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Because machine listening is trained on (more-than) human auditory worlds, it inevitably encodes, invisibilises and reinscribes normative listenings, along with a range of more arbitrary artifacts of the datasets, statistical models and computational systems which are at once its lifeblood and fundamentally opaque [McQuillan]. This combination means that machine listening is simultaneously an alibi or front for the proliferation and normalisation of specific auditory practices *as* machinic, and, conversely, often irreducible to human apprehension; which is to say the worst of both worlds.

Moreover, because machine listening is so deeply bound up with logics of automation and pre-emption, it is also recursive. It feeds its listenings back into the world - gendered and gendering, colonial and colonizing [interview YS], ![raced and racializing](soundcite:static/audio/halcyon-siri-imperialism.mp3)[^halcyon_audio_1], classed and productive of class relations - as Siri's answer or failure to answer; by alerting the police, denying your claim for asylum, or continuing to play Autechre - and this incites an auditory response to which it listens in turn. The soundscape is increasingly cybernetic. Confronting machine listening means recognising that common-sense distinctions between human and machine simply fail to hold. We are all machine listeners now.
Moreover, because machine listening is so deeply bound up with logics of automation and pre-emption, it is also recursive. It feeds its listenings back into the world - gendered and gendering, colonial and colonizing [interview YS], ![raced and racializing](soundcite:static/audio/halcyon-siri-imperialism.mp3)[^halcyon_audio_1], classed and productive of class relations - as Siri's answer or failure to answer; by alerting the police, denying your claim for asylum, or continuing to play Autechre - and this incites an auditory response to which it listens in turn. The soundscape is increasingly cybernetic. Confronting machine listening means recognising that common-sense distinctions between human and machine simply fail to hold. We are all machine listeners now. This must become the starting point of a contemporary politics of listening.

But machine listening isn't exactly listening either.

Technically, the methods of machine listening are diverse, but they bear little relationship to the biological processes of human audition or psychocultural processes of meaning making. Many are fundamentally imagistic. Many work by combining auditory with other forms of data and sensory inputs: machines that listen by looking, or by cross-referencing audio with geolocation data. In the field of Automatic Speech Recognition, for instance, it was only when researchers at IBM moved away from attempts to simulate human listening towards statistical data processing in the 1970s that the field began making decisive steps forward. Speech recognition needed to untether itself from "human sensory-motor phenomenon" in order to start recognising speech. Airplanes don't flap their wings.[^airplanes]
Technically, the methods of machine listening are diverse, but they bear little relationship to the biological processes of human audition or psychocultural processes of meaning making. Many are fundamentally imagistic [IBM Watson?]. Many work by combining auditory with other forms of data and sensory inputs: machines that listen by looking [light bulb thing], or by cross-referencing audio with geolocation data. In the field of Automatic Speech Recognition, for instance, it was only when researchers at IBM moved away from attempts to simulate human listening towards statistical data processing in the 1970s that the field began making decisive steps forward. Speech recognition needed to untether itself from "human sensory-motor phenomenon" in order to start recognising speech. Airplanes don't flap their wings [X Li].

Even if machine listening did work by analogising human audition, the question of cognition would still remain. Insofar as "listening" implies a subjectivity, machines do not (yet) listen. But this kind of anthropocentrism simply begs the question. What is at stake with machine listening is precisely a new auditory regime: an analog of Paul Virilio's "sightless vision", the possibility of a listening without hearing or comprehension, a purely correlative listening, with the human subject decentered as privileged auditor.
Even if machine listening did work by analogising human audition, the question of cognition would still remain. Insofar as "listening" implies a subjectivity, machines do not (yet) listen. But this kind of anthropocentrism simply begs the question. What is at stake with machine listening is precisely a new auditory regime: an analog of Paul Virilio's "sightless vision" [ref], the possibility of a listening without hearing or comprehension, a purely correlative listening, with the human subject decentered as privileged auditor.

One way of responding to this possibility would be to simply bracket the question of listening and think in terms of "listening effects" instead, so that the question is no longer whether machines *are* listening, but what it means to live in a world in which they act like it, and we do too.

Another response would be to say that when or if machines listen, they listen "operationally": not in order to understand, or even facilitate human understanding, but to perform an operation: to diagnose, to identify, to recognize, to trigger. And we could notice that as listening becomes increasingly operational sound does too. Operational acoustics: sounds made by machines for machine listeners. Adversarial acoustics: sounds made by machines *against* human listeners, and vice versa.
Another response would be to say that when or if machines listen, they listen "operationally": not in order to understand, or even facilitate human understanding, but to perform an operation: to diagnose, to identify, to recognize, to trigger [Andrejevic interview]. And we could notice that as listening becomes increasingly operational sound does too. Operational acoustics: sounds made by machines for machine listeners. Adversarial acoustics: sounds made by machines *against* human listeners, and vice versa [B Li].


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