A selection of world thoughts – about AI – for global citizens.
What are the global perspectives on AI? Here, you will find a selection of articles from top newspapers, research publications, and leading magazines from around the world, exploring AI’s impact on language, culture, geopolitics, and economies. Our collection of local sources helps you understand the global landscape and navigate change through innovative ideas, keeping you informed about what’s relevant in this constantly evolving field.
Last Month’s Most Read Articles
AI Signals The Death Of The Author
We’re used to asking who wrote a text to decide whether it should be believed—as if the name at the top guarantees its truth. But what happens when the writer is an algorithm, prompted by a human, but animated by neither? In this essay, David Gunkel argues that Large Language Models don’t just mark the death of the author—they reveal it was always a construct. In their place, they center a new player: the critical, meaning-making reader.
Read the full article on Noema Magazine
Gender Parity in the Intelligent Age
Generative AI is rapidly transforming economies, yet women remain underrepresented in the talent pipelines shaping this future. This joint paper from the World Economic Forum and LinkedIn reveals how early, inclusive action can turn AI into a force for gender equity—or deepen existing divides. With fresh data, strategic insights, and real-world policy levers, it’s a must-read for researchers, leaders, and decision-makers seeking to align technological progress with shared prosperity. The window to embed gender parity into the Intelligent Age won’t stay open forever.
Read the full report on World Economic Forum
Meta Is Building a Superintelligence Lab. What Is That?
Meta is betting billions on a bold new frontier: “superintelligence,” a form of AI meant to outthink the human brain. With a high-stakes lab and an all-out talent hunt, the company is trying to reshape its place in the global tech race. But what exactly is superintelligence — and why does Meta want it?
Read the full article on New York Times
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AI systems are built on English – but not the kind most of the world speaks
AI systems may be trained mostly in English—but it’s not just any English. From autocorrect to voice assistants, what gets encoded is overwhelmingly mainstream American English, sidelining the vast spectrum of global Englishes spoken by 1.5 billion people. This article dives into how AI reinforces linguistic hierarchies and what it means to design technology rooted in linguistic justice—not conformity.
Read the full article on The Conversation
You sound like ChatGPT
AI is quietly reshaping how we speak and write, injecting its “voice” into our vocabulary and tone—think words like “delve” suddenly everywhere. This article dives into how AI’s polished, uniform language risks erasing the authentic, imperfect quirks that signal our humanity and build trust. It reveals a brewing tension between standardized AI-driven speech and genuine human expression, raising urgent questions about what it means to communicate—and think—like ourselves in an AI-influenced world.
Read the full article on The Verge
What it Takes to be a Glyph-Breaker
What does it mean to crack a lost script? In this essay, we follow a self-described “glyph-breaker” who’s spent 25 years chasing the dream of deciphering ancient, undecoded writing systems like Linear A and the mysterious Singapore Stone. Unlike past breakthroughs—think Champollion’s Rosetta Stone or Ventris and Linear B—today’s glyph-breakers face fragmentary texts, no bilingual aids, and little academic support. But with a mix of cryptanalysis, computational tools, and sheer obsession, they keep going. This isn’t just about decoding signs—it’s about giving forgotten voices back their words. And in a world where full decipherments are rare, it’s also a stubborn act of intellectual resistance.
Read the full essay on Aeon
Will A.I. Become the New McKinsey?
Think of AI not as a sci-fi superintelligence, but as a digital McKinsey—streamlining operations, cutting costs, and often putting shareholder value above people. This article unpacks how AI, like management consultancies, can quietly shape corporate decisions, intensify inequality, and sidestep accountability. It asks the hard question: is an alternative possible?
Read the full article on New Yorker
How to draft a will to avoid becoming an AI ghost—it’s not easy
AI now enables the digital recreation of lost loved ones—often without their consent, sparking complex ethical dilemmas. Most wills fail to account for this emerging reality, leaving families exposed to AI ‘ghosts’ that can be both comforting and disturbing. Experts propose that future estate plans may include safeguards against unauthorized AI use, but legal frameworks lag behind. As this technology advances, we must reconsider how consent, memory, and humanity intersect in the digital afterlife.
Read the full article on Ars Technica
Why A.I. Isn’t Going to Make Art
Is generative artificial intelligence capable of generating art? Starting from the concept of art and the choices that must necessarily be made to create something artistically new, this article explores the actual possibilities of AI to generate unique and creative content in the near future.
Read the full article on The New Yorker
Two Failure Modes of Emerging Technologies
AI is exploding—but the biggest risks aren’t sci-fi scenarios. The real danger? AI either works too well in ways we don’t expect or fails badly in ways we can’t see, hurting real people. This article breaks down these two critical failure modes and why we need to focus on the real problems of AI today—not just futuristic fears.
Read the full article on The Future, Now and Then
Prototype Computer Uses Noise to Its Advantage
What if noise—long considered the enemy of computing—turned out to be the key to a new era of AI? In New York, Normal Computing has built a prototype that harnesses thermal chaos to solve complex problems like matrix inversion. Thermodynamic computing is still in its early days, but it promises faster, more energy-efficient algorithms. A challenge to silicon-based orthodoxy, born outside the academic mainstream, that could redefine what it means to “process data.”
Read the full article on IEEE Spectrum
Researchers warn of ‘catastrophic overtraining’ in LLMs
A new study from leading universities reveals a surprising downside to massive AI training: too much pre-training can weaken large language models. This “Catastrophic Overtraining” makes models increasingly fragile, harder to fine-tune, and ultimately less effective—challenging the long-held belief that more data always means better AI.
Read the full article on Venture Beat
The Global A.I. Divide
AI is worsening the global digital divide—just a few countries control the massive data centers powering today’s breakthroughs, while most of the world falls further behind. This article reveals how this growing gap fuels brain drain, geopolitical tension, and a fierce race for digital dominance.
Read the full article on New York Times
From fear to fluency: Why empathy is the missing ingredient in AI rollouts
AI adoption isn’t just about tools—it’s about people. As AI evolves from copilots to autonomous agents, the real challenge is emotional, not just technical. This piece lays out the “4 E’s” of successful adoption—Evangelism, Enablement, Enforcement, and Experimentation—and explains why empathy, trust, and psychological safety matter more than speed.
Read the full article on Venture Beat
For Some Recent Graduates, the A.I. Job Apocalypse May Already Be Here
What if the jobs millions of recent graduates are chasing don’t actually exist anymore? As AI takes over entry-level roles faster than expected, new workers face a harsh reality: shrinking opportunities, uncertain career paths, and a workplace that’s evolving overnight. But is this the end of the road—or the start of something entirely new? Explore how AI is rewriting the rules of work and what it means for the next generation stepping into the job market.
Read the full article on New York Times
