Update 'content/topic/against-the-coming-world-of-listening-machines.md'

content/topic/against-the-coming-world-of-listening-machines.md

@@ -6,7 +6,7 @@ has_lessons: []
 
 ## 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]. 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. As early as the 90s, the term was already being used in computer music to describe the analytic dimension of 'interactive music systems', whose behavior changes in response to live musical input [Rowe]. 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 and, for instance, the Australian Tax Office. 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', 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 [ref] and, for instance, the Australian Tax Office [ref]. And they are quickly being integrated into infrastructures of development, security and policing.
 
 Automatic speech recognition, transcription and translation - targeted key word detection - vocal biometrics and audio fingerprinting - speaker verification, differentiation, enumeration and location - personality and emotion recognition - accent identification - sound recognition - audio object recognition - audio scene analysis - intelligent audio analysis - audio event analysis - audio context awareness - music mood analysis - music identification - music playlist generation - audio synthesis - speech synthesis - musical synthesis - adversarial music - audio brand recognition - aggression detection - depression detection - laughter detection - stress detection - distress detection - intoxication detection - scream detection - lie detection - gunshot detection - autism diagnosis - parkinson's diagnosis - covid diagnosis - machine fault diagnosis - bird sound identification - gender identification - ethnicity detection - age determination - voice likeability determination - risk assessment ...
 
@@ -16,21 +16,20 @@ Digital voice assistants - voice user interfaces - state and corporate surveilla
 
 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.  
+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. And if there is to be a world of listening machines, we must ensure it is emancipatory.   
 
-The problem isn't a world of listening machines. Just the one that is coming.
 
 ## ~~Machine listening~~
 
 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 [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 [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].
 
 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. This must become the starting point of a contemporary politics of listening.
+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 [YS], colonial and colonizing, ![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.
 
@@ -40,7 +39,7 @@ Even if machine listening did work by analogising human audition, the question o
 
 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 [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 [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].
 
 
 # Footnotes