Introduction to WISE special issue, part I

a group of roughly 80 scholars gathered at the Carnegie Institution for Science's campus in Washington, DC, for the Workshop on Information, Selection, and Evolution (WISE).The goal of this workshop was to bring influential thinkers from various backgrounds to listen, learn and share ideas related to lawful, universal processes by which order, complex structures, adaptive behaviour and causally efficacious information arise in the cosmos.The general principle behind the meeting was the view that progress is made through combinatorial exploration (new configurations of people and ideas) followed by selection and refinement (critical winnowing of ideas that work).Fostering communication across disciplines is not easy.Mornings were spent listening to plenary talksprimers on the evolution of physical, chemical, biological, social and digital systems given by rising early-and mid-career researchers.Afternoons were dedicated to spontaneously organized group discussions about topics of interest, including the origin of life, quantifying evolution, evolution by processes other than natural selection, the nature of time, whether agency is real and the relationship between emergence and the laws of nature.In the evenings, we were treated to after-dinner lectures by leading senior researchers.New ideas burst forth, and this special issue represents the first concrete outputs of WISE.Within, one will find musings on the directionality of complexity and evolution [1,2], a philosophical treatise on natural laws in a timeless, holographic universe [3], an investigation into resourcerational reinforcement learning and sensorimotor causal states [4] and a new community-curated database for origins-of-life chemistry [5].

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Publication Details

Journal
Interface Focus
Published
2025-12-12
DOI
https://doi.org/10.1098/rsfs.2025.0066
Primary Topic
Technology Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Introduction to WISE special issue, part I

Stuart Bartlett, Michael L. Wong
Interface Focus
Technology Assessment and Management
article

Introduction to WISE special issue, part I

Stuart Bartlett, Michael L. Wong
article en

Abstract

a group of roughly 80 scholars gathered at the Carnegie Institution for Science's campus in Washington, DC, for the Workshop on Information, Selection, and Evolution (WISE).The goal of this workshop was to bring influential thinkers from various backgrounds to listen, learn and share ideas related to lawful, universal processes by which order, complex structures, adaptive behaviour and causally efficacious information arise in the cosmos.The general principle behind the meeting was the view that progress is made through combinatorial exploration (new configurations of people and ideas) followed by selection and refinement (critical winnowing of ideas that work).Fostering communication across disciplines is not easy.Mornings were spent listening to plenary talksprimers on the evolution of physical, chemical, biological, social and digital systems given by rising early-and mid-career researchers.Afternoons were dedicated to spontaneously organized group discussions about topics of interest, including the origin of life, quantifying evolution, evolution by processes other than natural selection, the nature of time, whether agency is real and the relationship between emergence and the laws of nature.In the evenings, we were treated to after-dinner lectures by leading senior researchers.New ideas burst forth, and this special issue represents the first concrete outputs of WISE.Within, one will find musings on the directionality of complexity and evolution [1,2], a philosophical treatise on natural laws in a timeless, holographic universe [3], an investigation into resourcerational reinforcement learning and sensorimotor causal states [4] and a new community-curated database for origins-of-life chemistry [5].

Interface FocusVol. 15(5)
California Institute of Technology (US), Carnegie Institution for Science (US)
Openalex Percentile: Top 53%
Technology Assessment and Management
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