挖掘环境公域:在环境知识、人工智能和创造性实践研究之间建立跨学科联系

IF 1 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES Interdisciplinary Science Reviews Pub Date : 2022-03-17 DOI:10.1080/03080188.2022.2036408
Ambrose Field
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引用次数: 2

摘要

摘要根据Brooks[2017。“自动驾驶汽车的最大问题是人”。IEEE Spectrum:Technology,Engineering,and Science News],在上下文和环境知识负责塑造人类互动的情况下,人工智能的有用性记录各不相同。2021年,对于涉及复杂系统的人工智能模型来说,为监督机器学习提供情境感知训练仍然是一项不平凡的任务。此外,知识仅在社区的分布式成员之间、文化中或在环境公域的更广泛环境中默认持有[Mcullough 2013。环境共享:信息化身时代的关注。马萨诸塞州剑桥:麻省理工学院出版社]回避了一致的可推广建模——即使是在交通流管理、大气化学或选举结果预测等技术领域。然而,正是这些背景、社区、文化和环境的互动也定义了音乐的创作方式。创造性艺术本身可以被认为是一个复杂的系统。假设创造力是不可推广的,本文通过机器学习和机器人的人文中心视角来评估创造力过程,旨在更好地理解艺术研究中背景、环境和实验系统之间的关系。这些关系现在本身就受到了显著的数字中介,需要改变学术话语,从需要离散研究论证的人工制品转向对需要文化情境的网络的更全面、往往是非线性的看法。在这样做的过程中,创造性问责制的问题[Field 2021。“改变创造性研究的词汇:网络、风险和责任在超越技术合理性中的作用”,载于《声音工作:作为关键技术实践的写作》,J.Impett编辑,303-317。鲁汶:鲁汶大学出版社]以及用“创造性问题”代替“研究问题”的含义在创造性研究中进行了研究。20世纪初,与进步主义有关的思想将创造性实践工具化,特别是在技术构成艺术创作一部分的情况下,受到了通过新模式重新思考变革的挑战。“三视野”改变模式[Sharpe 2016。《三个视野:转型之路实践》,《生态学与社会》21(2):47]最初旨在描述环境生态系统,被评估为设计创造性研究的实用工具。
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Mining the ambient commons: building interdisciplinary connections between environmental knowledge, AI and creative practice research
ABSTRACT According to Brooks [2017. “The Big Problem with Self-driving Cars Is People”. IEEE Spectrum: Technology, Engineering, and Science News], artificial intelligence has had a variable track-record of usefulness in situations where context and environmental knowledge are responsible for shaping human interactions. In 2021, providing contextually aware training to supervised machine learning is still a non-trivial task for AI models that involve complex systems. In addition, knowledge held only across distributed members of a community, within culture, or tacitly within the wider environment of the ambient commons [McCullough 2013. Ambient Commons: Attention in the Age of Embodied Information. Cambridge, MA: MIT Press] evades consistent generalizable modelling – even in technical domains such as traffic flow management, atmospheric chemistry, or the prediction of election results. Yet it is precisely these interactions of context, community, culture and environment that also define how music can be created. The creative arts can themselves be thought of as a complex system. Assuming that creativity is non-generalizable, this paper assesses creative processes through a humanities-centric lens of machine learning and robotics, aiming to better understand relationships between context, environment and experimental system in artistic research. These relationships are now themselves significantly digitally mediated, requiring a change in academic discourse away from artefacts which need discrete research justification towards a more holistic, and often non-linear view of networks that require cultural situation. In doing so, issues of creative accountability [Field 2021. “Changing the Vocabulary of Creative Research: The Role of Networks, Risk, and Accountability in Transcending Technical Rationality.” In Sound Work: Composition as Critical Technical Practice, edited by J. Impett, 303–317.Orpheus Institute Series. Leuven: Leuven University Press] and the implications of substituting “creative question” for “research question” are examined within creative research. Early twentieth century ideas related to progressivism which have instrumentalized creative practice, particularly where technology forms part of art making, are challenged by re-thinking change through new models. The Three Horizons change model [Sharpe 2016. “Three Horizons: A Pathways Practice for Transformation.” Ecology and Society 21 (2): 47] originally intended to describe environmental ecosystems, is assessed as a practical tool for designing creative research.
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来源期刊
Interdisciplinary Science Reviews
Interdisciplinary Science Reviews 综合性期刊-综合性期刊
CiteScore
2.30
自引率
9.10%
发文量
20
审稿时长
>12 weeks
期刊介绍: Interdisciplinary Science Reviews is a quarterly journal that aims to explore the social, philosophical and historical interrelations of the natural sciences, engineering, mathematics, medicine and technology with the social sciences, humanities and arts.
期刊最新文献
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