Introduction

Passionate about the Futures of Learning and Education, a serendipitous conversation between Robin Street, Director of Innovation at North London Collegiate School, and Carla Aerts (TrAIn Of Thought), led to a meeting with Vicky Bingham, Head of the school. Recognising that the Futures of Learning and Education are best explored in interdisciplinary dialogue, a new initiative was born.

On Friday 20th March 2026, the pilot of this initiative was launched. Twenty people, traveling from abroad and the UK, joined the launch to engage in dialogue and reflect on Learning and Education in Unexpected Places and Re-Socialising Learning. The day focused on what that means and can look like, and how we might begin to imagine new futures for both.

We welcomed Heads of schools, teachers and a professional musician, Innovation Directors, leadership experts and consultants, an entrepreneur, researchers and leaders in International Education and Education Reform, alongside experts working in STEM, publishing, system change, policy, data and, of course, AI in Education. The expertise gathered at North London Collegiate School’s Ideas Hub promised a special day. It turned out to be exactly that.

Why a Futures Dialogue?

In a world increasingly shaped by AI and standardisation, one question sits at the heart of everything we do today: how do we genuinely place learners and their teachers at the core?

Education is too often perceived through narrow frames: schools, universities, formal qualifications. Yet learning happens everywhere. Research, policy, practice, EdTech and AI tend to evolve in isolation, rarely in genuine dialogue with one another.

Today’s students and learners face a world that resists certainty and prediction. This forces harder questions: how do we nurture wellbeing and human values at the very moment intelligence itself is being redefined? How do we prepare young people for futures we can’t yet see?

The Education Futures Dialogue seeks to break down those silos. Learning and teaching take on many guises, in many places. Often, the best learning happens where it’s least expected. Yet we persist with systems that prioritise measurement over curiosity, benchmarking over aspiration, standardisation over the individual. In doing so, the essential social fabric of learning is too often eroded.

This dialogue is an invitation to rethink that. Not to discard what works, but to dare imagine a new paradigm: one that puts the learner and their teacher back at the centre, that takes learning beyond the classroom walls and prepares all of us for a future that is uncertain, technology-driven and full of possibility.

The box is gone. Time to start imagining, in dialogue.

Framing the Dialogue

Living in an AI revolution, it would have been the obvious choice to make AI the central theme for the day. We opted against it. Learning and Education go well beyond the classrooms and settings so often associated with them; yet we don’t necessarily give those other settings adequate attention. It is often there that the seeds for the Futures of Learning and Education are already germinating and flourishing. Making AI the central theme would prevent us observing those seeds.

Our day of dialogue revealed some of these seeds, often hidden gems of Learning in Unexpected Places that have significant impact on learners, teachers and wider communities. Programmes, projects and learning experiences beyond the classroom walls not only highlight the critical social dimension of learning; they reveal the importance of connection, of exploring the unknown in places where active, engaged and culture-relevant learning can take place to let learners flourish.

Sharing experiences throughout the day, it was also essential to bring learners themselves into the picture. We did exactly that, across two dialogue sessions during which they shared what matters to them and engaged enthusiastically with speakers and attendees.

Travel to the Canadian Arctic

Our day of dialogue opened with a trip to the Arctic. We discovered what Quarlimat, an Inuit-led summer programme for teenagers in Nunavik, does to build a brighter future for its teens and their communities. The programme was initiated by the Inuit community and Maggie McDonnell, the Canadian Global Teacher Prize winner in 2017, who has lived and worked closely with youth and elders in Inuit communities in the Canadian Arctic.

When you go running by yourself, you go fast.
But when you run with others, you can go so far.
Maggie McDonnell

Built on cultural activities, the programme creates safe spaces that nurture connections with Inuit role models, elders and community leaders. Hunters take the young people out onto the land to share traditional experiences and keep knowledge alive. The teenagers learn, share, socialise and connect in a culture-relevant context. They rediscover a connection with their land, communities and culture that, for many, had been lost.

A poignant example of learning happening in unexpected places: beyond the curriculum, in a deeply social, culture-inspired setting. The tone for the day was set.

The Highly Valued Currency of Education: Learning in Displaced, Disadvantaged and Refugee Contexts

Jane Mann, Director of the Cambridge Partnership for Education, illustrated the work the Partnership has undertaken in contexts of hardship, oppression and displacement. In a fireside conversation, she described how vital education becomes to people in these circumstances, how parents in refugee camps aspire for their children to find a way out, how they want their daughters educated in regimes that actively prevent it, and how evidence of learning and achievement becomes, in Jane’s words, “highly valued currency”.

Whether moving to the next stage of a learning journey or seeking a future beyond a Syrian refugee camp in Lebanon or Cox’s Bazar, where learning often happens for just a few hours a day in makeshift learning centres, that evidence matters enormously. The importance of the portability of this currency cannot be underestimated. It can offer a way out.

For girls in countries where schooling is forbidden, learning often must happen within the secrecy of the home, confined to the inside with little or no exposure to the outside world.

In these contexts of displacement, upheaval or restriction, demonstrating progress demands forms of assessment that meet the specific needs of learners and teachers. Jane described how bespoke wall charts, showing “I can…” statements, do more than record progress: they drive motivation, instil confidence and spark curiosity. Not only in the children, but in their parents too. They provide evidence that brings a sense of achievement, hope and at times can open doors.

“Learning and challenging contexts means staying close
to learners’ daily reality and building support that
helps them continue and progress.”
Jane Mann

A highly valued currency that goes far beyond opportunity. One that builds a genuine sense of achievement and the belief that learning is possible, wherever you are.

Teaching Musicians and Breaking Bach

Lisa Beznosiuk, renowned baroque flautist, has made recordings across Europe and played in major UK and European orchestras. She is a founder and Principal Flute of the Orchestra of the Age of Enlightenment.

Lisa has been teaching the baroque flute for around forty years, and many of her students are accomplished professional musicians, playing in orchestras, chamber ensembles and enjoy successful careers as soloists.

After a short introduction to the baroque flute, she discussed her teaching practice and how her students have embraced the online world for research, sourcing scores and exploring examples of baroque playing. Her teaching is highly personalised, predominantly in one-to-one settings, whether at renowned music conservatoires or in public masterclasses, a format she finds less conducive to deep teaching and learning.

What surprised many in the room, particularly the educators, was this:

“Of course, one teaches these students to teach themselves.” Her students become the self-reflective, self-directing explorers of their craft.

The Orchestra of the Age of Enlightenment rehearses at Acland Burghley, a London secondary school. Serendipitous encounters between learners and the orchestra happen naturally. They occasionally grow into something more: a programme that takes students enthused by hip hop and breakdance all the way to the Edinburgh Festival, performing Breaking Bach, dancing to baroque music.

We were fortunate to witness the surprise, bemusement, joy and achievement of these learners in a beautiful video^[1] . (Video link in footnote.)

“Teaching students is to get them to teach themselves.”
Lisa Beznosiuk

The Magic of Green Playgrounds:
Klimaat Speelplaats

St Paulus School in Kortrijk, Belgium is a small primary school that only had a concrete playground. The children didn’t play. They stood around the edges, engaged in bullying behaviour and rarely connected with each other.

The school decided to act. The teachers acted and conceived t he idea of a Klimaat Speelplaats, a climate playground. With no budget and no government support, they pressed ahead, designing the new space with a specialist bureau and, critically, with the learners themselves at the heart of the process.

Cedric Rykaert, one of the teachers and instrumental to the project shared how a hostile, featureless expanse that disengaged the children, turned into a green environment of nooks and crannies, secret corners, space for chickens, vegetable gardening, and room to explore. Open to the community at weekends, it is rarely empty.

The children’s behaviour changed radically. Bullying stopped. The space became a place for learning as well as for living. Standing at the edges turned into engagement, with the environment, with each other, with ideas.

St Paulus has since become a reference point for playground transformation across Belgium and beyond. Cedric and his colleagues are frequently invited to advise other schools undertaking similar projects. And yes, the initiative has caught the attention of the Flemish and Belgian governments.

MyMachine:
The Invention and Building of a Dream Machine

MyMachine^[2] is a global foundation built on an inter-generational collaboration model. Founded in Belgium, its methodology brings together three groups across one academic year: primary school children invent their dream machine with a sense of anything goes; university students design the concept; vocational secondary learners build a working prototype.

What makes MyMachine powerful goes well beyond skills development. Its ambition is to restore creative confidence, the kind of confidence that education systems too often erode by discouraging children from expressing their ideas and expressing their imagination. By bringing those ideas to life in unexpected, collaborative and hard-working spaces, it gives learners at every level something rare: a reason to believe their ideas and contribution matter. (Video link in footnote).

The Power of Peer-Learning: ZNotes

Zubair Junjunia, entrepreneur and founder of ZNotes, joined us from Saudi Arabia and shared the story behind the global peer-learning platform he conceived and founded.

Growing up in Jeddah, Zubair and a group of friends found that their schooling wasn’t taking them as deep into mathematics as they wanted to go. So, they started teaching each other. That experience sparked an idea: a platform where learners could solve problems and learn through their peers’ explanations and tuition.

ZNotes has grown into a free, globally accessible platform used by over six million learners worldwide, offering high-quality resources and active communities. What makes it genuinely distinctive is its ethos: a youth-led global movement that empowers young people to drive social change while building the skills and experiences that open doors to higher education and future careers.

The Dialogue: What the Room Revealed

The culmination of the day was the dialogue itself. Two roundtable discussions in small groups brought together attendees and learners from the school. The themes were Learning in Unexpected Places, places in the widest possible sense, and Re-Socialising Learning, the growing need to restore the social dimension of education in the face of its increasing individualisation. What follows is a synthesis of those conversations.

Learning in Unexpected Places

One of the first things this dialogue embarked on was quietly reframing the theme itself. The most interesting question, it turned out, wasn’t about unexpected places at all, it was about unplanned moments. Learners highlighted that places, in many cases, are not so surprising: a sports field, a drama rehearsal, a faith community, the street you run along in the morning.

What makes the learning happen is the moment of encounter within them, the thing that can’t be designed or scheduled. That recognition shifted something in the conversation in one of the round tables.

Examples came quickly and from every corner. Running a familiar city route, observing the street, navigating weather, watching interactions emerged as a rich account of learning through physical action, where the body processes what the mind has absorbed during the day. Team sport offers something different again: not just skills and fitness, but lessons in mutual support, in playing to other people’s strengths and, crucially, in losing.

One of the Heads noted that watching pupils work with each other in sport, especially when a team loses, taught them more about human resilience than almost anything else they’d witnessed in a professional context. Being a Brownie and earning badges; the social negotiations of a children’s birthday party; learning advocacy and political argument through agitprop theatre; finding culture and community in a church, mosque or synagogue aren’t just peripheral sites of learning. For many young people, they are where the most formative learning happens.

The learners in the room offered some of the sharpest contributions. One noted, with a directness that stayed with people: “Not being the best, but something to strive for.” It is the kind of honest observation that adults in formal education settings rarely feel licensed to say out loud. The youngsters’ honesty, several participants remarked, teaches us a great deal. Learning to be honest with yourself, realistic, but aspirational, turns out to be one of the harder things expected from education.

Drama, podcasts, interviews, and the simple act of really listening, these were named as sites of genuine learning. Listening is learning, one contribution read. Another: all learning comes from the unexpected. Nobody’s path is the same, and education that pretends otherwise does learners a disservice.

The conversation turned, as it inevitably does, to assessment. Here the room was unambiguous, and a little restless. Assessment, it was agreed, sits at the core of curriculum design and shapes everything downstream of it. But the current obsession with metrics leaves little room to breathe. It creates what one participant described as a system that conditions learners to be fearful. Qualifications, in their current narrow form, cannot capture the learning that happens in the places this dialogue had spent the day exploring. The Extended Project Qualification was offered as one existing tool for beginning to address this; its breadth of study at least points towards what a richer record might look like.

There was also a clear call for portability: qualifications that travel with displaced learners, that hold value across systems and borders.

And a student voice raised what may be the most urgent equity question of all: the gap in access to enrichment. The unexpected and unplanned learning experiences that were celebrated throughout the day may, in practice, be more available to some learners than others. Yet, the day clearly highlighted experiences in disadvantaged contexts and communities or inter-generational learning experiences that are available in regions where resources may be restricted, but imagination and attitudes to innovation flourish.

