Endemic Machines: Acoustic adaptation and evolutionary agents

David Kadish

Research output: Book / Anthology / Report / Ph.D. thesisPh.D. thesis


Endemic Machines is an interdisciplinary investigation of the question: What is required for a machine to adapt to a local ecosystem? Through the medium of sound, it explores the conceptualization and design of machines that belong in an ecosystem because they evolve within and alongside it. Drawing on research in soundscape ecology, artificial life, and artificial intelligence, it builds an interdisciplinary view of machine engagement with an existing soundscape.

Building on the biosemiotic concept of a sensory world, an umwelt, this work formulates a basis for the machine sensing of the soundscape. In parallel, it presents work — conceptual and based in practice — that constructs a new frame for the production and understanding of machinic vocalizations in the soundscape. The term robophony is devised to describe the sounds of ecologically engaged machines as they do not fit within the existing ontological framework which characterizes sound as originating from humans (anthrophony), (non-human) biological entities (biophony), or geophysical processes (geophony).

Additionally, the concept of eco-technogenesis is proposed as a way of understanding the cyclical co-evolution of technologies and ecosystems. This extends the concept of technogenesis, which situates technology and humanity as evolutionary partners, to the co-development of ecosystems and machines. The processes of feedback and co-creation inherent in eco-technogenesis provide a framework for understanding how machines can become endemic.

These theoretical contributions are scrutinized in the experimental design of an endemic machine that evolves a vocalization in an existing, real-world soundscape. Through this machine, the Rowdy Krause, adaptation to a local ecosystem is addressed in practice. The work delves into the nuances and complexities of adapting to a local ecosystem and the internal tensions embedded in the concept of an endemic machine.
Original languageEnglish
PublisherIT-Universitetet i København
Number of pages166
ISBN (Print)978-87-7949-049-9
Publication statusPublished - 2021


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