In an episode of Voices for Excellence, host Dr. Michael Conner spoke with Kunal Dalal, CEO of AI Parentology, about how artificial intelligence, micro schools and changing family expectations are reshaping education. The discussion explored what learning could look like when students are given greater autonomy, parents become more active partners and AI is used not as a shortcut, but as a tool for reflection, creativity and deeper human connection.
For decades, education has been built around a familiar formula: large institutions, age-based classrooms, standardised content and predetermined measures of success. That model has created structure and consistency, but it has also limited how quickly schools can respond to the needs of individual learners. The rise of artificial intelligence has exposed those limitations by making knowledge, explanations, creative tools and personalised support available almost instantly. This raises a much bigger question than whether schools should adopt another piece of technology. It forces us to ask what education is actually for when access to information is no longer the main barrier.
The answer is not to replace schools, teachers or human relationships. It is to rethink how those elements work together. AI has the potential to reduce some of the administrative burden that prevents educators from focusing on learning itself, while also making it easier to create more flexible, personalised and responsive environments. Used well, it can support a model in which students are not simply moved through a fixed sequence of tasks, but are given more agency over how they learn, who they collaborate with and how they apply their knowledge.
Micro Schools as Laboratories for Better Learning
Micro schools are small, community-based learning environments that often serve a limited number of students. They may operate from homes, community spaces, faith organisations or dedicated learning centres. Although the idea shares some similarities with homeschooling and the small-school movement, the key difference lies in where the design begins.
Traditional education systems are usually designed from the top down. Policies, curriculum, timetables and assessments are established first, and students are expected to fit within them. Micro schools have the potential to work from the bottom up, beginning with the needs, interests and ambitions of a particular group of learners. Families and educators can then build a structure around those needs rather than forcing students through a standardised model that may not reflect how they learn best.
Until recently, this kind of personalised environment was difficult to create and sustain. Parents and educators had to develop resources, organise curriculum, track progress and manage compliance largely on their own. AI can now support lesson planning, resource creation, personalised explanations, documentation and assessment design. That does not remove the need for adult expertise, but it can reduce the repetitive work involved in running a smaller learning environment, leaving more time for curiosity, collaboration, problem-solving and meaningful discussion.
This creates an opportunity for micro schools to become laboratories for new approaches to learning. They can test how students respond when they are given more choice, how learning changes when it is connected to real problems and how smaller communities can create stronger relationships between learners, families and educators. The aim is not to shrink the traditional school and repeat the same model on a smaller scale. It is to design something fundamentally more responsive.
Personalisation Is Not Isolation
One of the biggest misconceptions about personalised learning is that it means students working alone. In reality, personalisation should help learners understand how they work best, what motivates them and where they need support. It should then help them contribute more confidently within a group.
Students can learn independently while still collaborating deeply. They may work alone for part of a task, join a small group to test an idea, seek guidance from an adult or use an AI tool to explore a concept from another angle. The value lies in giving learners the flexibility to choose the form of support and collaboration that best fits the work.
The goal is not to place every child in front of a screen with a personalised programme. It is to create an environment where students have more control over how they engage with ideas, solve problems and make sense of the world around them. When they see that their thinking can lead to action, they begin to develop a stronger sense of self-efficacy. Education becomes less about completing work for approval and more about understanding how their ideas can create value for themselves and their communities.
Students Must Be Treated as Active Participants
Young people are frequently described as the future of education, yet they often have the least influence over how education is designed. That contradiction matters, particularly in a world changing faster than many institutions can adapt.
Listening to students does not mean removing structure or allowing children to make every decision. It means treating their experiences as useful evidence. Students know when learning feels relevant, when a system is helping them grow and when they are simply being asked to comply. They can identify where they feel supported, where they feel excluded and what helps them understand difficult ideas.
Adults still bring expertise, experience and access to wider networks. Their role is not to disappear, but to use those resources to remove barriers and help young people turn ideas into action. This requires a shift away from the assumption that adults must lead students towards a future that has already been defined. Instead, educators can help students explore and shape a future that adults may not yet fully understand.
