Talk:Main Page
General Structure of Discussion
For each discipline represented in the Big History community, list concisely:
1) Key insights from the discipline, that seem most essential for collaboration (what each discipline contributes to the whole picture).
2) Assumptions/limitations/blinders inherent to the discipline.
3) Current puzzles and paradoxes active in the discipline, stated within the framework of the discipline but with an eye toward the whole. How do these puzzles fit within questions of interest beyond the narrow confines of the discipline? (This question invites participants to think about how their discipline relates to others, and to the whole.)
I have in mind starting with standard disciplines such as history, physics, astronomy, geology, biology, paleontology, sociology, psychology, environmental science, philosophy, anthropology, mathematics, geography, literature, languages, political science, economics, computer science, art, theatre, music, education, complexity science, information theory, etc. But these need not be limiting: categories should be chosen and shaped by participants.
While the three questions above provide an initial foundation for the framework I have in mind, it may be useful to also suggest other questions as food for thought to spark conversation. For example:
• What similarities can I find between questions or problems in my discipline and those in other disciplines? Are there places where they are trying to solve the same problem (or where the problem in both fields can be revised to reveal a more general problem that is essentially the same)?
• What solutions do they have to similar problems, and can I adapt them to my discipline? Or can I modify the questions I ask to better align with their solutions?
• What does the narrative of another discipline emphasize that we tend to ignore in mine?
• It may be useful to apply narratives from different disciplines to overlapping topics and look for contradictions. Then ask, “What assumptions would I have to change or what tweaks could I make to one or more perspectives, to resolve the contradictions?”
• What core terminology from my specialty can I translate to make it more generally accessible, to help facilitate shared dialog?
Astrophysics
1) Key insights include a few basic patterns or laws that are universal and underlie everything we observe; the importance of basing our conclusions on empirical evidence; and a basic timeline of key overall stages of the development of the known universe over its 13.8 billion-year history.
2) Limitations include omitting the experience of subjectivity from direct consideration within the field.
3) Current puzzles include
-the nature of the dark matter and dark energy needed to explain large-scale motions within and among galaxies,
-how the first galaxies formed,
-how life emerges from non-living structures,
-how the laws of physics are encoded within the universe,
-why fundamental constants take on the particular values they have (such as the speed of light, strength of gravity, etc.), and
-why these values are such that they allow the emergence of life within the universe.
-Another puzzle is how to include observers within our models. As Sara Walker (2024) writes: “We cannot see ourselves clearly because we have not built a theory of physics yet that treats observers as inside the universe they are describing: that understanding is muddled across seemingly disparate concepts we refer to as ‘matter,’ ‘information,’ ‘causation,’ ‘computation,’ ‘complexity,’ and ‘life.’”
Computer Science
1) Key insights:
-Elements of intelligence: Planning, learning, analogy, decision making, pattern recognition, handling uncertainty, integrating multiple modes of information
-Compilers as a way to translate one knowledge representation to another with syntax
-The importance and power of recursion in computation
-In software development: the need to utilize decomposable hierarchical structures to maintain operations under large stresses from growth and change
-There is a difference between standard digital computing and quantum computing
2) Assumptions, Limitations:
-Often: computing is digital although there are elements of symbolic reasoning and analog computing
3) Current Puzzles:
-Why are the current AI techniques so effective?
-Is our current AI model of a neuron, an insult to the real workings of neurons?
-How can our brain work on such a small energy flow (20 W) compared to the near GW of data centers?
-Is there a way to solve NP Complete problems with quantum computing?