more concerned than excited about the increased use of AI in daily life, with a majority saying they want more control over how AI is used in their lives. ▪ Far larger shares say AI will erode than improve people’s ability to think creatively and form meaningful relationships. ▪ At the same time, a majority is open to letting AI assist them with day-to-day tasks and activities. ▪ Most Americans don’t support AI playing a role in personal matters such as religion or matchmaking. They’re more open to AI for heavy data analysis, such as for weather forecasting and developing new medicines. ( ❗ *Note*: the Q did not have AI in education as one of the use cases❗) ▪ Americans feel strongly that it’s important to be able to tell if pictures, videos or text were made by AI or by humans. Yet many don’t trust their own ability to spot AI-generated content.

If I had unlimited time I'd certainly go deeper into the whole AI literacy discussion. Too often it seems to come with an odd aftertaste: Everyone should use it or your out! AI is inevitable, here to stay - you must adapt, there is no other path! But who really benefits from all this “AI literacy” and the assumed adoption? I guess, the answer is obvious: AI companies. And then it seems like a trend to shift responsibility onto users (seen that before, right?). Suddenly, it’s on us to be “literate” rather than on companies to make AI safe, transparent, and accountable.  Maybe a bit user blaming involved. Maybe true AI literacy isn’t just about knowing how to use AI.. it’s about having that real or informed choice. The real, free option to say NO without nasty repercussions.

The D-K effect in AI Adoption (and no, that's not the Donkey Kong effect) The Dunning-Kruger phenomenon—where limited knowledge creates overconfidence—applies remarkably well to AI adoption patterns. Here's why: - The "Magic" Factor: For people with limited AI knowledge, AI capabilities appear almost "magical" and awe-inspiring". - Loss of Mystique: As AI literacy increases, users begin to understand the mechanics behind algorithms, training data, and computational models - Reality Check: Experts recognize AI's genuine limitations, potential biases, and unintended consequences. This awareness naturally tempers enthusiasm and reduces the perceived transformative impact. The paradox is clear: the more you understand AI, the more cautiously you approach it. Initial excitement gives way to measured consideration—a perfect demonstration of how knowledge can sometimes dampen enthusiasm. Credit to Luca Mora for the original insight—brilliant observation worth sharing! #AI #Adoption #Leadership

South China Morning Post - Artificial intelligence - World Opinion Published: 5:30am, 17 Sep 2025 Dr. Jack Ilmonen Opinion | Global AI war will be won in the key arena of education and training Nations must prioritise AI education or risk falling behind more agile competitors. Policy should centre on six moves: one, integrate AI across university, the kindergarten-to-12th-grade and vocational tracks; two, promote cross-disciplinary higher education that pairs AI with, for example, energy, law, agriculture and economics; three, treat AI education as strategic infrastructure with stable funding; four, embed responsible AI practices to build trust and accountability; five, link education to practical innovation through real-world projects; and six, align human capital development with national AI goals and metrics. The shift is under way. Google’s AI Works for America initiative is training workers and students in essential skills. China has issued guidelines for AI education in primary and secondary schools and powerful domestic models such as DeepSeek are diffusing quickly. Oil, steam and electricity mattered only when people knew how to use them. Want to win the AI war? Start learning and using AI tools. Thus, governments should democratise AI by investing in platforms that reskill everyone, fast. Jack Ilmonen Dr Jack Ilmonen is a professor of AI and data analytics at Keiser University (FL), US, Keiser Shanghai Centre. https://lnkd.in/gNMwVck6

Food for thought! "Generative AI as Seniority-Biased Technological Change: Evidence from U.S. Résumé and Job Posting Data" by Guy Lichtinger and Seyed Mahdi Hosseini Maasoum. "We study whether generative artificial intelligence (AI) constitutes a form of seniority-biased technological change, disproportionately affecting junior relative to senior workers." "The junior decline is driven primarily by slower hiring rather than increased separations, with the largest effects in wholesale and retail trade. Heterogeneity by education reveals a U-shaped pattern: mid-tier graduates see the largest declines, while elite and low-tier graduates are less affected. Overall, the results provide early evidence of a seniority-biased impact of AI adoption and its mechanisms." https://lnkd.in/eTw5r83H

A pharmacist from Egypt just outranked most Silicon Valley AI executives in global influence. The FavikonAI 200 September 2025 report reveals how completely the AI influence game has changed. While the old guard still holds some power, imagine them as the suited figures in this image, the established players who built the foundation, a new generation of AI influencers is reshaping the landscape entirely. Elon Musk leads with xAI and Neuralink, but the real story unfolds below. Greg Isenberg at #6 figured out AI-powered community building without running a major lab. Catherine Goetze (CatGPT) at #9 breaks down machine learning on TikTok and outranks most Fortune 500 CTOs. Kane Kallaway at #10 teaches AI workflows through billion-view videos. Then there's Hani Shaker at #12, that Egyptian pharmacist who became an AI educator. Ryota Tomogane at #13 went from Japanese beatboxer to AI engineer, making deep learning accessible through entertainment. The pattern is clear: influence flows from making AI useful for real people, not just building sophisticated models. Geographic barriers have collapsed, Brazilian educators, European researchers, and Asian creators are reshaping global AI discourse. Even traditional researchers who rank highly combine technical depth with communication skills. Andrej Karpathy at #8 moved from Tesla's Autopilot to launch Eureka Labs, proving research translation beats pure technical work. The data reveals a critical insight: technical excellence without effective communication creates influence bottlenecks. The people moving AI adoption forward aren't necessarily building the most advanced systems, they're helping others understand practical applications. This represents genuine democratization of AI thought leadership. You don't need a Stanford PhD or billions in funding, you need to solve the translation problem between AI capabilities and human needs. My goal is joining this list next year as the youngest member, because this shift shows the future of AI is being shaped by everyone who can help others navigate what comes next. #AI #ArtificialIntelligence #TechLeadership #Innovation #MachineLearning #AIInfluence #TechTrends #FutureOfWork #AIEducation #Leadership #Entrepreneurship #TechInnovation #DigitalTransformation