How do we capture those experiences when they happen? And how do we ensure they aren’t the exclusive province of those who already have the most, but also provide opportunity to those who have the least?

Education’s intent, someone offered simply, should be to improve lives. That framing, immediate, profoundly humane and almost embarrassingly obvious, cut through the rest.

Re-Socialising Learning

The second dialogue session opened with a concern that had been present all day but hadn’t yet been named plainly: that as education leans ever further into personalised, data-driven, technology-enabled models, it risks producing something socially thin.

Self-paced learning, left to itself, can induce loneliness. Data, when it is positioned above relationship, produces systems that are efficient and human at the same time in the way that most systems are — which is to say, not especially.

One participant drew a distinction that proved generative: the difference between loneliness and solitude. The act of reading is a solitary one, they observed, but it is not a lonely one. It constitutes a dialogue: with the text, with its author, with oneself. Productive solitude is worth protecting. What needs resisting is something different: a model of learning so thoroughly shaped by screens and data that the texture of human exchange, what one participant called the alive improvisation, is gradually stripped out of it.

The improvisation analogy, brought by someone who had worked in both policy and drama, revealed something important. Policy discussions, they noted, tend to run on yes, but… thus closing things down, hedging, qualifying. Improvisation, on the other hand, runs on yes, and… They build on what you hear, taking it somewhere, never apologising for where you’ve landed.

Learning, they argued, should follow the latter logic. It creates conditions for genuine exploration. It allows play. It teaches, among other things, that you can learn through not being good at something yet.

This sat alongside a harder truth: that much of what passes for learning today has been reduced to cognitive overload. We fill the time, assess the output, and call it education. But learning is fundamentally social; it happens in relationship, in dialogue and conversation, in the kind of environment where it feels safe to not know the answer. Several voices in the room converged on the importance of psychological safety: the need to create conditions in which failing is not just tolerated but recognised as part of the process in which fragility is not frowned upon. The commitment that emerged clearly from the discussion: we are teaching people, not just subjects.

The long view of education asks different questions, not only what a student knows, but how they have changed. Feedback sessions with parents, one participant suggested, might usefully include questions like: has your child become a better listener? A better friend? Some in the room noted, with interest, that tools for measuring exactly this do apparently exist, though time ran out to get deeper into that conversation.

“We are teaching people, not just subjects”
Heads and Directors of Innovation in Dialogue

Teachers featured prominently in this conversation, and not always comfortably. The role of the teacher is evolving, towards something closer to an orchestrator: someone holding a space for communal knowledge while simultaneously supporting highly individual learning paths: a steward. That is a genuinely demanding task. And it is being asked of a profession that is, in the room’s own word, frazzled. The pressure of differentiation, the weight of administrative expectation, the pace of change are not background conditions. They are the daily reality in which teachers are being asked to innovate, to personalise, to support good grades and achievement, and to re-humanise learning all at once.

One thread that deserves more attention than it received: at what point in a teacher’s professional development should new tools including AI, be introduced, without disrupting foundations still being formed? The question of timing and sequencing in teacher education and professional development is not merely logistical. Get it wrong and you create dependency or confusion at exactly the stage when a teacher most needs to develop her own instincts.

The roundtable also surfaced a false hierarchy that is doing real damage: the pervasive assumption that academic and vocational knowledge occupy different rungs of a ladder, with the former sitting above the latter. The Belgium example offered was stark though not unique: a country awash with overqualified master graduates whilst facing a serious shortage of plumbers. False hierarchies have consequences. Education systems that perpetuate them are not preparing learners for the world as it is, never mind what it will be.

The conversations in this roundtable ended, as good dialogues do, without resolution but with a shared direction. Togetherness and collaboration are not soft values or nice-to-haves. They are conditions of learning. Re-socialising education is not a reaction against technology; it is a commitment to ensuring that whatever role technology plays, it does not displace the human encounter at the centre of any serious act of learning.

What next?

The Education Futures Dialogue is not a one-day event. It is, as the name suggests, an ongoing conversation, one that is necessary because the questions are real, the stakes are high, and the distance between research, policy, practice and the learner remains costly.

What the day made clear is that the answers won’t come from any single sector, discipline or institution. They will emerge, as the best learning does, in unexpected places, through genuine encounter, and in dialogue.

The box is gone. The dialogue has started.

The end of a day of dialogue!

Huge thanks to Robin Street, Director of Innovation at NLCS, Vicky Bingham Head and all those enriching the dialogue during the day.
Mary Hamley (OUP), Laura Giddings (Rivers and Canal Trust), Zubair Junjunia (ZNotes), Cedric Rykaert (St Paulus School Kortrijk, Belgium), Safia Tmiri (Expert in AI and Education), Sally-Anne Huang (High Master of St Paul’s), Jane Mann (Cambridge Partnership for Education), Renate Samson (Digital, Data and AI Policy Specialist), Lisa Beznosiuk (Flute Teacher, Orchestral Player and Principal Flute - Orchestra of the Age of Enlightenment), Rebecca Warren (School of System Change), Alastair Falk (Education Consultant & Tsitsi Fringe Festival), Anna Paul (Head, South Hampstead High School), Brenda Eisenberg (Insight and Strategy Consultant), Estelle Linjun Wu (PhD student), Kate Howell (HMC - Headmasters and Headmistress Conference), Will Van Reyck (Director of Innovation, St Paul’s), Marion Smallbones (Education Development Trust)

^[1] Does hip hop dance work with Baroque Music? The story of Breaking Bach.

^[2] My Machine was founded in Belgium

https://mymachine-global.org

It was a very simple and short illustrated story. This and a particular conversation stopped me in my tracks. It’s why I’m writing this.

From the Chair that made a Difference by Roukaya Bakhsh

Over the past months, I worked with the Cambridge Partnership for Education on a three-month AI for Science Educators programme, commissioned by the Kuwait Foundation for the Advancement of Science (KFAS). We opened with a three-day residential at Kuwait University in November, working with 50 selected participants. This was followed by the online part of the course programme, supported by four 45-minute coaching sessions. Two and a half months later, we were back in Kuwait for an intense four-day programme.

Kuwait University

What made the different wasn’t the bespoke curriculum we developed for this programme. It was the context in which the programme was delivered. We worked in the national Kuwaiti education context, rooted in its own curricula, culture, language and local education priorities. Working within the Kuwaiti context meant we couldn’t default to familiar ground. We had to tune in — to the culture, to the perspectives, to what AI meant in this specific setting. That raised our bar. And it taught us more than one lesson.

We engaged with educators across the full education spectrum, from Kindergarten through to university. Educators from each level challenged one another in ways that simply wouldn’t happen within a single cohort. It was unusual. It was enriching.

The Kindergarten and Primary teachers were the ones who surprised us most. They navigated the AI tools with a creativity and problem-solving instinct that was frankly humbling. They created resources for their pupils, shared them with peers, built Instagram groups to keep learning and inform their peers on the good and practical use of AI. They pushed their learning and practice further with every new attempt, every lesson plan, every workflow, every resource.

The teacher behind The Chair also created animations to help her children distinguish carnivores from herbivores. Her goal was never to just put screens in front of children; AI was the tool to bring enrichment and augmentation to her classroom. And she was more than keen to share what she’d learned, with grace and inspiring humility.

Key Message: AI for augmentation, guided and reviewed by teachers

At secondary and university level, educators created resources to explain scientific concepts, including a comic strip on using GenAI effectively, built around the Art of Asking AI for students studying Quantum Mechanics, rather than simply offloading one’s thinking to the machine.

The Art of Asking AI: to support students to understand concepts of
Quantum Mechanics as well as teaching mindful use of AI

But something else emerged. Something that didn’t surprise me but highlighted a fundamental shortcoming of GenAI. One that should remind all of us, especially when using AI in education contexts.

During the last session with Kindergarten and Primary teachers, we continued a conversation about using GenAI and LLMs in Arabic. Using the most prominent AI LLMs’s, teachers often had to prompt in English to get usable results, before translating the content. When they used Arabic for prompting, the output felt like a translation, not content generated in Arabic in the first place. The grammar was off. The phrasing and often words, sounded strange. We couldn’t prove that LLMs were looking at English language data, prior to translating the output into Arabic, but we did suspect this might be the case. I told them I had seen similar results working with AI in other non-English languages. A sense of non-native origination was shared and reflected upon. What did that mean for their context, the culture and the learners in their schools or universities? I explained to them that I had the same experience using AI in non-English languages.

Then came the moment that brought everything together for me.

During one of their presentations, AI-generated images were displayed and discussed. I asked the teachers whether they felt the images represented them, the children in the classroom or their cultural context and references. Could they recognise themselves and their pupils in what had been generated?

The answer was unanimous.

No.

This opened a conversation about bias that went to the heart of what we’d spent three months working on together. The language models these educators were using did not draw on Arabic LLMs, but tended to be typically ChatGPT and Gemini. Co-pilot was also often used as Microsoft technologies are ubiquitous in education settings in Kuwait. The results of using these models did not represent Kuwaiti language, culture, context or their visual world. We were being confronted by the WEIRDness¹ of AI, a result of these go-to AI systems still predominantly being developed by Western, English-speaking white males in their contexts or originate in China.

For me, everything discussed during the programme somehow culminated in that final conversation. A shared recognition of how far GenAI still has to evolve to become more representative, inclusive and equitable. The message hit home.

¹ WEIRD — Western, Educated, Industrialised, Rich, Democratic — a term used to describe the narrow demographic from which much of AI’s training data and development still originates. This acronym was coined by the anthropologist Joseph Heinrich of Harvard University. He developed the WEIRD framework to raise people’s consciousness about psychological differences and highlight that WEIRD frameworks represent a rather thin slice of humanity’s cultural diversity. For Henrich, WEIRD accentuates the sampling bias present in studies conducted in cognitive science, behavioural economics, and psychology.
For those of you interested in the WEIRDness of AI, read this post on my Substack: https://www.trainofthought.me/p/the-weirdness-of-generative-ai

With thanks to the KFAS team, who managed the full logistics and operations throughout; to Niall McNulty of Cambridge University Press and Assessment, Ismail Sabry, Cambridge Partnership for Education; Educate Ventures, led by Madiha Khan and to Carmen Thomas, Kristina Cordera, Ali Chaudry and Jennifer Seon.

Image: TrendHunter

Introduction

I read Rebecca Winthrop’s^[1] World of Education LinkedIn post on the OpenAI and Mattel Strategic Collaboration a few days ago. In her newsletter Rebecca invites us to respond, with prompted c comments. My response proved too long for a ‘comment’ on LinkedIn. I resorted to this short article instead, below.

I embarked on a bit of a dialogue with Anthropic Claude Sonnet 4.0. I have included my prompts and Claude’s responses (verbatim), but have omitted the search trails Claude presented to inform its responses.

The newsletter focuses on a fundamental shift in ‘play and imagination’ as well as engagement with toys that children are likely to experience increasingly, as AI makes inroads into the Smart Toys. The theme is of particular interest, not only because of its AI dimension as such, but because of the impact such toys are likely to make on play, supported and informed by Generative AI models. While the partners may well laud the potential of this new generation of toys, significant fundamental ethical, philosophical, commercial and data privacy and protection questions emerge. We’re not even close to scratching the surface sufficiently, highlighted by my response.

In 2021, I was involved in the World Economic Forum Centre for the Fourth Industrial Revolution’s task force that focused on Smart Toys and was a lead author in the resulting toolkit focused on parents, children, C-Suite executives and Developers. (My focus was on parents). Rebecca’s newsletter resonated even more strongly.

You can find Rebecca’s newsletter on LinkedIn.
The WEF Toolkit can be downloaded here.
OpenAI-Mattel Strategic Collaboration Announcement.

Prompt 1 & Claude’s Response

Prompt: Mattel and OpenAI have formed a partnership for smart toys. Play will witness a paradigm shift, but is it really advisable.

How do we ensure kids have the wonder and imagination that play and free play brings them. Are we restricting these innate and essential attributes of children and force them in US culture and white male bias models for play. Is Barbie being amplified?

Response: You raise incredibly important concerns that many child development experts, advocates, and parents share. The Mattel-OpenAI partnership, announced in June 2025, does represent a significant paradigm shift in how children play—one that deserves serious scrutiny.

The Partnership Details

The collaboration aims to create AI-powered toys and experiences based on Mattel's iconic brands like Barbie, Hot Wheels, and Fisher-Price, with the first products expected to be announced later this year. Notably, the first product won't be for children under 13, helping Mattel avoid stricter regulations while sidestepping some criticism about marketing AI to very young children.

