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## Alexa, what is machine listening? ## Alexa, what is machine listening?


"Machine listening" is one common term for a fast-growing interdisciplinary field of science and engineering which uses audio signal processing and machine learning to "make sense" of sound and speech.[^Cella, Serizel, Ellis] Machine listening is what enables you to be "understood" by Siri and Alexa, to Shazam a song, and to interact with many audio-assistive technologies if you are blind or vision impaired [Alper]. As early as the 90s, the term was already being used in computer music to describe the analytic dimension of ['interactive music systems'](https://wp.nyu.edu/robert_rowe/text/interactive-music-systems-1993/chapter5/), whose behavior changes in response to live musical input.[^Rowe, Maier] It was also, of course, a cornerstone of the mass surveillance programs revealed by Edward Snowden in 2013: SPIRITFIRE's "speech-to-text keyword search and paired dialogue transcription"; EViTAP's "automated news monitoring"; VoiceRT's "ingestion", according to one NSA slide, of Iraqi voice data into voiceprints. Domestically, machine listening technologies underpin the vast databases of vocal biometrics now held by many [prison providers](https://theintercept.com/2019/01/30/prison-voice-prints-databases-securus/ "Prisons Across the U.S. Are Quietly Building Databases of Incarcerated People’s Voice Prints") and, for instance, the [Australian Tax Office](https://www.computerworld.com/article/3474235/the-ato-now-holds-the-voiceprints-of-one-in-seven-australians.html "The ATO now holds the voiceprints of one in seven Australians"). And they are quickly being integrated into infrastructures of development, security and policing.
"Machine listening" is one common term for a fast-growing interdisciplinary field of science and engineering which uses audio signal processing and machine learning to "make sense" of sound and speech.[^Cella, Serizel, Ellis] Machine listening is what enables you to be "understood" by Siri and Alexa, to Shazam a song, and to interact with many audio-assistive technologies if you are blind or vision impaired.[^Alper] As early as the 90s, the term was already being used in computer music to describe the analytic dimension of ['interactive music systems'](https://wp.nyu.edu/robert_rowe/text/interactive-music-systems-1993/chapter5/), whose behavior changes in response to live musical input.[^Rowe, Maier: 10.32-16.57] It was also, of course, a cornerstone of the mass surveillance programs revealed by Edward Snowden in 2013: SPIRITFIRE's "speech-to-text keyword search and paired dialogue transcription"; EViTAP's "automated news monitoring"; VoiceRT's "ingestion", according to one NSA slide, of Iraqi voice data into voiceprints. Domestically, machine listening technologies underpin the vast databases of vocal biometrics now held by many [prison providers](https://theintercept.com/2019/01/30/prison-voice-prints-databases-securus/ "Prisons Across the U.S. Are Quietly Building Databases of Incarcerated People’s Voice Prints") and, for instance, the [Australian Tax Office](https://www.computerworld.com/article/3474235/the-ato-now-holds-the-voiceprints-of-one-in-seven-australians.html "The ATO now holds the voiceprints of one in seven Australians"). And they are quickly being integrated into infrastructures of development, security and policing.


![Automatic speech recognition](audio:static/audio/kathy-reid-intro-to-ASR.mp3),[^kathy_audio_1] transcription and translation - ![Automatic speech recognition](audio:static/audio/kathy-reid-intro-to-ASR.mp3),[^kathy_audio_1] transcription and translation -
targeted key word detection {{< nosup >}}[[i](https://theintercept.com/2015/05/05/nsa-speech-recognition-snowden-searchable-text/ "How the NSA Converts Spoken Words Into Searchable Text")]{{< /nosup >}} - targeted key word detection {{< nosup >}}[[i](https://theintercept.com/2015/05/05/nsa-speech-recognition-snowden-searchable-text/ "How the NSA Converts Spoken Words Into Searchable Text")]{{< /nosup >}} -
@@ -90,20 +90,20 @@ gender vocal training {{< nosup >}}[[i](https://github.com/project-spectra "Proj


As with all forms of machine learning, questions of efficacy, access, privacy, bias, fairness and transparency arise with every use case. But machine listening also demands to be treated as an epistemic and political system in its own right, that increasingly enables, shapes and constrains basic human possibilities, that is making our auditory worlds knowable in new ways, to new institutions, according to new logics, and is remaking (sonic) life in the process. As with all forms of machine learning, questions of efficacy, access, privacy, bias, fairness and transparency arise with every use case. But machine listening also demands to be treated as an epistemic and political system in its own right, that increasingly enables, shapes and constrains basic human possibilities, that is making our auditory worlds knowable in new ways, to new institutions, according to new logics, and is remaking (sonic) life in the process.


Machine listening is much more than just a new scientific discipline or vein of technical innovation then. It is also an emergent field of knowledge-power and cultural production, of data extraction and colonialism, of capital accumulation, automation and control. We must make it a field of political contestation and struggle. If there is to be a world of listening machines, we must make it emancipatory [Data4BlackLives].
Machine listening is much more than just a new scientific discipline or vein of technical innovation then. It is also an emergent field of knowledge-power and cultural production, of data extraction and colonialism, of capital accumulation, automation and control. We must make it a field of political contestation and struggle. If there is to be a world of listening machines, we must make it emancipatory.[^exemplary projects]




## ~~Machine listening~~ ## ~~Machine listening~~


Machine listening isn't just machinic. 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](https://anatomyof.ai/ "Anatomy of an AI System").[^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 distant workers and permanently scars ecological systems [Joler interview].
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](https://anatomyof.ai/ "Anatomy of an AI System").[^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 distant workers and permanently scars ecological systems [Joler interview: 7.54 - 13.44].