This approach is especially important in discussions about educational innovation. Too often, new models are designed by boards, districts or technology companies and then delivered to students as finished products. A more effective approach would involve students earlier, not as passive recipients, but as contributors whose perspectives help shape the system itself.
AI Can Strengthen Family Learning
AI is also changing the way learning happens at home. Parents do not need to become technology experts, but they do need to become thoughtful guides who understand how these tools can support conversation, creativity and connection.
A child may ask a complicated question that a parent struggles to explain. AI can help translate the idea into language that matches the child’s age and understanding, while also generating examples, images or stories that make an abstract concept easier to grasp. Families can use these tools to explore memories, create visual representations of dreams, build stories together or explain parts of family history that may be difficult to communicate through words alone.
The value does not come from the generated output by itself. It comes from the conversation around it. Why does the image feel accurate? What is missing? What would the child change? What does the story reveal? These questions encourage children to think critically about what the tool has produced rather than treating it as automatically correct.
Used carefully, AI can become a tool for deeper connection rather than a replacement for human interaction. It can help parents enter their child’s world, understand how they are thinking and create shared experiences that may not have been possible before.
Bias in AI Is a Human Problem
Concerns about bias in AI are valid, but the phrase “AI bias” can make the problem sound as though it originated inside the machine. A more accurate description is embedded prejudice.
AI systems are trained on information created, collected and preserved by people. They reflect the patterns, assumptions, exclusions and inequalities within that information. The technology is not inventing prejudice from nothing. It is reproducing what humanity has documented and digitised.
This creates a major limitation. Large language models are trained primarily on written and digital knowledge, yet much of human experience has never been written down. Oral histories, indigenous knowledge, family traditions, community practices and everyday conversations may be absent from the data entirely. Even a system trained on every available book, article and website would still represent only a fraction of human knowledge.
That does not make AI useless, but it does mean users must understand what it can and cannot see. Educators, parents and students need to ask whose perspective is represented, whose experience is missing and what assumptions may be repeated in the output. AI literacy must include the ability to recognise gaps, compare sources and understand that confident language does not guarantee complete or accurate knowledge.
Critical Thinking Cannot Be Automated Away
There is a temptation to believe the ideal AI system would remove all errors, prejudice and uncertainty. But critical thinking develops precisely because information must be examined, challenged and interpreted.
Students should not be taught to accept AI outputs as final answers. They should be taught to use them as material for investigation. A response can become the beginning of a lesson, prompting learners to compare sources, test claims, identify missing context and examine how different prompts produce different results.
This prepares students for a world in which technology will be powerful, useful and imperfect. The aim should not be to create blind trust in AI, nor to reject it out of fear. The aim should be to develop judgement.
Educators therefore have an important role in teaching students how to work with uncertainty. They can help learners understand that not every answer will be complete, that not every tool will be neutral and that their own reasoning remains essential. In this sense, AI does not reduce the need for critical thinking. It makes it more urgent.
The Human Skills That Matter Most
The pace of technological change can create fear, particularly for parents and educators who feel responsible for preparing young people for an uncertain future. Yet the most important skills are not purely technical.
Resilience is essential because students and adults will need to adapt as tools, industries and expectations continue to shift. Resilience does not mean ignoring difficulty or pretending change is easy. It means recognising uncertainty without becoming paralysed by it.
Open-mindedness matters for the same reason. The world no longer changes in neat, predictable stages, and yesterday’s solution may not work tomorrow. Educators, leaders and families must be willing to question familiar assumptions, explore unfamiliar models and remain curious about possibilities that do not fit the structures they already know.
Joy matters too. Education cannot become a permanent emergency response to technological change. Curiosity, creativity, play and human connection still matter, perhaps more than ever. There will be difficult decisions, but there will also be opportunities to build learning environments that are more flexible, inclusive and meaningful than the ones they replace.
The future of education will not be defined by AI alone. It will be defined by the choices people make about how to use it. The strongest systems will not be the ones that chase every new tool. They will be the ones that use technology to create more agency, stronger relationships and more room for young people to imagine a world beyond the limits of the current one.