Your Concerns Are Well-Founded

Wonder and Imagination at Risk: Child advocacy experts worry that "endowing toys with human-seeming voices that are able to engage in human-like conversations risks inflicting real damage on children" and "may undermine social development, interfere with children's ability to form peer relationships, pull children away from playtime with peers". Josh Golin from Fairplay argues that "children's creativity thrives when their toys and play are powered by their own imagination, not AI".

Cultural and Gender Bias Your concerns about "white male bias models" are particularly relevant. Research shows that "algorithms trained on non-representative datasets risk perpetuating systemic inequities, disproportionately affecting marginalized communities". As one analysis noted, "AI systems are only as unbiased as the data fed into them, companies need to actively work towards ensuring diversity and fairness in AI training datasets".

The Barbie Amplification Question

Yes, this partnership will likely amplify Barbie's cultural influence significantly. The Barbie brand already spawned a $1.5 billion box office hit in 2023, and AI integration could create even more pervasive cultural messaging. Given Barbie's historically problematic representation of beauty standards and gender roles, an AI-powered version could reinforce these messages in more sophisticated, interactive ways.

Why This Matters More Than Previous Tech

Unlike earlier "smart" toys, generative AI systems "will engage in free-flowing conversation" and "may simulate care, express emotion, remember preferences and give seemingly thoughtful advice". There are concerns that children might "become more attached to AI than to the people around them", fundamentally altering how they develop social skills and emotional intelligence.

The Troubling Track Record

Mattel previously launched "Hello Barbie" in 2015, which asked personal questions about children and families, sending audio to third parties. Security researchers found vulnerabilities allowing eavesdropping, and Mattel pulled the toy in 2017. This history raises questions about whether the company has truly learned from past mistakes.

A Call for Resistance

Your instinct to question this development is spot-on. As Robert Weissman of Public Citizen argues, "Mattel should announce immediately that it will not incorporate AI technology into children's toys. Children do not have the cognitive capacity to distinguish fully between reality and play".

The risk is that we're potentially sacrificing the irreplaceable magic of child-driven, imaginative play for the convenience of AI-powered entertainment. Free play—where children create their own narratives, solve problems independently, and develop creativity—is fundamental to healthy development. When toys become the storytellers and problem-solvers, we may be diminishing children's capacity for these essential skills.

Rather than embracing this as inevitable progress, we should be asking: What kind of childhood do we want to preserve? And are we willing to let market forces and technological capabilities determine how our children play, learn, and develop their sense of self?

Prompt 2 and Claude’s Response

Prompt: I didn’t think the toys were going to be 13 years upwards? Won’t they be addressed at younger children too. If not, it won’t be long?

Response: You’re absolutely right to question this—and your instinct about the age restriction being temporary is likely correct. Let me clarify what's actually happening:

The 13+ Limitation is Strategic, Not Permanent

The first product won't be for kids under 13—a move that helps Mattel avoid stricter regulations and sidestep criticism over marketing AI to young children. This appears to be a calculated business decision rather than a principled stance on child development.

Why Are They're Starting with 13+

As OpenAI's services are not designed for children under 13, in principle Mattel will focus on products for families and older children. This is likely tied to COPPA (Children's Online Privacy Protection Act) regulations that create stricter requirements for collecting data from children under 13.

The Inevitable Slide Toward Younger Ages

Your concern about "it won't be long" is well-founded. Several factors suggest this age restriction is temporary:

1. Market Pressure: The AI toys market is projected to grow from $42 billion in 2025 to $224 billion by 2034. That kind of growth potential creates enormous pressure to expand into younger demographics.

2. Competitive Dynamics: Other manufacturers have already been "reckless, with numerous LLM-powered toys already on the market". If competitors target younger children, Mattel will likely feel compelled to follow.

3. Mattel's Core Market: The company's biggest brands—Barbie, Fisher-Price, Hot Wheels—have historically targeted much younger children. It would be economically illogical for them to permanently abandon their core demographic.

The Real Concern: Normalization Process

Starting with 13+ appears to be part of a broader normalization strategy:

- Test the technology with older children first
- Work out privacy and safety kinks
- Build public acceptance
- Gradually lower the age threshold

As one analysis noted, this represents "the convergence of several powerful forces: technological readiness, market demand, educational need, safety maturity, and cultural acceptance". Once these forces align for teenagers, extending to younger children becomes the logical next step.

What This Means for Younger Children

The 13+ restriction offers only temporary protection. Companies are already working on ways to make AI toys "safer" for younger ages, but this misses your fundamental point about preserving wonder and imagination. The question isn't whether AI toys can be made technically safe for 5-year-olds—it's whether they should exist at all in the developmental landscape of early childhood.

Your concern is prescient: we're witnessing the opening moves in what will likely become a systematic colonization of childhood play by AI, starting with teenagers and working downward. The 13+ age limit is more of a strategic pause than a permanent boundary.

To Summarize: Some further thoughts

Having embarked on this short dialogue with Claude Sonnet 4.0, the questions about the Relationship GenAI and Children have become even sharper. The toys’ anthropomorphizing and their behaviours will blur the boundaries between human relationship and inorganic machine relationships further and do so very fast.

The concerns this partnership raises are significant and require urgent attention. Not least to address the risks and dangers, as well as consider scenarios where such toys can bring benefits to children. This requires ensuring that children are made aware that these toys are not their real friends at all, but that they are clever machines. Urging them to spend more time imagining and playing with their ‘real’ friends, will have to be part of the future story of childhood in an AI world.

^[1] Rebecca Winthrop: Director of The Brookings Institution Centre for Universal Education and co-author of The Disengaged Teen.

After writing my review of Han’s Crisis of Narration, I performed a little Notebook experiment and went into Google Notebook Studio to create an AI-generated podcast. This may somewhat at odds with the reflection piece, and Han’s critique on the demise of narration.

However, we live in a time of AI exploration and the opportunity to remedy the erosion of the story and only our experimentation may bring us the reinvention of and remedy for narration and ‘the story’, multi-modally. So why not start with taken a written piece into a little AI podcast experiment?

Keeping prompts succinct and extremely simple and going through a few refinement cycles started off by:

• Having prompted for a male host and female speaker, Notebook LM couldn’t help itself and reveal its bias openly, reverting to the opposite.

• I requested a British accent and manner of delivery, rather than the exuberance of Notebook LM’s US, white speaker, preference. Although the list of languages in Notebook LM is exhaustive, British English is not fully embraced. I had to give up after a few tries. I did not pursue other flavours of the English language.

• The first attempt attributed the whole piece to Han. I’m sure he would not have been too happy about that. I had to point out that Han was not the author of this reflection piece and that the attribution needed some attention. Notebook LM did comply without any struggles.

• The included podcast, based on my TrAIN Of Thought substack post by the same title is the result of a dialogue with Notebook LM.

• Whilst not perfect and still biased to US speakers and culture, the result was not entirely disappointing.

Here to listen

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Byung-Chul Han: Critic of Neoliberal Society

Byung-Chul Han is a South Korean-German philosopher renowned for his critiques of neoliberal society and concerns about the digital age and its societal impact. In many of his works, Han has expressed concerns about the currents and malaise of a neoliberal techno-world, in which individuals increasingly view themselves as “achievement-subjects” or individuals that have become “projects: always refashioning and reinventing themselves”1 in their striving for success, omnipresence and status in the online world.

Han’s essays draw on the German philosophical tradition. In particular Heidegger, Arendt and Benjamin have been influential on his thinking, including in The Crisis of Narration, a philosophical discussion.

Although a philosopher at heart, Han claims to be more popular amongst artists than philosophers. This emerges from the English translation of a German interview in ArtReview that discusses his work as a new ‘narrative against prevailing doctrine’ in which art is the saviour, not philosophy, resonating with the ideas expressed in The Crisis of Narration, one of Han’s more recent works, discussed below.2

"Effectively more artists than philosophers read my books. Philosophers are no longer interested in the present. Foucault once said that the philosopher is a journalist who captures the now with ideas. That's what I do. Moreover my essays are on their way to another life, to a different narrative. Artists feel addressed by that. I would entrust art with the task of developing a new way of life, a new awareness, a new narrative against the prevailing doctrine. As such, the saviour is not philosophy but art. Or I practise philosophy as art."3

The Crisis of Narration

The Crisis of Narration, a short and highly recommended essay that highlights a paradox of our time in which storytelling and narrative surround us, yet in which we find ourselves in a crisis of narration.

According to Han, the not so distant past was alive with stories. They gave people’s lives meaning and direction. They made sense of the complex world in which they lived. Unfortunately, in our modern age stories have been reduced to fleeting commercial narratives that no longer bind and connect us, but lead to isolation.

The power and magic of narration and story has eroded into the fashionable storytelling, that permeates marketing and consumer society reliant on storyselling and the grabbing of our attention, pillars of neoliberal capitalist online society. The author equally highlights how contemporary society is increasingly reduced to online and social media storytelling. These accelerate societal and community erosion. Caused by floods of fragmented information, the antithesis of “narration of stories” has led to an impoverished sense of community, social cohesion and isolation of individuals.

In this recommended short essay, Han calls for a renewed appreciation and revaluation of the true and unifying power of stories and narration.

Demise of Narration

Han’s critique of the modern world, manifests strong views on the societal impact of today’s digital world. Witnessing a profound societal and technological transformation, contemporary digital and digitised society expects to be connected anywhere and at all times. We expect to constant access to social media and the Internet. Big Tech, advertising and marketeers compete for our attention. Eyeballing is meant to fulfil the instant gratification we aspire to. Our attention-span increasingly weakens, our hunger for information increasingly gets stronger, but less fulfilled as we are encouraged to view the next post.

Clickbait, the use of ‘likes’ and emojis underpins the online social communities and information-sharing, have introduced a transience of engagement, hunger for the next post on TickTock, Snapchat, Facebook, X…

Han argues that this has led to the demise of narration and the communal experience of stories, making place of information driven by data, often atomised, that lack ‘story arcs’ and a shared experience of story. According to the author, today’s world of marketing and corporate storytelling has become a world of “storyselling”, stripped of the power of narration and shared experience.

Deeply influenced by the German philosopher Walter Benjamin and his essay, The Storyteller, Han accentuates this argument. Benjamin did not witness the rise of the digital world. He witnessed rise of fascism and Nazism in Germany forcing him, as a Jew, to flee. To him, noteworthy stories were disappearing, being replaced by information that lack psychological connection.

"Every morning brings us news of the globe, and yet we are poor in noteworthy stories. This is because no event comes to us without being already shot through with explanation. In other words, by now almost nothing that happens benefits storytelling; almost everything benefits information. Actually, it is half the art of storytelling to keep a story free from explanation as one reproduces it. . . .

The most extraordinary things, marvellous things, are related with the greatest accuracy, but the psychological connection of the event is not forced on the reader. It is left up to him to interpret things the way he understands them, and thus the narrative achieves an amplitude that information lacks."

Narrative Fragmentation to Information Fragmentation

Han argues that in the age of the Internet and relentless appetite for information, we live in a state of hyperactivity and never-satiated hunger. In fact being disconnected from the constant information stream makes us even more relentless, feeling we might be missing something.

According to Han and Benjamin, this makes information only momentary, unable to transcend beyond time. Its inherent need for newness makes that impossible. The author goes even further. Experiencing the world of data-driven information and information as a representation of fact, whether fact is true of fake, not as narration, not only leads to narrative fragmentation, but a fragmentation of information itself. In other words, narration appears to have ceased to exist and information too vanishes beyond its moment.

"The value of information does not survive the moment in which it was new. It lives only at that moment; it has to surrender to it completely and explain itself to it without losing any time. A story is different. It does not expend itself. It preserves and concentrates its strength and is capable of releasing it even after a long time.”
Walter Benjamin - The Storyteller

What stories give us

Han argues that data provide us with facts and that in current society numbers talk for themselves. Data don’t explain anything nor do they have memory. They only provide us information and allow for correlations. Too often we interpret them as reality and accept their truthfulness. They drive our digital world and our digital truth, manifested on our phone screens.

We live in a world of Phone Sapiens, a digital panopticon devoid of narration, devoid of synthesis and personal and social memory. Social and self-knowledge have become one of bits and bytes and numbers in which narration plays no role.

