From 232d7d14dd5fa5fbef820cc10f254d1288e2df36 Mon Sep 17 00:00:00 2001 From: james Date: Fri, 11 Sep 2020 04:48:56 +0000 Subject: [PATCH] Update 'content/topic/against-the-coming-world-of-listening-machines.md' --- .../against-the-coming-world-of-listening-machines.md | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/content/topic/against-the-coming-world-of-listening-machines.md b/content/topic/against-the-coming-world-of-listening-machines.md index a38d053..2741847 100644 --- a/content/topic/against-the-coming-world-of-listening-machines.md +++ b/content/topic/against-the-coming-world-of-listening-machines.md @@ -25,7 +25,7 @@ Machine listening isn't just machinic. Materially, it entails enormous exploitation of both human and planetary resources: to build, power and maintain the vast infrastructures on which it depends, along with all the microphones and algorithms which are its most visible manifestations [Crawford and Joler]. Even these are not so visible however. One of the many political challenges machine listening presents is its tendency to disappear at point of use, even as it indelibly marks the bodies of workers and permanently scars environments and the atmosphere [Joler interview]. -Scientifically, machine listening demands enormous volumes of data: exhorted, extracted and appropriated from auditory environments and cultures which, though numerous already, will never be diverse enough. This is why responding to machinic bias with a politics of inclusion is necessarily a trap [HL excerpt]. It means committing to the very system that is oppressing or occluding you: a "techno-politics of perfection" [^Goldenfein]. +Scientifically, machine listening demands enormous volumes of data: exhorted, extracted and appropriated from auditory environments and cultures which, though numerous already, will never be diverse enough. This is why responding to machinic bias with a politics of inclusion is necessarily a trap [HL excerpt]. It means committing to the very system that is oppressing or occluding you: a "techno-politics of perfection." [^Goldenfein] 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. @@ -33,13 +33,13 @@ Moreover, because machine listening is so deeply bound up with logics of automat 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 [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 [^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](https://medium.com/@krishna_84429/audio-classification-using-transfer-learning-approach-912e6f7397bb "Audio classification using transfer learning approach"), in the sense that they work by first transforming sound into spectograms. Many work by combining auditory with other forms of data and sensory inputs: machines that [listen by looking](https://www.wired.com/story/lamphone-light-bulb-vibration-spying/ "Spies Can Eavesdrop by Watching a Light Bulb's Vibrations"), 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 [^airplanes]. Speech recognition needed to untether itself from "human sensory-motor phenomenon" in order to start recognising speech. Airplanes don't flap their wings [^airplanes]. -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. +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" [^Virilio], 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 [Faroki, Paglen]: 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]. +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].[^Faroki, Paglen] 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 excerpt]. # Footnotes @@ -50,3 +50,5 @@ Another response would be to say that when or if machines listen, they listen "o [^andre_audio_1]: Interview with [André Dao](https://andredao.com/) on September 4, 2020 [^Goldenfein]: Jake Goldenfein, *Monitoring Laws: Profiling and Identity in the World State* (Cambridge University Press, 2019) https://doi.org/10.1017/9781108637657 [^halcyon_audio_1]: Interview with [Halcyon Lawrence](http://www.halcyonlawrence.com/) on August 31, 2020. +[^Virilio]: Paul Virilio, *Sightless Vision* +[^Faroki, Paglen]: biblio refs \ No newline at end of file