Establishing counterpoints in the sonic framing of AI narratives

Jennifer Chubb, David Beer
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Abstract

In order to challenge dominant representations and conceptions of artificial intelligence (AI), this article explores how AI is sonically represented in documentaries. Using a corpus of documentaries alongside expert interviews with sound designers, we explore the ways in which music and sound may influence perception about AI. The notion of ‘counterpoint’ in music theory is developed as a concept to capture and explain how the integrated dynamics of human/machines are represented within these sonic framings. The concept of the counterpoint allows us to reflect on how the relations between AI and the human and how they are sonically framed in ways that separate and blend without recourse to reductive or binary futures, which potentially misrepresent AI capabilities and performance. The article identifies and develops four types of counterpoint in what we refer to as AI sonic narratives. This article provides a framework from which AI could be sonically framed responsibly, which is critical when misinformation and hype impede the public understanding of science.

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在人工智能叙事的声音框架中建立对立点
为了挑战人工智能(AI)的主流表现和概念,本文探讨了如何在纪录片中表现人工智能的声音。我们使用纪录片的语料库以及对声音设计师的专家采访,探索音乐和声音可能影响人们对AI的看法的方式。音乐理论中的“对位”概念是作为捕捉和解释人类/机器的综合动态如何在这些声音框架中表示的概念而发展起来的。对位的概念使我们能够反思人工智能与人类之间的关系,以及它们如何以分离和融合的方式进行声音框架,而不依赖于简化或二元未来,这可能会歪曲人工智能的能力和性能。本文确定并发展了我们称之为AI声音叙事的四种对位类型。本文提供了一个框架,当错误信息和炒作阻碍了公众对科学的理解时,这一点至关重要。
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