PERSONAL-NOTES, QUANTA-MAGAZINE

Notes on "The New Math of How Large-Scale Order Emerges"

Modeling the emergence of complex systems could have a lot of world-changing applications

A framework for understanding how emergence arises: Software in the natural world: A computational approach to hierarchical emergence

What I was thinking about:

A few years ago, Rosas started thinking about the vexed question of whether the brain is a computer. Consider what goes on in your laptop. The software generates predictable and repeatable outputs for a given set of inputs. But if you look at the actual physics of the system, the electrons won’t all follow identical trajectories each time. “It’s a mess,” said Rosas. “It’ll never be exactly the same.”

Modeling the emergence of robust, large-scale structures like Jupiter’s Great Red Spot could be an interesting field of study:

The researchers also considered artificial neural networks like those used in machine-learning and artificial-intelligence algorithms. Some of these networks organize themselves into states that can reliably identify macroscopic patterns in data regardless of microscopic differences between the states of individual neurons in the network.

Reminds me of movie “Blade Runner” in which they’d mastered the life. By maturity of modeling the complex systems, it might be possible to understand a living organism(i.e. any human) to the fullest:

As for living organisms, they seem sometimes to be emergent but sometimes more “vertically integrated,” where microscopic changes do influence large-scale behavior. Consider, for example, a heart. Despite considerable variations in the details of which genes are being expressed, and how much, or what the concentrations of proteins are from place to place, all of our heart muscle cells seem to work in essentially the same way, enabling them to function en masse as a pump driven by coherent, macroscopic electrical pulses passing through the tissue. But it’s not always this way. While many of our genes carry mutations that make no difference to our health, sometimes a mutation — just one genetic “letter” in a DNA sequence that is “wrong” — can be catastrophic. So the independence of the macro from the micro is not complete: There is some leakage between levels. Rosas wonders if living organisms are in fact optimized by allowing for such “leaky” partial emergence — because in life, sometimes it is essential for the macro to heed the details of the micro.

همین الان که به این موضوع فکر می‌کنم، متوجه می‌شوم که بی‌اختیار با انگشتم در حال پاک کردن لکه‌ای از روی لپتاپ هستم و به این فکر فرو می‌روم که آیا تمام این اعمال غیر ارادی و حتی خودِ فکرکردن هم از فعل و انفعالات تک‌تک نرون‌های درون مغذم نشأت گرفته یا نه. آیا با یک مدل سازی دقیق می‌شود تمام این افکار و افعال را در بوسیله یک کامپیوتر بازسازی کرد؟ آیا عوامل خارجی هم در این اتفاقات دخیل هستند؟

احتمالاً حالا به درک بهتری از مسئله جبر و اختیار رسیدم. اگر با بلوغ روش‌های مدل‌سازی سیستم‌های پیچیده امکان مدل‌سازی انسان فراهم شود؛ می‌توان افکار و اعمال فردی را در آینده‌ی کوتاهی، حتی یک اپسیلون ثانیه بعد، پیش‌بینی کرد یا انسان فراتر از بعد مادی است؟

The new ideas touch on the issue of free will. While hardened reductionists have argued that there can be no free will because all causation ultimately arises from interactions of atoms and molecules, free will may be rescued by the formalism of higher-level causation. If the main cause of our actions is not our molecules but the emergent mental states that encode memories, intentions, beliefs and so forth, isn’t that enough for a meaningful notion of free will? The new work shows that “there are sensible ways to think about macro-level causation that explain how agents can have a worthwhile form of causal efficacy,” Seth said.

At this point, some of the arguments are pretty fuzzy. But Crutchfield is optimistic. “We’ll have this figured out in five or 10 years,” he said. “I really think the pieces are there.”