Yet to Han, story and narration make us deeply human as social beings, encouraging reflection and nurturing our collective memory. Story allows us to imagine and reflect in and on a social context of shared values and mutual cultural understanding. They help us make sense of our world and imagine our humanity in it.

Han believes fervently that this is what narration gives us; a binding thread that links us as human communal beings. Today’s digital and AI world is becoming increasingly devoid of the power of shared narration, reflection and experience of time and space that Han believes, we seem to have lost,

Turning to AI, the author argues that AI knows or has no passion and is incapable of creating passionate narration. He argues that even philosophy as science has lost its original narrative nature and discursive character, being mired in bureaucracy. For him, philosophy too has lost its courage for narration, prominent in centuries of dialogues.

Considering Heidegger, Arendt, Freud, Proust and especially Benjamin, Han calls for the healing hand of narration that does not always need explanation, but achieves

“a psychological connection of the event that is not forced upon an individual, but allows for interpretation, allowing the narrative to achieve and amplitude the information lacks.”4

Lessons for Education?

The Crisis of Narration does not focus on education. Yet, aren’t there any lessons we can draw for education? Too often experienced by learners as boring and irrelevant, education lacks sense, relevance and meaning for them. Han’s short essay may give us some clues.

Education’s heavy focus on the imparting and standardised measuring of curriculum knowledge, even going as far as predicting grades, accentuates strengths and weaknesses of learners rather than their potential. This risks further accentuation through the entry of GenAI epistemic agents into the classroom. Focused on efficiencies and claiming improvement of learning outcomes (a valiant objective in itself) in education, this exponential technological evolution could easily reduce learners and their teachers to datasets and statistical predictions that serve efficiency and serve the system.

Yet unless carefully considered and embedded in narration that promotes curiosity and passionate exploration, this technological evolution risks losing what matters most: creating learning narrations between learners and their teachers in socialised contexts. Galvanising learning dialogue with peers, teachers, their learning spaces and cultural context, in human and even human:ai relationships, may create new opportunities for learning narration. These are opportunities I believe Han may well endorse.

Perhaps education can become the healing hand for narration?

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A Read for Our Time

Lyndsey Stonebridge’s beautiful book on Hannah Arendt’s thinking invites us on a journey into one of the twentieth century’s greatest minds and the importance she attributed to the act of thinking. In this masterful work, Stonebridge echoes Arendt’s thinking, highlighting how today’s violent unease, uncertainty and Zeitgeist would be all too familiar to the Jewish German-American refugee and influential and political theorist, who did not want to be labeled a philosopher.

Hannah Arendt: Refugee

Hannah Arendt (1906-1975) was a German-born Jewish philosopher and political theorist best known for her work on the nature of power, totalitarianism and the human condition.

During the rise of the Nazis, Arendt was forced to flee Germany after being arrested and released by the Gestapo. She escaped to Paris where she lived in exile. When Germany occupied France, she was forced to flee once more, ultimately arriving in America as a refugee. There she continued to live with as a stateless refugee for many years, before gaining US citizenship.

Hannah Arendt was a pupil of the German philosopher and Nazi-sympathizer Martin Heidegger, with whom she had a relationship while studying in Marburg. She also studied with Karl Jaspers, who was to have a profound influence on her life and became a close friend.

Her refugee status profoundly affected her life and thinking:

“We lost our home, which means the familiarity of daily life. We lost our occupation, which means the confidence that we are of some use in this world. We lost our language, which means the naturalness of reactions, the simplicity of gestures, the unaffected expression of feelings.”^[1]

Hannah Arendt: Influential and Profound 20^th Century Thinker

Hannah Arendt was a prolific thinker and author who disliked being labelled a philosopher, considering philosophy “to be the subject of Man”. Her concern lay with “men”: humanity and the human condition, identifying as a political theorist whose thinking was rooted in the plurality of humanity.

As a German Jew in exile, her experiences of persecution, statelessness and being a refugee deeply influenced her thinking and work. So too did the horrors of the Nazi regime, capable of the terrible act of the Holocaust, persecution and, the cruelty of fascist totalitarianism. Shaped by these experiences, her writing focused on totalitarianism, power, terror, exile, love, the human condition and above all freedom.

These themes resonate skilfully throughout Arendt’s writing and Stonebridge’s beautiful biographically inspired journey of thought and questioning with Hannah Arendt for a world in significant turmoil.

Lessons in Love and Disobedience for Our Unpredictable Times

Lyndsey Stonebridge, author of this beautifully written and profound book on one the 20^th century’s most influential political thinkers, “invites us to an urgent dialogue with our troubled present”. She calls on each of us to “think our way, as Hannah Arendt did, unflinchingly, loving and defiantly, through our own unpredictable times”.

Early on, Stonebridge highlights how The Origins of Totalitarianism (Arendt’s most famous work) rose to the top of the bestseller list, following 2016’s Trump election and Brexit results. The book saw a 1000-fold sales increase during the first year of Trump’s presidency. Arendt’s writings on totalitarianism warned us that although totalitarian regimes invariably fall, their thinking and Zeitgeist can linger and influence our relationship to the future. A warning that most certainly resonates today.

Reflecting on Arendt’s life and ideas, Stonebridge continues to draw lessons for a contemporary troubled world, inviting us to an “enlarged mentality”^[2], a fundamental notion for Arendt. She urged people to train and expand our imagination to “go visiting” and engage mutually with different perspectives and viewpoints.

We are Free to Change the World highlights how Hannah Arendt believed this to be the foundation of good judgement, a foundation that not only inspires but guides us through this wonderful read, encouraging us to widen our thinking and questioning.

Stonebridge, like Arendt, invites us to think; not what to think, but how to think. She highlights how Arendt believed thinking to be dangerous and revolutionary, not surprising given the time when she lived and the fascist and racist ideology that forced her into exile. To her, thinking is what brings us freedom, and a free mind gives us the power “to keep possibility alive”, a clear message of hope.

Important to Arendt was not only engagement in thinking, but the act of questioning to protect us from tyranny. Her 20^th century writing and thinking couldn’t be more apt for our time in which ‘thinking’ and ‘questioning’ are increasingly subject to the new paradigms of the rise of inorganic intelligence of AI versus a free human mind.

A Biographical Journey for Our World

The power of Stonebridge’s writing is heightened by weaving Arendt’s thinking and work into a biographical journey for our time. Unlike most biographies, its axis is Arendt’s profound thinking and great mind, which has resulted in a prolific compendium that resonates loudly today.

Hannah Arendt did not witness the technological (r)evolutions of the past decades, nor the rise of AI’s exponential strides, introducing new uncertainty into an already uncertain and fragile world. There is no doubt these rapid and exponential evolutions would have led to more urgency in her plea for nurturing a free human mind in dialogue with our troubled present to keep our possibility alive. An urgency and message echoed by Stonebridge’s with an enlarged mentality in this wonderful and highly recommended read.

This is what makes this book so unique: it transports us not only to Arendt’s mind, thinking and concern for humanity, love and freedom. It equally opens a window to Stonebridge’s mind, sensitivity and desire to keep possibility alive, deeply inspired and intertwined with Arendt’s love for humanity. It sends us a warning message and urges us to think and question for our time and our future.

Message for Education

Hannah Arendt considered education to be crucial for nurturing a love for the world. As well as being a prolific thinker and writer, she thought at several elite US universities.

Going beyond the boundaries of Stonebridge’s book, but given my engagement in and passion for education and learning, I could not omit a message from Arendt to Education, to add to my short discussion on this exceptional and profound read.

“Education is the point at which we decide whether we love the world enough to assume responsibility for it and by the same token save it from that ruin which, except for renewal, except for the coming of the new and young, would be inevitable. And education, too, is where we decide whether we love our children enough not to expel them from our world and leave them to their own devices, nor to strike from their hands their chance of undertaking something new, something unforeseen by us, but to prepare them in advance for the task of renewing a common world."^[3]

^[1] Hannah Arendt, “We Refugees” (1943)

^[2] Term used by Immanuel Kant, adopted by Hannah Arendt

^[3] Arendt, Hannah. "The Crisis in Education." The Humanities Institute, 1954, thi.ucsc.edu/wp-content/uploads/2016/09/Arendt-Crisis_In_Education-1954.pdf.

^[4] Adolf Eichmann (1906–1962) : high-ranking Nazi official and one of the Holocaust’s key architects. He orchestrated mass deportation of Jews, Roma, homosexuals, disabled people, political opponents to the regime and non-Arian people to the concentration and extermination camps. He was put on trial in Jerusalem in 1961.

Carla Aerts

First Published on LinkedIn January 29, 2025

Setting the scene

Rebecca Winthrop, Senior Fellow and Director, Center for Universal Education at the Brookings Institution reported some findings of what she heard at Davos. Link to here article here.

The discussion below, comments on three of her five takeways, regarding Neuroplasticity and AI in education.

Link to Rebecca's article http://tiny.cc/gf18001

Takeaway #1: Neuroplasticity and Manipulation

A comment from Daniel Barcay, Executive Director of the Center for Humane Technology, has stuck with me. He said something close to “I think the most beautiful thing about humans is neuroplasticity, but it also makes humans really easy to manipulate.” This dual nature of neuroplasticity lies at the core of why education is often targeted by oppressive regimes.

This comment couldn’t be more apt. Rather than unlocking a world of potential and possibilities for learners and teachers, the influence of oppressive regimes on education, does the inverse and manipulates their neuroplasticity aiding their turning into instruments of the regime. Yet, we should also recognize that even in non-oppressive regimes, education is not entirely void of manipulation, lacking in promotion learner agency. That, however, is a discussion for another time.

Daniel Barclay’s comment highlighted by Rebecca Winthrop also invites us to consider its implications in the world of AI.

For quite some time, AI has received significant attention in education and education research, especially in the context of personalized learning, where machine learning has and still is gradually replacing the rule-based algorithm. Personalized learning became the new promise for improved learning outcomes. Adaptivity and personalization became a new kind holy grail for education. Simply because the technology makes it possible?

This is where the intersection of neuroplasticity and AI merits deeper questions and discussion.

We are all unique learners with distinct learning needs and aptitudes and, most crucially, unique brains. This provided the perfect argument for the introduction of ‘personalized learning’. Let’s be clear, context allowing, good and experienced teachers have used personalized approaches in the classroom for years, without technology.

But t promise of AI-driven personalized learning became quite beguiling. I remember reading a report in 2015, published by the Word Economic Forum in collaboration with the Boston Consulting Group in 2015: New Vision for Education Unlocking the Potential of Technology[1] (note what is being “unlocked” here). The report championed the use of technology to not only to improve learning outcomes and develop higher order thinking skills. What I found rather staggering, was that it referred to, and recommended, the ‘closed loop’ instructional system served beautifully by technology. The alarm bells started ringing.

Serving the needs of closed loop instructional systems? What does this mean in practice? Too often adaptive and personalized learning technologies focused very narrowly on improving grades, relying solely on a ‘rote learning’ regimen. This may help memorization but doesn’t necessarily foster neuroplasticity. Although spaced practice is beneficial for learning, the approach of many an adaptive platform traps learners and teachers (when using adaptive teaching platform) in learning loops. These often amplify the learner’s struggles through repeated narrow practice rather than appropriate feedback and intervention – unless the good and practiced teacher intervenes. The goal? Passing the exam.

While machine learning has come a long way since 2015, it has also intensified the strive and amplification of personalization. The highly data-dependent approach has been combined with prediction, risking a rather deterministic defining of a learner’s ability and promoting the prediction of grades.

Is neuroplasticity’s beauty being developed or are we simply amplifying machine-led manipulation? If the focus remains on knowledge construction through curriculum adherence and too strong a focus on memorization, rather than application and self-regulation. Aren’t we missing the real opportunity?

The question remains open. Promising EdTech innovations continue to emerge, but in K-12, they are still too often retrofitted into systems that do not promote higher order thinking skills and undervalue learner agency. Without thoughtful implementation, AI’s predictive capabilities could easily stifle the beauty of neuroplasticity, boxing learners into their predefined expectations – their potential being predetermined by the algorithm, rather than nurturing their neuroplasticity and capacity to grow.

Takeaway #2: Education Is Fundamentally Different When It Comes to AI

Rebecca Winthrop highlights AI for good and its innovative use. e.g. to support the delivery of clean water to underserved communities, a super tool with meaningful goals - one firmly controlled by the adults.

