Social Dreaming: Leveraging AI for Collective Solution-Oriented Dreaming
Thought
During a lucid dream, the dreamer becomes aware they are dreaming and can potentially influence the dream's content. What if we "lucid dream" collectively, in a waking state, to creatively solve global issues?
Note
Social dreaming, facilitated by AI, to solve complex global problems.
Analysis
Lucid dreaming is a well-documented phenomenon where individuals gain awareness within their dreams and can, to varying degrees, control dream scenarios. This could be likened to a creative sandbox, where the mind imagines and plays out scenarios without real-world limitations. The essence of this concept can be transferred to a philosophical framework I contemplate—Social Dreaming.
Social Dreaming is about harnessing the collective subconscious of humanity, combining insights, fears, hopes, and innovative ideas in a structured, facilitated manner. If an AI were to be designed like a digital facilitator, it could analyze, synthesize, and project collective dreams, ideas, and solutions regarding pressing world matters like climate change, healthcare, or political conflict. This AI's architecture would be comprehensive, integrating machine learning, natural language processing, and data analytics, honed by the contributions of myriad individuals partaking in the Social Dreaming sessions.
How does this fit into Arthur Koestler's Bisociation concept? Social dreaming could be a novel matrix where two seemingly unrelated frames, the personal subconscious and collective problem-solving, intersect. It is here, in the crucible of this intersection, that creative resolutions could emerge.
Books
- "Collective Intelligence: Mankind's Emerging World in Cyberspace" by Pierre Lévy
- "The Wisdom of Crowds" by James Surowiecki
- "The Social Construction of Reality" by Peter L. Berger and Thomas Luckmann
- "Reinforcement Learning: An Introduction" by Richard Sutton and Andrew G. Barto — AI structuring
Papers
“Reward is enough” by David Silver, Satinder Singh, Doina Precup, Richard S. Sutton — The concept of using rewards in AI, which can drive the AI to facilitate optimal social dreaming sessions. “The Collective Dynamics of Smoking in a Large Social Network” by Nicholas A. Christakis and James H. Fowler — Analysis on how behaviors and ideas spread through networks, possibly analogous to how dreams and solutions could spread through collective dreaming.
Tools
- Machine learning frameworks like TensorFlow or PyTorch for building the AI system
- Sentiment analysis tools for gauging collective emotional responses to dream scenarios
- Network analysis software to map and visualize the connections and flows of ideas
Existing Products/Services
- Online forums and social media platforms—primitive forms of collective idea sharing and problem solving.
- Crowdsourcing platforms like Kickstarter or Innocentive where collective efforts are channeled toward creative projects or problem solving.
Implications
On the positive side, this idea could lead to the emergence of innovative solutions that a single mind or a conventional group could not conceive. On the downside, it involves the aggregation of personal data, necessitating robust privacy and ethical standards.
Assumptions
This thought experiment assumes that a large and diverse group of individuals are willing to contribute their subconscious musings and that the AI developed is capable of effectively analyzing and synthesizing such data.
Mental Models
We're relying on a mental model that combines elements of crowd wisdom, the power of dreams in understanding and problem-solving, and AI as a tool for amplification and synthesis.