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: 40.55-44.35]. 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.
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 - (<span class="soundcite" data-id="893380750" data-start="946000" data-end="1390000" data-plays="1">gendered and gendering</span>),[^YS] colonial and colonizing, ![raced and racializing](audio: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 [ref Germany/Abu Hamdan], 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. We have been becoming machine listeners for a long time. Indeed, the becoming machinic of listening is a foundational concern for any contemporary politics of listening; not because mechanisation itself is a problem, but because it is the condition in which we find ourselves.[^Abu Hamdan]
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 - (<span class="soundcite" data-id="893380750" data-start="946000" data-end="1390000" data-plays="1">gendered and gendering</span>),(15.46 - 23.10)[^YS] colonial and colonizing, ![raced and racializing](audio: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](https://www.theverge.com/2017/3/17/14956532/germany-refugee-voice-analysis-dialect-speech-software), 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. We have been becoming machine listeners for a long time. Indeed, the becoming machinic of listening is a foundational concern for any contemporary politics of listening; not because mechanisation itself is a problem, but because it is the condition in which we find ourselves.[^Abu Hamdan]


But machine listening isn't exactly listening either. But machine listening isn't exactly listening either.


@@ -119,14 +119,17 @@ Another response would be to say that when or if machines listen, they listen ![
# Footnotes # Footnotes


[^Cella, Serizel, Ellis]: LIBRARY [^Cella, Serizel, Ellis]: LIBRARY
[^Alper]: Meryl Alper, *Giving Voice: Mobile Communication, Disability*, and Inequality (MIT Press, 2017)
[^Rowe, Maier]: LIBRARY; Stefan Maier: [*Machine Listening*](https://technosphere-magazine.hkw.de/p/Machine-Listening-kmgQVZVaQeugBaizQjmZnY), Technosphere Magazine (2018) [^Rowe, Maier]: LIBRARY; Stefan Maier: [*Machine Listening*](https://technosphere-magazine.hkw.de/p/Machine-Listening-kmgQVZVaQeugBaizQjmZnY), Technosphere Magazine (2018)
[^intelligent_audio_analysis]: ![](bib:827d1f44-5a35-4278-a527-4df67e5ba321) [^intelligent_audio_analysis]: ![](bib:827d1f44-5a35-4278-a527-4df67e5ba321)
[^Abu Hamdan]: Interview with Lawrence Abu Hamdan [^Abu Hamdan]: Interview with Lawrence Abu Hamdan
[^airplanes]: ![](bib:6676af8a-7a4d-4aa8-af96-f26452f58753) [^airplanes]: ![](bib:6676af8a-7a4d-4aa8-af96-f26452f58753)
[^kathy_audio_1]: Interview with [Kathy Reid](https://blog.kathyreid.id.au) on August 11, 2020 [^kathy_audio_1]: Interview with [Kathy Reid](https://blog.kathyreid.id.au) on August 11, 2020
[^andre_audio_1]: Interview with [André Dao](https://andredao.com/) on September 4, 2020 [^andre_audio_1]: Interview with [André Dao](https://andredao.com/) on September 4, 2020
[^exemplary projects]: See for instance [Data 4 Black Lives](https://d4bl.org/programs.html), [Feminist Data Manifest-No](https://www.manifestno.com/) [add]
[^Crawford and Joler]: LIBRARY Anatomy of an AI [^Crawford and Joler]: LIBRARY Anatomy of an AI
[^Goldenfein]: LIBRARY (if jake's willing to share?) Jake Goldenfein, *Monitoring Laws: Profiling and Identity in the World State* (Cambridge University Press, 2019) https://doi.org/10.1017/9781108637657 [^Goldenfein]: LIBRARY (if jake's willing to share?) Jake Goldenfein, *Monitoring Laws: Profiling and Identity in the World State* (Cambridge University Press, 2019) https://doi.org/10.1017/9781108637657
[^McQuillan]: LIBRARY Data Science as Machinic Neoplatonism
[^halcyon_audio_1]: Interview with [Halcyon Lawrence](http://www.halcyonlawrence.com/) on August 31, 2020. [^halcyon_audio_1]: Interview with [Halcyon Lawrence](http://www.halcyonlawrence.com/) on August 31, 2020.
[^Virilio]: LIBRARY Paul Virilio, *Sightless Vision* [^Virilio]: LIBRARY Paul Virilio, *Sightless Vision*
[^Faroki, Paglen]: LIBRARY; Mark Andrejevic, [Operational Listening (Eavesdropping)](https://youtu.be/OxOKlgsc3_M), recorded on August 10, 2018 [^Faroki, Paglen]: LIBRARY; Mark Andrejevic, [Operational Listening (Eavesdropping)](https://youtu.be/OxOKlgsc3_M), recorded on August 10, 2018

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