Her discussion on educator-mediated vs direct-to-child use highlights the importance of retaining teacher agency in mediated use of AI in the classroom.

I would argue that there is and must be room for both. This is especially the case with the introduction of generative AI (GenAI) in the classroom and beyond. These technologies, though not yet ubiquitous in education, are increasingly become integral to life outside of school and society. They will even play a greater role in the workplace of tomorrow. The extent of their influence remains debated and uncertain, but one thing is certain Education needs to become Fundamentally Different when it Comes to AI.

And here is where neuroplasticity’s can flourish – if we allow it. The adult in the room should remain the mediator, but mediation itself must evolve. Learning needs to evolve beyond being the recipient of instruction and make room for more co-creation. Too often teachers are distanced from learning, being positioned as the disseminator of learning, rather than active meta-learners. This must change.

The introduction of GenAI in the classroom make this even more pressing. As an epistemic tool it has the potential to aid the development of knowledge, skills and agency. If used in collaborative and social learning contexts – rather than limited to the tunnel vision of personalized practice – AI can genuinely transform education and the how learners engage in learning.

This is why education cannot simply adapt AI to its current structure, nor can it stick to its current views; it needs a rethink for a human-AI world. That means ensuring that learners and their teachers can be the custodians and be in control of the relationship between human intelligence and artificial intelligence. This will be a fundamental skill for humanity’s future, one that will determine whether we merely survive or truly thrive.

Where should this start? With teacher-mediated (or rather, meta-learner and co-learner) experimentation in the use of GenAI in the classroom. This needs to happen in a safe, structured and intentional process, supported by relevant pedagogies in a dialogue that benefits both learners and educators[2].

Takeaway #3: Learning “AI Skills” Is Just One Piece of the Puzzle

Rebecca points to the growing emphasis on equipping young people in the use AI to meet workplace demands but argues that this is not just the endgame. The real goal must be to cultivate the ability of “learning to learn”. to empower young people to adapt to rapidly evolving technologies. After all, AI itself will soon look radically different.

This strengthens my argument that mediated and self-regulated use of GenAI and AI tools in the classroom is critical for learners and their teachers. If they are not able to engage as active co-learners, they will fall behind and at risk of suffering from skills atrophy, unable to adapt as technologies advance.

The time has come to see GenAI and AI, not as mere tools, but as partners in learning and teaching (co-learning). They must serve as co-mediators to ensure that learners can become the controlling human agent in the process of “learning to learn”, augmenting and augmented by the beauty of neuroplasticity – not manipulated by it, whether by the machine or the regime.

Final Thoughts

The intersection of AI and education presents immense opportunity—but also profound challenges. If we allow AI to determine learning pathways and predict learner potential, without human oversight and control, we risk undermining the very essence of what makes us human: our ability to learn, adapt, and think freely. But if we leverage AI as another co-learner rather than a controlling force, we can create an education system that not only prepares learners for the future but galvanises them to shape it.

The choice is ours.

[1] World Economic Forum, (2015), New Vision for Education Unlocking the Potential of Technology , Industry Agenda, https://www3.weforum.org/docs/WEFUSA_NewVisionforEducation_Report2015.pdf

[2] Note: The arrival of new LLMS that don’t require the bells and whistles such as deepseek, may also help bridge the inequality in access to education and learning. It could make the use of GenAI available to under-resourced contexts. However, the challenge to support minority languages and local context may not be solved that soon (topic for another post).

Werbach’s[1] podcast series focuses on Artificial intelligence and its promise to transform our world. This promise requires scrutiny, as AI’s potential cannot be reached without accountability and guardrail mechanisms, including governance, that ensure AI is deployed responsibly. The challenge of AI development is equal to ensuring its safe and trustworthy deployment, as we are already witnessing shadows that these amazing epistemic technologies can cast.

It was no surprise to see David Weinberger as the latest guest in this podcast series.

David is an American author, technologist and speaker, with quite a few other strings to his bow. His influential work explores how our ideas about knowledge, business and society are reshaped by technology, in particular the Internet and AI^[2].

His well-known quote: “The smartest person in the room is the room.”, encapsulates a central idea in David’s work: knowledge is no longer an individual attribute or privilege but resides in the collective intelligence of connected people and systems. His “room” represents the group, the internet, or collaborative environments that nurture and host diverse ideas and perspectives. With the rise of AI, the room has grown exponentially larger and continues to expand; its shifting walls are becoming increasingly indefinable, blurred and elusive.

The Discussion: Starting with a Question

The podcast introduced a fundamental question: why is considering the deep impacts of AI important to ask in the first place? Isn’t this a premature question to ask?

David highlighted that although his current writing considers whether and how AI might be shaping our thinking about fundamental things, the inquiry into considering its impact might be too early. Yet he feels it is a valid question to explore and engage in a way of thinking about it, especially since he doesn’t know the answer. His approach of exploring without knowing or reaching an outcome, gives us a sense of what it means to ask such profound questions. My ears were pricked.

Technology has deeply influenced our thinking across a vast spectrum of domains, disciplines, and societal transformation by changing how we view and deal with information. This influence has spread very quickly. Now, in the early beginnings of the Age of AI, exploring our relationship with information and its effects on our thinking is, to say the least, intriguing. This exploration becomes even more fascinating when we admit not knowing the answer to AI’s impact on shaping our thinking, while engaged in the speculation that AI is the next dominant technology. Even though current developments suggest the likelihood of AI’s technological domination, the answer to its impact on our thinking remains elusive.

A New Machine Paradigm: Beyond Human Generalization

In this fascinating exchange, Weinberger puts forward that large language models are already permeating our interactions with AI. More significantly: they have been designed to sound like humans and react to us like very smart persons. In short: they represent technological anthropomorphisms. This quality differentiates them from other machine learning developments. However, we are not interacting with a person; in fact, we are interacting with quite the opposite: a world of bits and bytes found in other computer technologies, presenting a human-like veneer.

For centuries humans have sought and aspired to generalizations as the foundations for knowledge, scientific endeavour and discovery. In our knowledge world, principles and general truths prevail. They are what humanity relies on to build knowledge and inform research and discovery.

It may not be that outlandish to propose that humanity needs generalizations to make sense of the world that would otherwise be impossible to fathom.

Not disputing the validity and importance of Laws of Physics, Newton or Einstein as examples of generalizations, David highlights that machine learning is leading us to a very different view of the world namely, that of the.

To illustrate his argument, the podcast’s guest refers to the use of machine learning applications in retinal scans research^[3]. Contrary to the generalizations that emerge from research( such as the link between cancer and smoking), what emerged here represents a completely different way of viewing the world, in this case the retinal scan and the eyeball. Using patterns and predictions, the machine discovered anomalies, variations or differences that human specialists could not detect. In other words, David argues that while humans typically look for what we have in common i.e. the generalization or universal, the machine reveals the opposite: what is particular, different, and therefore hard to detect.

The Capacity of the Machine

Already emerging in this new dawn of organic and inorganic intelligence is the capacity of machines to reveal particularities and variations that humans couldn’t detect on their own.

We may have become masters of creating the epistemic tools or agents that enable us to expose new truths of particulars that can identify and predict based on tremendous amounts of information. However, these present an order of magnitude that our limited brains cannot fathom, never mind hold.

Our generalizations served us well to date; the machine’s nous for revealing particulars relies on a new multi-dimensional capability that uncovers novel correlations through predictions. At times these predictions lead to “hallucinations”^[4], at others they reveal new and valid truths. Interestingly, hallucinations can be the direct result of generalizations in the data sets. These tend to favour or represent our human biases, too often stemming from the WEIRDness of the data sets, referring to the Western, Educated, Industrialized, Rich and Democratic populations generating the data sets used. This creates manifested bias.

David puts forward the argument that the machine is a black box, because our world too is a black box. This presents us with new challenges and opportunities.

The Power of the One versus the Many

No surprise that the dialogue eventually moves toward power dynamics, as relatively few people are involved in a technology that affects the vast majority, typically representing a very thin white layer on a multi-coloured cake. Rich and increasingly powerful corporations and autocratic governments dominate the AI landscape with their gigantic and expensive models. To counter this dominance, David calls for smaller models and new companies entering the field. On top of that, more regulatory control and governance over what the companies are allowed to do is necessary. These are by no means certain.

In Summary

Needless to say, the discussion in this podcast reached well beyond what I’m trying to highlight in this post. This reflection merely encapsulates what stood out for me personally. There is no doubt that my discussion sells the podcast and its presenter and guest short. To discover the full depth of the conversation, I recommend tuning in^[5].

What struck me most in the discussion was David’s highlighting of generalizations (universals) and how humanity relies on them, versus the manifestation and prowess of the machine for detecting the particulars. Somewhat of an oxymoron, these machines are fed our generalizations yet reveal the particulars we are unable to observe by ourselves.

Despite the human brain being the inspiration for AI development, it seems that our brains versus those of the machine have developed distinct minds of their own, with unique capacities and limitations that complement rather than mirror one another. Where these minds will take one another, and how the shape of our thinking will change resulting from this new intelligence relationship, remain an elusive answer to a very profound question.

^[1] Prof Kevin Werbach: Professor of Legal Studies and Business Ethics at the Wharton School of the University of Pennsylvania

^[2] Books include: The Cluetrain Manifesto, Everything is Miscellaneous, Too Big to Know and Everyday Chaos.

^[3] The research project in question was performed at Leeds University using deep learning techniques in machine learning to analyze retinal scans for identifying several eye conditions and research on the correlations between retinal anomalies and cardiac disease.

^[4] Term used in connection with AI referring to a response or contains that contains false or misleading information, whilst appearing plausible.

^[5] Podcast available on Spotify, Apple, YouTube and through several websites, including https://accountableai.net
Prof. Kevin Werbach’s The Road to Accountable AI: AI You Can Trust, podcast webpage.

Introduction

Having engaged in some thought experiments on Reality, Being and Existence: Metaphysics for Humanity’s New Dawn, I have been exposed to several philosophical discussions on reality and ontology, one over many, universals and particulars, realism, idealism, free will, space time and the question of the existence of time. Whilst each module has presented me with new insights and challenges, reflecting all of them in a short essay would not reflect sufficient depth.

Yet, seeking to demonstrate a reflection of my engagement in metaphysical challenges, I have decided to narrow my focus and apply my learning journey to the context of the virtual world of Generative AI.

In this short musing, I discuss the ontological status of Generative AI and explore whether Ancient Greek philosophical frameworks and Armstrong’s theory on particulars and universals can be applied to our modern AI era.

Whilst the thinking and writing in this short essay are mine, I have had the help from Claude Sonnet 3.7 in proofreading and checking spelling, grammar and syntax.

The Ontological Status of AI-Generated Entities: A conundrum?

Engaging with ontology and Quine’s^[1] paper: On what there is, I became increasingly drawn to considering our experience of the virtual world, and particularly the ontological status of Generative-AI generated entities.

Considering Quine’s exploration of Wyman’s distinction between things (entities) that exist and merely unactualized possibles, that only ‘subsist’ (e.g. the Pegasus example), I wondered whether Generative AI brings a new perspective to this argument.

To illustrate this, I propose presenting a new hypothetical character “Y-AI” who challenges both McX and Wyman, introducing Generative AI, an epistemic tool, to the discussion. Y-AI argues that the virtual world of Generative AI, with its neural networks and algorithms, cannot be compared to Wyman's "unactualized possibles." She asserts that, unlike Pegasus, AI-generated entities aren't defined or named prior to their generation and only become entities through the process of generation itself. Therefore, they can’t even be considered existing entities in as defined by Wyman.

Y-AI goes beyond Quine’s scepticism, rejecting the view that unactualized possible entities underpin Generative AI. Instead, she proposes a third ontological category: “unactualized virtual emergence”. Putting this seemingly paradoxical concept forward, she acknowledges that reality is unactualized, even – and especially – in the virtual world. It is after all “virtual”. Y-AI argues that AI entities only manifest through emergence dependent on human-machine (or machine-machine) interaction. It is only through this causal relationship between external triggers and the machine’s virtual processing, resulting in statistical prediction, that knowledge is generated.

Y-AI’s position aligns to the Occam’s razor metaphysical principle, shunning unnecessary entities, yet challenges whether asking whether AI-generated entities exist, is even meaningful. She would deem such an enquiry superfluous; considering entities exist only as temporarily instantiated virtual statistical predictions, rather than persistent objects or entities with identity.

