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These applications are all either currently in use by states, corporations and other entities around the world, or under development. The list is obviously not exhaustive. Nor does it convey the real diversity of markets, cyberphysical and political contexts into which these applications are quickly embedding themselves:
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Digital voice assistants - voice user interfaces - state and corporate surveillance - profiling - border security - home security - pre-emptive policing - weapons systems - court systems - hospital systems - call centre optimisation - disability services - grocery store wayfinding[[1](https://edition.cnn.com/2020/08/27/business/amazon-fresh-first-grocery-store/index.html)] - ambient elderly monitoring - baby monitoring - house arrest monitoring - human rights monitoring - remote education - school security - remote diagnostics - biomonitoring and personalised health - social distancing - music streaming - music education - composition - gaming - brand development - marketing - acoustic ecology - employee performance metrics - wearables - hearables - recruitment - banking - insurance ...
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Digital voice assistants - voice user interfaces - state and corporate surveillance - profiling - border security - home security - pre-emptive policing - weapons systems - court systems - hospital systems - call centre optimisation - disability services - grocery store wayfinding[[1](https://edition.cnn.com/2020/08/27/business/amazon-fresh-first-grocery-store/index.html)] - ambient elderly monitoring - baby monitoring - house arrest monitoring - [^andre_audio_1] - remote education - school security - remote diagnostics - biomonitoring and personalised health - social distancing - music streaming - music education - composition - gaming - brand development - marketing - acoustic ecology - employee performance metrics - wearables - hearables - recruitment - banking - insurance ...
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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.
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@@ -40,9 +40,8 @@ One way of responding to this possibility would be to simply bracket the questio |
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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.
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# Bibliography
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# Footnotes
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[^andre_audio_1]: Interview with [André Dao](https://andredao.com/) on September 4, 2020
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[^halcyon_audio_1]: Interview with [Halcyon Lawrence](http://www.halcyonlawrence.com/) on August 31, 2020.
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Sean Dockray