Session K12: Living Histories of Ideas

Matter in motion

Life on earth began with the single-celled organism. They often embody one of the most basic signatures of life - namely 'purposeful' movement. In learning about and exploring the diverse physical mechanisms and principles that govern how microscopic creatures move, navigate, and interact with their unpredictable world, scientists past and present have been able unravel some of the key evolutionary pathways that led to the emergence of complexity and multicellularity. Conversely, these fundamentally biological questions have also inspired the discovery of new physics and mathematics, and as such were instrumental to shaping our recent understanding of active matter and non-equilibrium systems at microscale. In this talk I will examine and highlight this fascinating duality from both a historical and contemporary perspective.   

More Is Still Different

2022 marked the 50^th anniversary of Philip Anderson’s classic article ``More is Different,’’ a deep analysis which asked what it means for different parts of science to be “fundamental.”  Though Anderson’s insights into physics remain relevant to this day, my talk will focus instead on the argument that questions about whether microscopic understanding is the route to “fundamental” understanding are even more important in the context of modern biology.    The molecular conception of biology has been one of the biggest success stories in the history of science.  And yet, with the proliferation of sequences and protein and RNA structures, questions abound about the implications of such data for interpreting biological reality.  In this talk, after a brief review of Anderson’s classic paper, I will give several disparate examples of the way that “natural variables,” coarse-grained descriptions of diverse biological phenomena emerge that provide both intuition and predictive power.  The specific examples will consider a billion-fold difference in length scales ranging from the herding of wildebeest to the actin-based motility of parasites to the dynamics of inducible transcription factors.  These examples will reveal emergence as illustrated by herding without animals, cytoskeletal dynamics without actin and molecular dynamics without molecules.   

On Being Curious

What is curiosity? Is it an emotion? A behavior? A cognitive process? Curiosity seems to be an abstract concept—like love, perhaps, or justice—far from the realm of those bits of nature that mathematics can possibly address. However, contrary to intuition, leading theories of curiosity from history, philosophy, and psychology are surprisingly amenable to formalization in the physics of network science and can be tested in linguistic and behavioral data. In understanding the foundational processes of curiosity, we can turn to pressing societal questions that can only be addressed through interdisciplinary work that foregrounds a critical consciousness. How can we practice, mentor, and teach curiosity? In what ways might we value and support diverse curiosities? What is an ethical curiosity?   

Technologies as Ideas and Ideas as Technologies

I would like to suggest that the most general definition of a technology is the combination of a set of rules with a system of rigid constraints whose degrees of freedom perform useful work when governed by these rules. Hence procedures with hammers, scissors, and engines are all technologies. And by generalizing the idea of work to computational work, we include the use of algorithms with the abacus, calculators, and computers. By generalizing rigidity to imply reliable inference and causality, then ideas, to include geometry and software, are candidate technologies. For simple classical phenomena, microscopes and telescopes have been our "go to" technologies. I shall focus on the world of complex adaptive phenomena, where ideas and ideas in software, are our most compelling candidate technologies. And the latest evolution of technology amplifies the fundamental dilemma of technology -- the fraught relationship between work-prediction and simplicity-understanding.   

Geometry, topology and emergent simplicity

Complex systems involve many varied working parts and display structured, yet complicated phenomena that are difficult to understand. Can we make sense of complexity without knowing the detailed inner workings of the system? What robust predictions can we make and are there simple emergent laws to describe such phenomena? One powerful and old approach is to use tools from geometry and topology to address this question. Using both historical and contemporary examples I will dicsuss how these tools afford simple lessons in complex systems and highlight some future exciting frontiers, particularly in relation to biology.