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RECLAIM-FUTURE Mini-Project

By Wacera Thande, on 3 August 2023

By Wacera Thande and Robert Biel

The Radical Exploration of Co-Learning through Artificial Intelligence for Managing a Food-centric Urban Territory of Unprecedented Resilience and Equity or RECLAIM-FUTURE is a mini project co-lead by Prof. Robert Biel and MSc student Wacera Thande. We are both co-creators in this project seeking to understand how AI can be used to facilitate a co-learning experience to enable students to learn and understand complex systems within the Development Planning Unit’s Food and the City module headed and curated by Prof. Robert Biel.

This project is underpinned by Paulo Freire’s pedagogy and includes these three concepts:

  • Dialogue/Co – learning as a model of creating knowledge as a collective where participants are equal. Mutual respect and trust underpin this form of learning process. Each participant including the teacher/lecturer must be willing to question the knowledge they have acquired and be open to change and the creation of new knowledge.
  • Praxis – This means the testing of ideas through practice or action learning. It is not enough for people to come together in dialogue, it is key that we act upon our environment to be able to critically reflect on the knowledge we create for further action and critical reflection.
  • Liberation – Through practice and dialogue, knowledge should be used to awaken the consciousness of teachers and students to empower them to transform an unjust world through liberating ourselves from the dominating ideologies both cognitively and also in practice.

Paulo Freire: Image from Google

How does this relate to the Food and the City module?

The Food and the City module seeks to enable students to understand some underlying issues of the food crisis, understand agriculture in relation to the climate crisis, and outline the features of sustainable alternatives such as Agroecology, and link these technical solutions to social struggles of emancipation from oppressive systems such as unjust property relations and the democratization of knowledge. From the module handbook, this module shows how the city can implement these principles both within itself, and in its relations to the surrounding countryside. Internally, the city should evolve an urban metabolism (using compostable waste, heat, gray water) in order to grow some of its own food, as well as various food-related social networks acting to eliminate waste; externally, it can – through ‘community-supported agriculture’ and other means – work to revitalise small farms and free them from the tyranny of globalised value chains. The module uses systems theory to understand these complex systems within the city in relation to food.

 

What is the potential role of AI?

Simply put AI employs feedback in an attempt to answer prompts/questions it has been asked. Our key role in this mini project is to understand these feedback loops and understand how we can use AI in class to enable an understanding. We ask these questions.

  • Can AI enhance the ability for students to embrace complexity?
  • Can AI be a collaborative problem solver in the classroom?
  • Can AI enhance our reflective and reflexive skills within the classroom?

If we imagine in a Food and the City classroom, we would have a discussion across 3 agents: the students, the lecturers and the AI all as collaborators. Potentially AI could help in structuring a discussion by generating prompts through interaction with it. This counts AI as an agent that is not based on creative thought; but as an agent that helps stimulate it. Furthermore, AI can be a good agent in structuring discussions in group activities where open dialogue and reflective sessions may be carried out to enable a more collaborative approach of generating knoweldge. Using student to student and student to teacher dialogue for a co-creative space. Collaborative problem solving seeks to solve questions or problems through pooling their knowledge, skills, and efforts. With the help of AI as an agent can stimulate our human pooling and collaboration that is key for collaborative problem solving. In these cases the AI can generate maps, data sets, and other creative tools that enable greater collaboration processes amongst students. This can be linked to a form of collaborative commons, a concept that is central to the Food and the City module. Mapping and other creative tools can be created within the classroom as a form of commoning such as creating an AI version of a Miro board.

If we are redesigning the module AI’s role seems to be quite useful in those aspects especially when we are seeking to liberate our minds from the alienation of ruling ideology. An Interesting idea we have is that AI seems to have less of a bias in terms of the historic cause and is open to different forms of knowledge and experience.

AI is a tool that has many potential benefits that encourage inquiry based learning, collaborative problem solving, enhancing critical thinking of students and teachers and finally employability beyond the classroom. As described earlier our work is underpinned by Freire’s pedagogy. Therefore, collaborative problem solving may look like interacting with the AI in a classroom as a collaborator in facilitating conversations that are critical and help students reflect on already existing knowledge and newly made knowledge. We recognise the potential of AI in helping to co-design learning environments that replicate the structure and tools that students may find in real world situations. AI could potentially be used as a virtual avatar of the real world to enable the praxis paradigm that Freire talks about before they make it into the real world. Practically for the food and the city course an idea would be to have the real world situation of already existing food systems be replicated by AI. Where AI can design food systems that create an avatar of various ideas generated by students as a trial of potential food systems. Having a customized AI that generates virtual food systems that are conceptualized and imagined by the students. This can foster enquiry based learning, which comes from a drive by curiosity which in turn helps learners cultivate critical thinking and problem solving.

There are many opportunities we have identified with AI and we hope this mini project will at least address some of those opportunities.