Open Systems: TEK, AI & Embodied Cognition | MIT Symposium

Added:

Land Acknowledgment
Introducing Speakers
Alien Intelligence Tropes
Witchcraft & Other Knowledges
Historical Remedies & AI
Spiritualism & Automata
Psychedelia & Molecular Art
Oceanic Feelings Politics
Oceanic Connections
AI, Toxicity & Future

Land Acknowledgment

4:06
Playing Section
  • 1

    Acknowledges MIT's colonial history and indigenous land stewardship.

  • 2

    Outlines session focus on indigenous epistemologies and non-human cognition.

Fundamental concepts of Embodied Cognition, emphasizing how cognitive processes are deeply rooted in the body's interactions with the physical environment.
An introductory understanding of Traditional Ecological Knowledge (TEK) and how indigenous scientific methodologies differ from Western empirical frameworks.
Basic principles of Machine Learning (ML), specifically how algorithms recognize patterns and process high-dimensional environmental data.
General Systems Theory, specifically the distinction between closed systems and open systems that continuously exchange matter, energy, and information with their surroundings.
The emerging field of Indigenous AI, exploring how diverse cultural epistemologies can guide ethical and non-anthropocentric machine learning designs.
Advanced frameworks in cybernetics and active inference (e.g., the Free Energy Principle) to model how intelligent systems interact dynamically with environments.
Practical applications of combining TEK and ML in environmental monitoring, climate change adaptation, and biodiversity conservation strategies.
Bio-inspired and neuromorphic computing paradigms that seek to implement embodied intelligence principles directly into hardware and software architectures.
416 views9likes1:01:14@ArtsatMITOriginal Release: 2021-05-12

Open systems in AI and computation involve opening our machinic systems to alternative forms of intelligence beyond human-centric models, including more-than-human entities, distributed cognition, and non-human epistemologies, which challenges the dominant white, humanoid narratives of artificial intelligence and expands possibilities for understanding intelligence as permeable, multi-species, and cosmically diverse.