Change-Ability for a World in Flux

IF 1.2 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Adaptive Behavior Pub Date : 2022-10-17 DOI:10.1177/10597123221133869
Erik Rietveld
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引用次数: 5

Abstract

This article aims to sketch a new integrative perspective on what I call change-ability. I define change-ability as skilled ways of coordinating with a rapidly changing world. Many urgent societal challenges – from climate change to obesity, from the mass extinction of species to fraying social cohesion – require people to collectively change everyday patterns of behaviour they take for granted. The key insight I start from is that to durably change undesirable patterns of behaviour, we could start by changing the affordances the environment offers – the possibilities for action offered to us by the living environment. The aim of this article is to sketch an integrative conceptual framework for understanding change-ability in terms in terms of a dynamical ‘brain ↔ body ↔ community ↔ landscape of affordances’ system. This Change-Ability Conceptual Framework starts from the idea that individuals and communities are situated in the same rich landscape of affordances and suggests that making communities more change-able entails transforming the material ‘grooves’ that have formed in this landscape of affordances.
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变化——变化世界的能力
本文旨在概述一种新的综合视角,我称之为“改变能力”。我将改变能力定义为与快速变化的世界协调的熟练方式。许多紧迫的社会挑战——从气候变化到肥胖,从物种大规模灭绝到社会凝聚力的削弱——要求人们集体改变他们认为理所当然的日常行为模式。我的关键见解是,要持久地改变不受欢迎的行为模式,我们可以从改变环境提供的能力开始——生活环境为我们提供的行动可能性。本文的目的是概述一个综合的概念框架,以便从动态的“脑↔身体↔社区↔景观的功能”系统的角度来理解可变性。这个变化能力概念框架的出发点是,个人和社区都处于相同的丰富的功能景观中,并建议使社区更具可变化性,需要改变在这种功能景观中形成的材料“凹槽”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Adaptive Behavior
Adaptive Behavior 工程技术-计算机:人工智能
CiteScore
4.30
自引率
18.80%
发文量
34
审稿时长
>12 weeks
期刊介绍: _Adaptive Behavior_ publishes articles on adaptive behaviour in living organisms and autonomous artificial systems. The official journal of the _International Society of Adaptive Behavior_, _Adaptive Behavior_, addresses topics such as perception and motor control, embodied cognition, learning and evolution, neural mechanisms, artificial intelligence, behavioral sequences, motivation and emotion, characterization of environments, decision making, collective and social behavior, navigation, foraging, communication and signalling. Print ISSN: 1059-7123
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