Hi
Hope you had wonderful weekends wherever you may be. It’s Autumn in Hanoi which means the weather is beautiful and warm with blue skies and fantastic sunsets (see pic) – long may it last! A few quick notes from the world of AI to kickstart your Mondays:
Game Over for Copyright Claims: Legal Landmark as AI Labour Ethics Heat Up 🏆
A massive shake-up in the AI world as a New York federal judge drops a game-changing ruling that could rewrite the rules of AI and copyright law! The core bombshell? AI systems don’t copy – they synthesise, just like our own brains do. This makes some sense when you consider we’re talking about training datasets so massive it would take 170,000 years to read (at 8 hours daily). The court basically said what many AI experts have been arguing: the chance of actual plagiarism is mathematically tiny. And those early concerns about content regurgitation? There’s a case to be made that these are being solved by next-gen models like o1 that can track content provenance. This isn’t just another tech update – it’s a fundamental shift in how we think about AI and intellectual property.
Meanwhile, the darker side of AI’s integration into media is playing out in real time at the New York Times, where tech workers are striking for better wages and working conditions. In a controversial move that sparked immediate backlash, Perplexity AI’s CEO offered to provide technical support during the strike – a stark reminder of how AI companies might undermine worker leverage in labour disputes. While courts may be validating AI’s approach to learning, the industry needs to grapple with serious ethical questions about AI’s role in labour relations. The message is clear: as we solve technical and legal challenges around AI, the human cost can’t be ignored. Big Tech’s rush to replace human workers with AI solutions isn’t just about efficiency – it’s about power, and who gets to wield it.
Inside EU’s AI Archive Revolution: From Paper Trail to Digital Democracy 🇪🇺
The European Parliament has lifted the curtain on its ambitious archive transformation, showcasing how Archibot (powered by Claude) is revolutionising access to 70+ years of democracy in action. Since 1952, the archive has swelled from tens of thousands to over 2 million documents – but the real game-changer isn’t just the size, it’s the accessibility.
What’s fascinating is the Parliament’s careful approach to AI integration. While embracing Claude’s multilingual capabilities for instant document access, they’ve prioritised constitutional AI principles – ensuring every response is trustworthy and controlled, with clear sourcing and no data harvesting. For researchers and policymakers who once spent hours digging through physical archives, this isn’t just about efficiency – it’s about democratising European history. Trust and transparency, it seems, are just as important as technological innovation.
Beyond the Hype: UK Schools’ AI Reality Check Reveals Growing Digital Divide 🎓
In a sobering new report, aptly titled “Beyond the Hype,” the excellent Rose Luckin shatters illusions about AI readiness in English education. Examining 256 schools, the research cuts through the AI buzzwords to reveal stark realities: while 87% of educators grasp AI concepts, only 38% feel ready to actually use it in their classrooms. But here’s the real bombshell: Independent schools are significantly outpacing their state counterparts across every measure – from implementing safeguards (3.10 vs 2.51) to understanding bias (3.62 vs 2.99). And with just 30% of all institutions having any AI policy in place, we’re watching a digital divide unfold in real time.
While Singapore, Estonia, and Finland race ahead with strategic AI implementation, England lags behind. Without urgent action on professional development and ethical frameworks, AI risks deepening existing inequalities – especially as students increasingly use AI tools at home rather than school. Time for policymakers to move beyond the hype and ensure AI’s transformative potential benefits all students, not just the privileged few.
AI in Education Symposium Reveals Real-World Impact: From Medical Training to Journalism 🎓
The 2024 Cogniti mini-symposium held last week (5th November) showcased a remarkable breadth of AI applications in education, far beyond simple chatbot interactions. From medical students practicing histopathology to journalists honing newsroom skills, educators are creating sophisticated AI agents that transform how students learn. Most striking? The focus on practical, real-world applications – virtual patients helping physical therapy students perfect interview techniques, AI-powered peer learning reducing student anxiety, and custom agents cultivating curiosity in the classroom.
What’s clear from the dozens of presentations across three streams is that we’re moving past theoretical discussions about AI in education. Instead, institutions from Sydney to Saskatoon are delivering concrete results: personalised exam preparation for large cohorts, automated pre-submission review for scientific writing, and AI-enhanced assessment clarity. Hat tip to Danny Liu on putting together both a fantastic platform but a wonderful sharing forum for the wider HE community as we come to grips with this ever-evolving space. 🥳
Beyond AI Guidelines: Teacher’s Radical Classroom Experiment Shows New Path Forward 🚀
In a compelling post, AI Literacy tinkerer Nick Potkalitsky shares a classroom experiment that challenges conventional wisdom about AI in education. Rather than following the many and varied exemplars of methodological frameworks and usage guidelines sweeping through education, Potkalitsky simply asked students to use AI to brainstorm their own learning objectives. No restrictions. No predetermined pathways. Just pure exploration.
The results were transformative. Students forged intellectual partnerships with AI, mapping unexpected research directions and documenting their journey. When focus shifted from AI’s outputs to metacognitive development and agency, something remarkable emerged: students weren’t just learning to use AI – they were designing their own learning ecosystems. Potkalitsky’s experiment shows that perhaps the future of AI in education isn’t about control, but empowering students to architect their own learning journeys. 🤩
That’s all for this week’s roundup of AI in education. From courtroom precedents to classroom innovations, we’re seeing the landscape shift rapidly – sometimes in concerning ways, but also with remarkable opportunities for positive change. Keep experimenting, keep sharing your stories, and keep pushing the boundaries of what’s possible in AI-enhanced learning. Until next time! 🚀
Hanoi I love you at this time of year….😍