Experiential AI

AI matters Pub Date : 2019-04-22 DOI:10.1145/3320254.3320264
D. Hemment, R. Aylett, Vaishak Belle, Dave Murray-Rust, E. Luger, J. Hillston, Michael Rovatsos, F. Broz
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引用次数: 8

Abstract

Experiential AI is proposed as a new research agenda in which artists and scientists come together to dispel the mystery of algorithms and make their mechanisms vividly apparent. It addresses the challenge of finding novel ways of opening up the field of artificial intelligence to greater transparency and collaboration between human and machine. The hypothesis is that art can mediate between computer code and human comprehension to overcome the limitations of explanations in and for AI systems. Artists can make the boundaries of systems visible and offer novel ways to make the reasoning of AI transparent and decipherable. Beyond this, artistic practice can explore new configurations of humans and algorithms, mapping the terrain of inter-agencies between people and machines. This helps to viscerally understand the complex causal chains in environments with AI components, including questions about what data to collect or who to collect it about, how the algorithms are chosen, commissioned and configured or how humans are conditioned by their participation in algorithmic processes.
体验式人工智能
体验式人工智能是一种新的研究议程,艺术家和科学家聚集在一起,消除算法的神秘性,使其机制生动地显现出来。它解决了寻找新的方法来开放人工智能领域,以提高人与机器之间的透明度和协作的挑战。假设是,艺术可以在计算机代码和人类理解之间进行调解,以克服人工智能系统中解释的局限性。艺术家可以使系统的边界可见,并提供新颖的方法,使人工智能的推理透明和可破译。除此之外,艺术实践可以探索人类和算法的新配置,绘制人与机器之间的跨机构地形。这有助于从内心深处理解人工智能组件环境中复杂的因果链,包括收集什么数据或收集谁的数据,如何选择、委托和配置算法,以及人类如何通过参与算法过程而受到制约。
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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