There has been a lot of focus in the increased importance of critical thinking in an AI world. But could its adoption in learning environments undermine the development of this skill? This is the risk raised by MIT in a new study. While it is yet to be peer reviewed and is based on a small sample, the researchers where sufficiently concerned to release a pre-review paper. What they found was that after breaking participants into three groups (ChatGPT, Google search and nothing at all), over a four-month period ChatGPT users had the lowest brain engagement and “consistently underperformed at neural, linguistic, and behavioural levels.”  The researchers conclude “The LLM undeniably reduced the friction involved in answering participants' questions compared to the Search Engine. However, this convenience came at a cognitive cost, diminishing users' inclination to critically evaluate the LLM's output or ”opinions”. However, the results were not all concerning. In the final session participants who had not used AI where able to use it to rewrite an essay from session 1 prepared without tools. This group according to the researchers “exhibited significant increase in brain connectivity when allowed to use an LLM on a familiar topic. This suggests that AI-supported re-engagement invoked high levels of cognitive integration, memory reactivation, and top-down control”. Will be interesting to watch this space as researchers further seek to understand the impact of AI use on the human brain. As a minimum, educational institutions may want to consider combining AI tool assistance with tools-free learning phases to optimise both immediate skill transfer and long-term neural development. Original research can be found here: https://lnkd.in/gFQCUYZK #CriticalThinking, #AIInEducation #EducationPolicy #EducationResearch

Beyond IQ: Rethinking intelligence in the age of AI. For generations, IQ has been our gold standard of intelligence. In India, it often decides which school you get into, which career path you’re pushed toward, and sometimes even your worth in society. A neat number that says: gifted, average, or struggling. But today, that definition is crumbling. AI can already solve equations faster than our brightest students, write essays in seconds, and analyze data with superhuman efficiency. It dominates the very areas traditional IQ tests measure - logic, memory, reasoning, language. If that’s all we mean by “intelligence,” then the machines are already winning. This is why Howard Gardner’s Theory of Multiple Intelligences (1983) feels so urgent today. Gardner argued that intelligence isn’t one score, it’s a spectrum: - Linguistic - Logical–Mathematical - Spatial - Musical - Bodily–Kinesthetic - Interpersonal - Intrapersonal - Naturalistic - Existential Seen this way, human intelligence is not just about solving problems, it’s about creating meaning, connecting with others, moving bodies with grace, sensing patterns in nature, and asking the deepest questions of existence. And here’s the good news: AI struggles with these intelligences. It cannot choreograph a Kathak performance with emotion, empathize with a grieving friend, or mentor a team through lived wisdom. These uniquely human abilities are exactly what the future demands. So how do we navigate this age of AI? - Expand your definition of intelligence. Marks and IQ are only a fraction of your potential. - Cultivate non-traditional intelligences. Creativity, empathy, leadership, and self-awareness are future-proof. - Use AI as a partner, not a crutch. Let it handle repetition; you focus on judgment, meaning, and innovation. - Encourage children beyond exams. Every child has gifts, not all of them show up on a test paper. The future won’t belong to those with the highest IQ. It will belong to those who can blend multiple intelligences with AI and remain deeply, unmistakably human. #Intelligence #MultipleIntelligences #AI #EmotionalIntelligence #FutureOfWork #Learning #IndianEducation #HumanPotential #Innovation #BeyondIQ

Yesterday, I stumbled on the concept of elective affinity. Elective affinity is a concept, first born in chemistry and later adopted in sociology, that explains why some things naturally “click” together and reinforce each other. You’ve seen it before: smartphones and social media reinforced each other until they became inseparable. Goethe (in literature) used it as a metaphor for human relationships. What about AI? AI doesn’t just exist; it gravitates toward what it fits with. - Abundant data + appetite for efficiency → AI thrives. - Human craving for certainty + AI’s statistical fluency → hallucinations feel “truthy.” - Agile organizations + experimental mindsets → adoption accelerates. - Opaque leadership + black box systems → risk compounds quietly. This is an example of an elective affinity in action. AI finds its home where the cultural, technical, and psychological conditions align, not necessarily where it is “needed” the most. Maybe the better question isn’t “Where should we apply AI?” but rather: “What kind of environments is AI naturally selecting and what kind of environments is AI quietly rejecting?” Because just like in toxic cultures where blame-shifters “fit” and innovators get pushed out, AI also shapes who gets amplified and who gets sidelined. #AITransformation #LeadershipInsights #DigitalCulture #FutureOfWork #ElectiveAffinity

⚠️AI IS SCARY AND DANGEROUS⚠️ Here’s a valid concern regarding AI use: 🗣️”There are so many AI stories now it’s so hard to believe what is real and what is not…..I also feel like we need more regulations on AI. Like they need to have a watermark or imprint on the image or video if it was altered…AI is scary and dangerous!!!” -Concerned Mom Here’s our response: What you’re naming is why AI literacy is so critical right now. People of all ages need to understand not just how to use AI tools, but also how to question, verify, and safeguard against misuse. At Umemba Health, this is one of the reasons we’re leaning into AI education. The answer can’t just be fear or avoidance, it has to be awareness, responsible use, and stronger guardrails like you mentioned. We believe everyone should have AI Literacy Education and why we developed our new course. The course is free and open for enrollment: https://lnkd.in/g99QKDJr #ArtificialIntelligence #AIForGood #ResponsibleAI #AILiteracy