Considering the ontological status of Generative AI and the nature of AI-generated entities raises the question whether Classical Greek philosophical frameworks might be relevant. Can we apply the perspectives of Parmenides and Plato to the modern context of the Generative AI-era? Do their positions on one over many have a place in this discussion?

The Classical Greek Frameworks and Generative AI:
Parmenides’ Sail and Plato’s Form

Considering Parmenides'^[2] Sail metaphor in the context of a Generative AI system, one could argue that, like the Sail when not all partake of it, the GenAI system does not remain the same. After all, the system constantly changes.

The system constantly learns through reinforcement learning algorithms, neural networks, and the reweighting of data in its sophisticated models (the system’s structure). It evolves through user interaction and feedback loops from human-machine dialogue, refining the generation of its outputs (the behavioural level of the system, realised through the system’s code implementation).

Analogous to the Sail changes resulting from shifts in those partaking of it, applying Parmenides' metaphor to GenAI is reasonable and may help position AI within metaphysical frameworks. This can be extended by considering Plato’s Form and whether the Allegory of the Cave^[3]may strengthen the proposal for positioning AI within these frameworks.

In The Republic, Plato introduces the Form as an abstract entity. This is only accessible and comprehensible to philosophers. He illustrates this in the Allegory of the Cave, in which prisoners mistake shadows for reality.

Viewing modern GenAI as an entity that is incomprehensible to users and increasingly so for its developers, the assertion could be made that a Generative AI system is not unlike a Platonic Form. Users experience statistical predictions based on patterns embedded in the system. These could be considered imperfect representations, like the shadows. We may mistake these outputs for reality. Yet they are merely shadows produced by sophisticated data models and the machine’s structure and processes, resulting from the user partaking in a dialogue with the machine. All she receives is a virtual shadow of its abstract Form.
The analogy of Plato's concept of Forms or abstract universals from ancient Greek philosophy to the Generative AI machine, offers a framework for the metaphysical positioning of AI in the modern world. Yet this could be enhanced by a deeper exploration of the problem of particulars and universals.

Generative AI and the problem of particulars and universals

Continuing with Plato’s Theory of Forms, placing Forms outside of the world of experience. The question arises whether this can serve effectively as a metaphysical framework for AI and in particular Generative AI.

Our analysis draws on Armstrong’s^[4] Theory of Universals, which discusses universals (Plato’s Form being a universal) as instantiations of particulars and claims that without such instantiation universals can’t exist.

To consider this in the context of Generative AI or AI, we need to extend Armstrong’s theory to the virtual world, in which particulars exist, instantiating the universal: intelligence. To achieve this, we need to consider GenAI systems and their particulars and accept that these possess Armstrong’s essential qualities that enable instantiation of the universal intelligence. These possess unique criteria and distinct properties (just like the rose being red). Moreover, the virtual qualities have causal properties, despite lacking spatial and temporal attributes. The particulars in the AI systems transform patterns using statistical prediction that result in outputs that did not exist previously. These influence human behaviour and knowledge. This reflects the instantiation process required for the universal intelligence.

To substantiate the argument of the instantiation of this universal by virtual particulars, we need to delve into the workings of the machine. These rely on a hierarchical exchange of particulars, i.e. its algorithms, neural networks as well as trained data models (the system’s structure), its code (its implementation level) and interaction of inputs and outputs (its behavioural level). This hierarchy of particulars’ processes lead to the universal’s instantiation.

However, the virtual nature of AI presents a problem for Armstrong’s theory. The universal intelligence can be repeatedly instantiated by a hierarchy of distinct particulars whilst keeping its identity: ‘intelligence’. This challenges Armstrong’s universal particular relation, implying immanent universal in the particulars themselves, rather than transcendentally sitting above them, where both Armstrong and Plato would situate them.

This raises the question whether an immanent universal can even be instantiated in the virtuality of AI. Whilst the plausibility of instantiation may be questionable, we can consider the virtual nature of a universal as representing its relation to the particular within a designed and defined virtual system. Its artificial property can be considered as Armstrong’s state of affairs.

By extending Armstrong’s theory to accommodate virtual particulars in Generative AI systems, our exploration reveals the plausibility of particulars and universals in virtual contexts and offers a new philosophical framing of universals in relation to AI. This framework demonstrates that instantiated universals can transcend the traditional physical boundaries of Armstrong’s theory, existing immanently within virtual systems and their particulars.

Conclusion
This discussion has explored the ontological status of Generative AI. It has also explored whether Ancient Greek philosophical frameworks can be positioned in the modern context of Generative AI, focusing on Parmenides’ One over Many and Plato’s Form. Having argued that these frameworks remain relevant in our AI era, we have extended our discussion to Armstrong’s Theory of Universals. This has led to highlighting the feasibility of considering particulars and universals in virtual contexts, as virtual entities.

By raising these arguments, I wanted to represent some of the learnings that this course in Metaphysics has allowed me to explore and apply to our modern AI era.

Bibliography

Armstrong, D. M., "Selection from Universals: an Opinionated Introduction," in Crane, Tim and Katalin Farkas, eds. Metaphysics: A Guide and Anthology. Oxford: Oxford University Press, 2011, pp. 235-249.

Course Materials and Discussion Fora in On Reality, Being and Existence an Introduction to Metaphysics, https://hilary2025.conted.ox.ac.uk/course/view.php?id=88, [accessed from 15 February – 1 April 2025].

Crane, Tim, and Katalin Farkas, eds. Metaphysics: A Guide and Anthology. Oxford: Oxford University Press, 2011.

‘David Malet Armstrong’, Wikipedia (2023), https://en.wikipedia.org/wiki/David_Malet_Armstrong [accessed 28 February 2025].
Discussion Fora in On Reality, Being and Existence an Introduction to Metaphysics, participants’ discussions, https://hilary2025.conted.ox.ac.uk/course/view.php?id=88, [accessed from 15 February – 1 April 2025].

Plato, "Selection from Parmenides and Republic," in Crane, Tim and Katalin Farkas, eds. Metaphysics: A Guide and Anthology. Oxford: Oxford University Press, 2011, pp. 227-234.

Quine, W.V., "On what there is," in Crane, Tim and Katalin Farkas, eds. Metaphysics: A Guide and Anthology. Oxford: Oxford University Press, 2011, pp. 179-193.

Rodriguez-Pereyra, Gonzalo, 'Nominalism in Metaphysics', Stanford Encyclopedia of Philosophy (2015) https://plato.stanford.edu/entries/nominalism-metaphysics/ [accessed 26 March 2025]

‘Universals’, Internet Encyclopedia of Philosophy https://iep.utm.edu/universals/ [accessed 10 March 2025]

Weinberger, David, 'The Rise of Particulars: AI and the Ethics of Care', Philosophies, 9.1 (2024), 26 https://www.mdpi.com/2409-9287/9/1/26 [accessed 14 February 2025].

^[1] Quine’s On what there is: T. Crane and K. Farkas, Metaphysics: a guide and anthology, (Oxford, Oxford University Press, 2011) pp. 179-192.

^[2] Plato ‘Selections’ pp. 228-230, ch. 19.

^[3] ‘Plato Selections from Parmenides and Republic’ in Tim Crane and Katalin Farkas, eds., Metaphysics: A Guide and Anthology (Oxford: Oxford University Press, 2011), pp. 230-234, ch. 19.

^[4] Armstrong’s Selection from Universals: T. Crane and K. Farkas, Metaphysics: a guide and anthology, (Oxford, Oxford University Press, 2011) pp. 235-238, ch. 20.
David Malet Armstrong, Wikipedia (2023), https://en.wikipedia.org/wiki/David_Malet_Armstrong [accessed 28 February 2025].

Image by Pawel Cherwinski

Carla Aerts

Taking organisations, leadership & startups into AI & Futures of Education | AIEd Strategy | EdTech | Thought Leadership | Policy | Strategic Innovation & Research | Innovation | Transformation | Facilitator | Speaker | Mentor |

March 15, 2025

Introduction

The world many of us live in is pretty WEIRD. Academic research, societal structures, medical interventions and education systems are all profoundly shaped by this WEIRDness. The acronym WEIRD[1] stands for:

W: Western E: Educated I: Industrialized R: Rich D: Democratic

It represents how the Global North and especially the West has disproportionately influenced world order, scientific progress, and economic development, ignoring the non-WEIRD people, their cultures, endeavours and societal structures. Despite evolving global dynamics, WEIRD perspectives remain dominant in technological innovation. The generative AI revolution is no exception.

LLMs underpinning GenAI, are predominantly built on Western Internet data and data models, algorithms and computational paradigms, heavily influenced by the “BigAI” players in Silicon Valley. Even as we witness a significant emergence of Chinese players, their systems still largely perpetuate WEIRD world views, potentially amplifying existing cultural, racial and societal biases.

The WEIRDness of GenAI presents significant challenges, and opportunities, for Education and equity and equality. While tackling these issues isn’t straightforward, this discussion will examine the WEIRD paradigm in a global context, highlight its cultural biases and implication for AI development and the LLMs, and explore the consequences for education as these technologies increasingly enter learning and teaching environments. We’ll consider how the introduction of these technologies can create new divides that could threaten education as a fundamental human right, but equally bring new opportunities that need actionable solution to help ensure AI advances educational equity rather than undermine it.

The WEIRD Paradigm in Global Context

WEIRD (Western, Educated, Industrialised, Rich and Demographic), a framework developed by Joseph Heinrich, has shaped our research shaped and knowledge, while “representing a rather thin slice of humanity’s cultural diversity”. The West and the Global North have been the drivers of this trend, too often ignoring cultural diversity and representation. It suffices to say that this results in considerable bias.

WEIRD dominance has significantly impacted cultural representation and diversity. A good example of this is in pharmacology and medicine, which only recently have started to consider ethnic diversity in the development of medicines and medical interventions. This example is only the tip of the iceberg in how WEIRD has had profound societal and cultural impact. The argument that our WEIRD view of the world, has led to a social colonization most certainly isn’t far-fetched.

Whilst we are witnessing slow change, the WEIRD frameworks and ensuing trends has ignored humanity’s rich cultural diversity and expression for far too long. The developments AI and, especially, GenAI sadly are only a reflection and continuation of this trend. After all, LLMs to date rely on Internet content, reflecting languages and cultures that are predominant on the World Wide Web. Several minority languages are supported by LLMs’, yet far too many local languages and cultures are not represented, perpetuating WEIRD in GenAI.

Cultural Bias and Its Implications

Most of you reading this article, need little introduction to the speed of evolution we have witnessed in the development of GenAI. Daily news on new versions of ChatGPT, Claude, Gemini, Perplexity, Midjourney and an increasing set of LLMs is challenging to keep up with. The past years of Internet and Social Media developments and ensuing social evolution, are set to pale into insignificance compared to what we are witnessing in AI and GenAI developments.

It is no secret that Silicon Valley has been the most significant driver of these technology developments and their societal impact. Although China is a significant player in GenAI developments and Europe is a small entrant, it is fair to see that the WEIRD dominance in technology development remains overwhelmingly US-influenced, resulting and Anglo-American cultural bias and dominance that reinforces inequality and unequal representation. The Internet may be vast, the slice of humanity’s cultural diversity representation is getting considerably thinner.

Bias in AI and algorithmic amplification of bias are no secret. It is subject of significant concern and discussion, the detail of which is not considered in this article. What is considered in this discussion, is its impact on cultural representation and the absence of indigenous, tribal and native cultures in GenAI support.

This absence presents us with a feedback loop between biased systems and societal outcomes, that is only set to grow and reinforce WEIRD-ness, creating a new ‘digital divide’.

Generative AI and LLMs: Examining WEIRD Origins

To understand LLMs’ weird origin, let’s have a short glimpse at their history. Large Language Models are the result of decades of natural language processing research. The field witnessed a fundamental breakthrough with Google’s development of the Transformer architecture in 2017. This allowed models to process language much faster. This innovation led to the birth of OpenAI’s GPT (Generative Pre-trained Transformer), that led to an explosive arrival of ChatGPT in 2022, bringing a paradigm shift, introducing conversational AI to the public. Other models such as Claude, Llama, Gemini (predecessor BARD), and Mistral were quick to follow. The continuing developments and evolutions of these technologies, the training of language models and refining of alignment techniques, have turned these technologies into powerful tools. They can generate human-like text and are even improving their reasoning capabilities across multiple domains.

