Building the Next Generation of Factories
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Human-Machine Pedagogy

Applied Human-Machine Pedagogy in Manufacturing

Current limitations in industry

Pedagogy is the art and science of teaching and learning. In manufacturing we use different kinds of pedagogies. For example, individuals may learn at college, attend a manufacturing apprenticeship where they learn skills from a more experienced worker, train ‘on the job’ as part of a production line, or be re-skilled by an external trainer.

The use of robots, AI, augmentation and virtuality in manufacturing radically changes the way we need to think about all processes. Do humans need to learn from other humans? It is easy to see how human-centred assumptions can be limiting when dealing with physical forms, for example: a robot arm based on an octopus tentacle may be more efficient than one based on a human arm and a swarm of sensors may be better than a single sensor. This can also be applied to ideas behind learning and pedagogy. A current limitation in industry is the assumption that the ways that humans currently learn in manufacturing is optimal, and pedagogy in current manufacturing is little different from methods used in the Nineteenth century.

Current limitations in scope of research

Existing educational theory assumes that humans all share some common characteristics which mean they learn in a particular way. Robot and animal learning are seen as different from human learning, yet share similarities with human theories of learning, for example machine learning and animal behaviourism are instrumental; establishing statistical or stimulus “reward” pathways through which outcomes emerge. Recent theoretical literatures look beyond human assumptions about learning. We call these theories human-machine pedagogy as they look beyond the human centered assumptions of learning. These theories include exopedagogy, posthumanism, object-oriented ontology, actor network theory and cybernetics, all of which investigate interactions between people, objects/tools/machines and organisational systems. They consider the limits of human-centred learning, which are very hard for us to spot when we are embedded in existing systems. They also offer ideas about alternative forms of learning to transform relationships between people, tools and systems. However, these theories remain abstract and the practical implications, e.g. for interventions in manufacturing, have not yet been explored.

The value added to research

The research will transform basic/abstract theoretical ideas about human-machine pedagogy and post-human forms of learning into a practical typography and applied toolkit. This will 1. Construct a literature review that compares and contrasts a very wide range of theories in a new context; 2. Test the usefulness of a range of theories for observing and understanding practices in an applied context; 3. Test their usefulness for undertaking interventions in a manufacturing context; 4. Consider the social and ethical issues raised by the possible inclusion of new pedagogic techniques in manufacturing.

The value added to industry

The research will consider the limitations that assumptions about human learning place on manufacturing processes. These limitations may impact on a broad range of values important to businesses, such as: profit; efficiency; quality; creativity; innovation; integrity; teamwork and environmental sustainability. By mapping how assumptions about human learning inhibit organizations from developing these values, the research will also suggest practical interventions for the other members of the Chatty Factories research team to develop applications which maximise desired values through interactions between humans and robots

Visualising the future.

•Workers and robots training together in real time through symbiotic forms of learning. This learning could be reciprocal, and the robot / human could develop a shared domain of learning.
•Robots and workers co-creating a learning domain through an AI interface that enables them to combine skills over time to optimise production.
•Companion robots that assist workers using training similar to that between humans and companion animals.
•Swarm production where workers and machines learn production processes in synergistic ways.

Research Investigators:

Prof John Preston, Dr Rhiannon Firth

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