Part 3 – Explainable disruptions, dilemmas and directions
Here is the final part of my series of summaries of the provocative essays published in UNESCOs AI and the Future of Education
The collection argues that education requires more than technical fixes. Education is social, it will take dialogue, reflection, and imagination to co-create an inclusive, ethical, and human-centred educational future. Our stories about AI and education are still being written, and we have a collective responsibility to shape them with care, clarity, and courage.
Part one is here
And part 2 here
Page 98: Compassion by design: Building AI with and for caring educators (Arafeh Karimi)
Arafeh Karimi provides a practical guide for creating AI that is kind and fair. She outlines seven actionable shifts, such as participatory co-design with teachers and students, trust and well-being audits, and giving educators control over data. She sees AI as a collaborator in an educational ecosystem where AI supports a positive and inclusive school environment, deliberately nurtured through concrete policy and procurement mechanisms.
Page 108: Towards an ethics of care by design in AI in education (Kaska Porayska-Pomsta and Isak Nti Asare)
Porayska-Pomsta and Asare propose an "ethics of care by design" framework, arguing that ethics can't be an afterthought for AI in schools. Because education involves vulnerable people growing and learning, ethical care must be built into the technology from the very beginning, with students and teachers helping to design it through participatory, inclusive design processes. They hope for an AI which is built around the lived experiences of learners and teachers, centering human rights and dignity as foundational to AI governance in education.
Page 117: Artificial intelligence and governing education: Rethinking democratic action, resistance and participation (Kalervo N. Gulson and Sam Sellar)
Gulson and Sellar examine the rise of "synthetic governance," and warn that as AI is used more for decision-making in education, power can shift to algorithms and the companies that make them. The authors urge us to question this shift, challenging the assumption that AI is neutral, and demand that the use of AI in schools remains democratic, transparent, and focused on the public good.
Page 121: Ensuring inclusive, contextualized AI in education: Considerations towards a roadmap (Vukosi Marivate, Nombuyiselo Caroline Zondi and Baphumelele Maskisiki)
Marivate, Zondi, and Maskisiki propose a grounded vision for integrating AI into African higher education in a way that respects culture and language. They advocate for participatory, locally led approaches that prioritise human agency and pedagogical care. Their strategies include ethical data governance, support for underrepresented languages, and developing AI systems that are co-designed with communities ensuring AI tools are relevant and effective for the people who actually use them.
Page 125: From compliance to creativity: Reimagining AI in young women’s learning (Kiran Bhatia and Payal Arora)
Bhatia and Arora call for a reframing of the relationship between young women in the Global South and AI. Rather than the need to be protected from technology, they advocate giving them the tools to be creators and leaders with AI, focusing on joy, creativity, and using technology to change their own worlds for the better. Creating this world where young women are co-authors of digital futures would involve a bold shift from token consultation to co-creation, from compliance to creativity, and from control to care.
Page 132: Conceptual clarity: The missing link in the implementation of AI technologies for inclusive education (Yuchen Wang)
Yuchen Wang argues that the word "inclusion" is often used too vaguely when talking about AI. True inclusion isn't just personalising a lesson; it's about relationality, belonging, and collective learning. AI tools need to be designed with this deeper goal in mind. She invites developers and educators to co-design AI systems grounded in the lived experiences of learners and informed by the moral imperative to transform education systems for justice and participation.
Page 136: Inclusion or illusion? Rethinking AI for learners who are deaf or hard of hearing in under-resourced settings (Marloes Williams van Elswijk)
This piece explains that for deaf or hard-of-hearing students, whose diverse needs intersect with structural barriers like language deprivation and data poverty, AI alone can't solve their challenges. These students have diverse needs that require technology designed with their input and, crucially, combined with direct human support to be truly effective, particularly in under-resourced settings of the Global South.
Page 140: Human and machine: Policy implications of emerging AI capabilities (George Siemens)
This article offers a sobering reflection on the transformative impact of AI. Siemens frames AI as a geopolitical force, a technology that nations are racing to control, similar to military or economic power. This means there is an urgency for education ministers to act strategically, through policy, about how to use AI to benefit society while protecting human well-being and values.
Page 146: Adding intelligence to AIED policy and practice (Ilkka Tuomi)
This final essay suggests that education policy for AI can't be a fixed set of rules; rather, policy becomes collective sense-making and developmental experimentation. Because AI changes so quickly, policy-making itself needs to be a learning process, constantly experimenting, gathering evidence, and adapting based on what works for students and teachers - human agency and social purpose. He also calls for a rethinking of what counts as evidence and for designing evidence to serve policy-making as an "intelligent learning system" itself.