LLMs rely on training data, typically harvested from the Internet and therefore representing its demographics and cultures. The Internet provides trillions of data points needed to train the models. But what about the demographics and cultures that aren’t represented in the data? They will be absent from the training data and subsequently from the Language Models.

The corporate concentration of AI development (BigGenAI) doesn’t preoccupy itself absence of cultural and language representation. They are responsible to their shareholders the growth of their solutions, so minority representation is not really their concern. Their argument: “There just isn’t data available to do this”.

Add to this problem the technical architecture decisions that rely on and encode the WEIRD assumptions, and little further explanation is needed. The problem is not going to be solved quickly.

The Educational Divide: Problems and Outcomes

Amplified WEIRD dominance and bias will continue and create societal impact and division to which education is not immune.

Educational AI applications will reflect this bias; minority, indigenous and native language and dialects will be left wanting. The same applies to cultural relevance and reference points in contextual examples and curricula support. Even where infrastructure and technology access allow for the introduction of GenAI in learning environments – too often still a fundamental issue - the crucial importance of context and cultural relevance won’t be reflected. The cultural bias and WEIRD dominance in data models and technical architectures will be amplified, affecting contextualised curricula delivery and assessment.

Both teachers and learners will lack resources and relevant support to develop the skills needed to be the citizens the AI era will need. This will lead to an AI-divide, not only in education but in future opportunity as these teachers and learners will be left behind.

What can we do to hold BigGenAI to account? The challenges are considerable. The ‘black box’ makes AI transparency hard and the lack of insight in algorithmic and neural network behaviours is increasingly limited. Add to that the above-mentioned profit motives of these tech giants, educational equity gets quickly demoted on their agenda.

Regulatory frameworks – even with the EU AI act and Data legislation, equally are still also reliant on the WEIRD views of humanity and don’t tend to take these considerations into account, leaving the BigGenAI players at liberty not to engage with these issues.

Impact on Education and the Right to It

United Nations’ SDG 4[2] stipulates ensuring inclusive and equitable quality education and promotion of lifelong learning opportunities for all by 2030. The achievement of this goal is increasingly unlikely.

This is not solely dependent on access to infrastructure and resources but is also due to an increasing and endemic shortage of qualified teachers. Most acute in the Global South, it is no longer solely a Global South problem. Adoption of AI in Education, not as a teacher replacement but supporting teaching and learning challenges is becoming more urgent. Yet, it is exactly the areas where teacher shortages are most severe that are most likely to be unable to reap the benefits of AI integration into education. This will exacerbate inequality and inequity and increase the competency- and skill-gaps teachers and learners face.

Several local, ethnic minority and indigenous initiatives have begun[3]. Yet it is unlikely they can move quickly enough or gain sufficient data access to make their impact felt in education. The need for diversity of knowledge can no longer be ignored, yet it will require considerable mobilisation and pressuring to secure BigGenAI support and expertise to provide solutions for equity in education and opportunity, leaving WEIRD frameworks behind.

From Challenges to Opportunities

To move to solutions, considerable changes in technical approaches need to be considered. These include data diversification strategies and alternative model training methodologies. These strategies and approaches need to be informed by cultural enquiry and auditing frameworks for GenAI. Without these, the above can’t happen.

Solving the challenge requires more than BigGenAI support and mindset change. Global regulatory and governance frameworks will need adapting and will be instrumental for solutions. These will require not only educational technology standards and regulation but will also demand investment for diverse AI development. Where the latter will come from, remains a very open question.

Current educational institutions’ response to AI varies significantly and, in many cases, sees levels of anxiety around AI integration into school and education institutions’ life and modus operandi. AI literacy is one of the main challenges that keep raising its head and needs solving. Educators are often not ready, nor are appropriate pedagogical approaches and the affordances of GenAI sufficiently considered.

We can’t just bring AI into the classroom, without changing what happens in it and how. Retrofitting to today’s classroom paradigm will not work and will result in failure. New pedagogies are needed as this is not solely a question of AI literacy and technology-led integration, Supporting and developing agency and ownership for educators, allowing them to encourage learner-agency and develop empowerment strategies to create a sense of AI ownership that relies on cultural relevance will be needed.

When it comes to local knowledge and its preservation, an additional challenge as well as opportunity is introduced that will need addressing. This requires relevant skillsets and teacher education, that not only focuses on curriculum, but the ethical and safe use of AI, focus on care and emotional wellbeing supported by cultural relevance. It will also require insights and wisdom of communities and their elders.

Realising this will aid the transition from problem to opportunity.

Conclusion

The explosion of GenAI will create new societal paradigms and profoundly change the world and the role of humanity in it. Education can no longer sit on the sidelines. Yet, when it comes to addressing equity and equality in education, these powerful tools and technologies are lacking. Support for minority languages and cultural relevance is lacking as current reliance of data and training of language models rely on and are informed by WEIRD frameworks favouring a representation of humanity, that prioritise its majority.

This reliance exacerbates the challenge of integration of GenAI and AI in education to promote equity and equality. It favours the WEIRD demographic, whilst ignoring indigenous people, ethnicities, native cultures, languages and dialects. Unless we can address this challenge comprehensively in co-creation and collaboration with and the support of the BigGenAI players, it is unlikely that the challenge can turn into an opportunity for education to be the catalyst for an equitable society. A society in which diversity can thrive and benefit the whole of humanity with equal access and opportunity, serving global community.

Very short reading List

Henrich, J., THE WEIRDEST PEOPLE IN THE WORLD, How the West Became Psychologically Peculiar and Particularly Prosperous, Harvard University, accessed 2025, https://weirdpeople.fas.harvard.edu/qa-weird

Indigenous Representation in AI: 21st Century Implication, A view of diversity and discrimination in AI Systems, accessed Feb 2025, https://www.theindegenous.org/indigenous-representation-in-ai-21st-century-implication

United Nations, The 17 Goals, Sustainable Development Goals, accessed Feb. 2025, https://sdgs.un.org/goals

In addition, many an AI newsletter, Andrew Maynards – The Future of Being Human, Ethan Mollick, et all.

Note: Proofread by Claude Sonnet 3.7

[1] Acronym coined by the anthropologist Jospeh Heinrich of Harvard University. He developed the WEIRD framework to raise people’s consciousness about psychological differences and highlight that WEIRD frameworks represent a rather thin slice of humanity’s cultural diversity. For Henrich WEIRD accentuates the sampling bias present in studies conducted in cognitive science, behavioural economics, and psychology.

[2] One of the 17 UN Sustainable Development Goals to be implemented by 2030, but unlikely to be realized. https://sdgs.un.org/goals

[3]nbsp;Example found here:nbsp;Indigenous Representation in AI: 21st Century Implication,nbsp;A view of diversity and discrimination in AI Systemshttps://www.theindegenous.org/indigenous-representation-in-ai-21st-century-implication

When discussing AI with education policy makers and education leaders during a visit to New Brunswick, I proposed The Art of the Question. What did I really mean? This question surfaced during a workshop. I sought to elevate the Generative AI discourse, beyond a simple discussion on prompt engineering.

Instead, I highlighted how the Age of Generative AI demands a Socratic transition in education, moving from just knowing the answer to an ability to formulate the question. Such a proposed transition requires new pedagogical models. I suggested dialogic pedagogies[1] to support learners and teachers in developing skills for meaningful human: machine interaction, reliant on the Art of Questioning.

Although my talk in New Brunswick focused on education, The Art of the Question extends far beyond the classroom. Generative AI and machine intelligence are becoming ubiquitous in the workplace, creating challenges and opportunities that demand deeper questioning. As we increasingly collaborate with co-agents and co-intelligence in professional life, critical questioning aptitude becomes essential, whether the technology moves beyond prompt engineering or not.

Moreover, AI’s growing societal impact calls for more profound reasoning about what it means to be human in a world of human: machine co-intelligence, a world in which machine capability easily surpasses our own, unless we become the questioning agents who actively shape humanity’s place in this new reality.

The Art of the Question: Necessitating New Pedagogical Models

Education assessment and exams remain focused on knowing the answer rather than developing the ability to formulate the question. In most education systems, knowing the answer demonstrates a level of knowledge acquisition and mastery. These systems’ objectives and measurements focus on the correct answer as a knowledge indicator and benchmark.

Whether formative, summative or high stakes, mainstream assessment modes and models are often instruments associated with instructional pedagogies, and in many cases, rote learning.

The instructional pedagogical model promotes gathering and memorizing of knowledge. It tends to overlook the development of metacognitive and self-regulation skills that encourage reflection, develop learning strategies, nurture understanding of how learning happens and promote learner agency. The teacher’s imparted knowledge, the textbook or curriculum resources are unquestionable. The objective? Getting the answer right. Those who achieve the highest number of correct answers, fare the best and receive the highest merit, leaving behind learners who have more questions than answers and seek discovery in learning.

But what about the ability to Ask the Question? Isn’t asking the question a demonstration of curiosity and engagement that ultimately lead to knowledge acquisition and application?

Humans possess an innate ability to ask questions. We are curious creatures who seek discovery, a characteristic most observable in small children. When discovering the world, they never cease asking: “Why?”. What happens to this curiosity and their continuous questioning, their way of figuring things out? It soon evaporates when they enter kindergarten or school.

In these learning environments, the focus shifts from questioning to knowing the answer and too often, questioning is discouraged. The answer becomes the yardstick, the holy grail in education. We strive for ‘knowing, knowing more and more, and priding ourselves on what we know’. The ‘how’ is put aside as education systems emphasize measuring and benchmarking knowledge. They ignore children’s innate curiosity and questioning abilities – essential skills for problem-solving, tackling challenges and gaining the insights and know-how to navigate their world.

Rebecca Winthrop’s and Jenny Anderson’s book: The Disengaged Teen[2], reinforces this perspective, exploring how rigid education systems result in teenage disengagement. The book highlights how “the discovering learner” - one who actively engages in learning, through questioning and connecting ideas - becomes the agent of her learning and education. The authors discuss that discovering learners fare better than high achievers, who excel in the test. They urge education systems to prioritize and implement this discovering learner model.

Although this article cannot explore their work in greater depth, Winthrop and Anderson convincingly argue how curiosity and discovery - second nature to small children - must become the bedrock for effective and engaging teenage education. Current educational approaches unfortunately have eroded these critical elements of engaged learning and agency.

Socrates[3] , the ancient Greek philosopher did not resort to writing but is said to have engaged in dialogic reasoning with his students. His philosophical dialogues, recorded and represented by Plato, started with a question. His engagement with students relied on question and answer. Scrutinizing the answer Socrates would soon throw a new gauntlet, i.e. another question, inviting reasoning, connecting ideas and dialogue. His approach gave rise to the term Socratic method.

An ancient Greek philosopher’s method is now often quoted in models for education using dialogic pedagogies[4], re-emerging in our contemporary era of AI and humanity’s highest technological achievements to date.

As Generative AI finds its way into education, discovery-based learning and assessment that leverages the power of the question across multi-modal experiences and environments, should be prioritized. Depth of questioning and deepening of enquiry interacting with Generative AI, need honing and scaffolding to augment critical thinking and avoid cognitive and skills atrophy[5] that would result from over-reliance on AI and non-critical questioning. It would erode human agency and the development of reasoning and critical thinking, vital for the AI era.

Schools, colleges, and universities must foster and equip learners with this critical skill that extends far beyond the classroom walls. Innate in the youngest learners, enquiring children, the art of questioning needs fostering and encouraging. This extends to professional environments. Here, employees increasingly collaborate with AI systems in transformed workplaces, augmented by technology. In these settings, the ability to ask incisive, thought-provoking questions is no longer solely an academic exercise, but becomes a fundamental professional competency that supports discovery, drives innovation and facilitates problem-solving through human: machine collaboration.

The Art of the Question: Beyond the Classroom to Professional Life

Our professional life and occupations are increasingly mediated by AI systems. As AI increases its foothold in education, its presence in the workplace is fast gaining ground. From process automation and task management, marketing strategies and campaign planning as well as content creation, AI has moved into research and the development of the life-sciences. Its potential and application in medical and clinical applications, augmenting diagnosis among others, is progressively influencing healthcare. The ever more rapidly evolving presence of AI technologies often outpaces leadership understanding and employee skillset.

