Sean Manion has spent more than 25 years in neuroscience, clinical research and health technology. Mark “Moose” McGrath and I asked him to look at Boyd’s OODA loop through the natural sciences, cybernetics and complexity, and to tell us what that means for AI.
Feedback at the core
The loop rests on feedback. Sean connects that foundation to reinforcement learning and active inference. Ideas from cybernetics and information theory can help engineers build AI that adapts and uses less energy, closer to how living systems work.
Cybernetics and Boyd
Cybernetics is the science of communication and control in living things and machines. Sean traces its influence on Boyd’s thinking and on the early history of AI. We also cover symbolic AI, neuromorphic computing and complex adaptive systems.
Rethinking intelligence
Sean thinks neuroscience can make AI more explainable and more trustworthy. He sees large language models as tools that mimic a narrow slice of human cognition. Feedback loops, adaptive systems and even epigenetics shape how people decide, and he wants AI research to take that seriously.
Boyd worked across disciplines. Sean argues that AI innovation needs the same integrated, systems view.
For us, orientation is the link. A system that learns has to keep updating its picture of the world.
What would an AI built around orientation look like in your work?
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