The arrival of Generative AI in the workplace has triggered a new transformation that the workplace and its stakeholders are embracing at varying speeds. Whilst the early adopters and the AI champions claim rapid acceleration of its presence, the reality of that presence may prove somewhat different. Skillsets are often one of the main problems. Yet it cannot be denied that business and the workplace increasingly rely on new modes of interaction with the machine. The adoption of Generative AI, necessitates embarking on new modes of collaboration, engaging in a dialogue with a new form of inorganic intelligence, as a co-worker or co-agent. This relies on questioning (heavy use of prompt engineering), but with a deepening and critical lens, refining the question for tackling challenges and problem solving.

The evolution of AI’s presence in the workplace is evolving towards a deeper reliance and collaboration with this co-intelligence, creating new modes of collective intelligence that are believed to drive and enhance the workplace, its productivity and output. Whilst it is difficult, even for the experts, to predict this evolution, it is widely accepted that these models of co- and collective intelligence, will increasingly rely on the ability of humans to evolve with it and pivoting in their working life.

The career as we have known and have aspired to, is becoming a thing of the past. A career path, carving out career development and evolving into promotion, is becoming increasingly rare. It is set to morph into cycles of employment with times out of work, but evolving technologies and workplace or business challenges demanding new approaches and evolving skillsets. These employment cycles are equally set to be diminishing due to AI automation and presence in the workplace, making the relevant skillsets and Art of the Question even more important.

Those who thrive in these scenarios, are human agents with continuous learning and adapting skill sets that the workplace will demand of them, with self-directing learning skills. The Art of the Question and critical engagement in problem-solving, formulating and honing this skill will support their workplace endeavours. Rather than being subject to skill-erosion and cognitive decline as the machine outpaces humans, this will be critical for employees to become and remain fully-fledged human agents, critically harnessing the potential and the power of the machine for good.

Whilst the workplace is a strong focus in the Generative AI discourse and its drive, it is important to recognize that we are faced with questions that by far exceed the workplace. These concern societal challenges, world instability and uncertainty that is set to increase, climate change being a key cause and contributor. Generative AI’s impact on society and the world, will increasingly rely on our relationship with this artificial and inorganic intelligence necessitating honing our critical questioning skills.

The arrival of AGI[6] may be less or more imminent. After all, experts are very divided on this AI development. We may not be able to prepare ourselves sufficiently for this exponential AI development. Yet, engaging critically in the Art of the Question, supported by Generative AI (and AI) as it evolves, will be vital for us to prepare ourselves for the not yet understood manifestation and potential of this AI (r)evolution that will present new profound questions for humanity and the world. Ensuring the human in the loop as a critical agent, in the deployment of an inorganic intelligence that is set to outpace ours much further, and be fully independent will rely on our ability to ask the relevant questions to establish a meaningful and human-centric co-existence with this unknown artificial intelligence entity, that may or may not arrive sooner rather than later.

The Art of the Question: Questioning for Society and an AI World

The Art of the Question can by no means be considered in isolation of education and the workplace as vehicles and environments for Generative AI and AI. AI is ubiquitous in our smartphones, social media, streaming services, online retail, marketing etc. Its ubiquity is already so enmeshed in daily life, and becoming increasingly so in less technologically advanced contexts.

The presence of AI in our daily life and the rapid progress of Generative AI, necessitates a third approach to the Art of the Question. That is, we must question the use of AI and its impact on society, the world and humanity itself. AI will help us solve fundamental challenges to our world, whilst creating new profound challenges and conundrums for humanity, impacting on climate, the workplace, cultural values and beliefs, as well as impacting our daily lives.

How can we equip ourselves with the profound societal transformation that AI is bringing and will exponentially bring? Can we ask ourselves the questions with the relevant depth of questioning how to address societal challenges? Have we got sufficient imagination and questioning aptitudes to explore and discover the exciting opportunities these technologies bring?

How can we make use of Generative AI to help us navigate both challenge and opportunity, truth and falsehood, geopolitics as well as citizenship? How can we leverage these technologies to ensure we question and address human-centricity and -agency in an evolving dialogue with the machine, keeping the human in the loop?

The power and negative potential of these technologies, their geopolitical influence and weaponization capabilities in which the distinction between truth and falsehood evades us, as well as humanity-induced environmental and climate issues we face, do throw down a gauntlet. It is one that demands ongoing questioning of ourselves as human beings that will live alongside machine intelligences that may exceed our own.

In short, what are the questions we should ask ourselves and how do we avoid atrophy in questioning?

Conclusion

The ability to ask ourselves these profound questions in dialogue with the machine to solve fundamental societal challenges, is perhaps more acute than ever. It will be required and need to develop throughout our lives from early childhood through school, to further and higher education, learning in and adapting to the workplace and life in our communities and fast-changing world. We by no means have the answers but need to start engaging with The Art of the Question to gain the relevant knowledge and skills to formulate them.

[1] Dialogic pedagogies emphasize the power of classroom dialogue and interaction for foster learning, thinking, reasoning and problem-solving, encouraging teachers and learners to engage in meaningful dialogue and joint exploration of ideas, turning dialogue into a co-learning experience. The term Oracy is also often used in this context.

[2] Anderson, J., Winthrop, R., (2025), The Disengaged Teen: Helping Kids Learn Better, Feel Better, and Live Better, Crown Publishing Group, New York, ISBN-10: 059372707X

[3] Socrates, Athenian philosopher lived c. 470-399BC. He is often considered to be the founder of Western Philosophy. Not in favour of the written word, no texts remain but his thinking is known through posthumous writings of his students Plato and Xenophon in the form of dialogues, giving rise to the term ‘Socratic method’ or ‘Socratic dialogue’.

[4] Dialogic pedagogies emphasize the power of classroom dialogue and interaction for fostering learning, thinking, reasoning and problem-solving, encouraging teachers and learners to engage in meaningful dialogue and joint exploration of ideas, turning dialogue into a co-learning experience. The term Oracy is also often used in this context.

[5] Cognitive Erosion: Refers to the decline of mental functions such as memory, attention and executive functions. Skills Atrophy refers to a loss of skillset and knowledge due to disuse and practice.
Both are believed to be the likely result of the lack of friction in Generative AI. Unless the Art of the Question and the positioning of this powerful technology in education, the workplace and its impact on society is carefully considered, the risk of these occurring is significant.

[6] AGI or artificial general intelligence refers to a hypothetical form of intelligent machines or systems that possess the ability to understand and learn any intellectual task that a human can perform. Whilst still a field of theoretical research, AGI developers seek to create a highly autonomous system that outperforms humans at tasks they currently excel in compared to the machine. This type of artificial intelligence is believed to be capable of performing a range of cognitive tasks comparable and even exceeding the performance of humans. The estimated arrival of this AI evolution is topic of expert debate and disagreement.

May 10, 2024

Having been rather intrigued by the concept and the nature of the false positive, I have been doing some digging and would love comments from those who know Hannah Arendt's work much better than I do (I don't, but getting slowly into it).

And living in the age of the LLMs and Chat*, I did some exploration in English and asked three Chats* to tell me how Hannah Arendt would describe the false positive, or perhaps more appropriate - how would she consider it?

Calling those who know her work to comment on whether I received a false positive on the below, hitting the ball back, as truth and false with and from the engine are such a hot topic of discussion.

Dixit Claude

Hannah Arendt, a renowned political philosopher, might have explained the concept of a false positive using her ideas about truth, knowledge, and the human condition. Here's an attempt to explain false positives in her style:

In our quest for knowledge and understanding, we often rely on various methods, tools, and systems to help us discern truth from falsehood. However, these very systems, designed to illuminate reality, can sometimes lead us astray by presenting us with false positives.

A false positive, in its essence, is a deceptive affirmation – a claim that something is true or present when, in fact, it is not. It is a manifestation of the inherent fallibility of our human-made systems and the limitations of our knowledge.

In the realm of science and technology, false positives can arise from the imperfections in our instruments and the boundaries of our understanding. A medical test might indicate the presence of a disease where there is none, leading to unnecessary anxiety and treatment. A security system might sound an alarm, mistaking an innocent passerby for an intruder, causing unwarranted suspicion and fear.

But false positives are not confined to the technical sphere alone. They can also emerge in the realm of ideas, beliefs, and judgments. When we are too eager to confirm our preconceptions or too hasty in our conclusions, we risk embracing false positives – affirming notions that, upon closer examination, prove to be illusory or misleading.

The danger of false positives lies not only in their immediate consequences but also in their capacity to distort our understanding of reality. By leading us to believe in the presence of something that is absent, they can cloud our judgment, misguide our actions, and hinder our ability to confront the truth.

To navigate the perils of false positives, we must cultivate a spirit of critical thinking, a willingness to question our assumptions, and a openness to the possibility of error. It is through the constant exercise of our human faculties – reason, doubt, and inquiry – that we can hope to minimize the impact of false positives and move closer to a clearer understanding of the world around us.

ChatGPT elaborates, and true to form, a structure with headings...

Hannah Arendt, a political theorist known for her work on the nature of power, totalitarianism, and the human condition, would likely approach the concept of a false positive through her keen insights into truth, morality, and the social implications of errors in judgment. A false positive, in a general sense, occurs when a test incorrectly indicates the presence of a condition (such as a disease) when it is not actually present. Here's how Arendt might analyze this:

Epistemological Context

Arendt would first place the idea of a false positive within the broader epistemological framework, examining how truth and falsehood affect human affairs. She might argue that the false positive is a manifestation of the modern world's struggle with truth and reality, a topic she explored deeply in her works. Arendt would likely note that a false positive represents a type of error that stems not merely from technical limitations but also from the human desire to achieve certainty in an uncertain world.

Impact on Authority and Trust

In Arendt’s view, authority relies heavily on trust, credibility, and the responsible handling of truth. A false positive in a significant area, such as medical diagnostics or criminal justice, could erode trust in institutions, as it demonstrates their fallibility. She would likely explore how repeated false positives might lead to a wider crisis in authority, where people begin to doubt the veracity of those in power and the systems they use to make determinations.

Moral and Ethical Implications

Arendt would also delve into the moral and ethical implications of false positives. She might suggest that beyond the error itself, the response by those in power to a false positive is crucial. The ethical handling of such mistakes—acknowledging them, correcting them, and seeking to prevent them—reflects broader moral questions about responsibility, accountability, and the duty of care in society.

The Human Condition and Action

Linking to her thoughts in "The Human Condition," Arendt would see the false positive as an example of the unpredictability of human action and the unintended consequences that can arise. Every human action, according to Arendt, has the potential to yield results beyond our control or original intentions, which in the case of false positives, can severely impact lives and decisions.

Conclusion

In summary, Arendt would likely treat a false positive not just as a statistical or scientific anomaly, but as a significant phenomenon that can illuminate deeper truths about the nature of human society, the pursuit of knowledge, and the moral responsibilities of individuals and institutions. She would emphasize the importance of confronting these errors openly and responsibly as part of the broader endeavor to live together in a shared world where truth and reality are respected and upheld.

Mistral the wind from the South...

Hannah Arendt, a prominent political theorist, might have approached the concept of a "false positive" from a philosophical and political perspective. While she didn't directly discuss this term, as it's more common in fields like statistics, medicine, and technology, we can infer how she might have understood it based on her existing work.

A "false positive" typically refers to a result where a test or a system indicates that a given condition is present when it's not. For instance, a medical test might incorrectly show that a person has a disease when they are actually healthy.

Arendt might have viewed this concept through the lens of human error, fallibility, and the potential dangers of over-reliance on systems or systems of thought. She often emphasized the importance of critical thinking and judgment, and she might have argued that false positives can arise when we fail to question or scrutinize the methods and assumptions underlying our tests or systems.

Furthermore, she might have connected false positives to her concept of "the banality of evil." Just as ordinary people can unknowingly participate in evil acts, ordinary systems can produce harmful false positives. This isn't necessarily due to malicious intent, but rather to a lack of critical reflection and understanding.

In conclusion, while Arendt didn't specifically discuss false positives, her philosophical perspectives can provide a unique framework for understanding this concept. She would likely encourage us to critically examine our systems, to question our results, and to understand the potential consequences of our reliance on these systems.

Still perusing the respective answers myself... but not versed in her work Looks like fallibility of thought (human) and prediction of information generation (machine) may help us frame how to deal with True and False and the effect of our dealing (human flaws?) with them....

Comments welcome and requested.

p.s. I asked the same question to all of them i.e. Explain a false positive the way Hannah Arendt would have done. I did this just in English, but may proceed to French...

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