!publish!

content/factor/stillnotrobots.md

@@ -72,6 +72,15 @@ During the pandemic, this exclusion defined at least two different models of car
 
 
 
+
+**Social Reproduction and Hyperemployment**
+
+>The histories of machines, femininity, and waged labour have long been understood as deeply entangled and mutually constitutive. This merging of woman, machine, and work is taken in a new direction in the twenty-first century, with the advent of the “digital assistant”. These applications are knowledge navigators, available as part of various operating systems, which recognise natural speech, and use this ability to help answer user’s queries and to aid in organizational tasks, such as scheduling meetings or setting reminders. Perhaps the most famous of these is Apple’s Siri – now widely recognised as the voice of the iPhone – but there are several others, including GoogleNow and Microsoft’s Cortana, all of which perform similar functions with varying degrees of efficiency. The connections between these digital assistants and the conventions of low-status clerical work are obvious; Microsoft even went so far as to interview human PAs whilst developing Cortana, and a reviewer from Wired magazine declared that using Siri is: ‘kind of like having the unpaid intern of my dreams at my beck and call, organizing my life for me’ (Chen, 2011: n.p.). These apps represent, in many respects, the automation of what has been traditionally deemed to be women’s labour. [...] This brings us to the topic of ‘hyperemployment.’ What do we mean by this term? Hyperemployment is an idea, advanced by Ian Bogost, which links contemporary technological developments with a qualitative and quantitative change in personal workloads. His argument is that technology – far from acting in a labour-saving capacity – is in fact generative of ever more tasks and responsibilities. 
+
+from: Helen Hester, [Technically Female: Women, Machines, and Hyperemployment](https://salvage.zone/technically-female-women-machines-and-hyperemployment/), Salvage magazine, 2016.
+
+**Make-up for the voice**
+
 >Accents are a constant hurdle for millions of call center workers, especially in countries like the Philippines and India, where an entire “accent neutralization” industry tries to train workers to sound more like the western customers they’re calling – often unsuccessfully. As reported in SFGate this week, Sanas hopes its technology can provide a shortcut. Using data about the sounds of different accents and how they correspond to each other, Sanas’s AI engine can transform a speaker’s accent into what passes for another one – and right now, the focus is on making non-Americans sound like white Americans. 
 [...]
 Narayana said he had heard the criticism, but he argued that Sanas approaches the world as it is. “Yes, this is wrong, and we should not have existed at all. But a lot of things exist in the world – like why does makeup exist? Why can’t people accept the way they are? Is it wrong, the way the world is? Absolutely. But do we then let agents suffer? I built this technology for the agents, because I don’t want him or her to go through what I went through.” The comparison to makeup is unsettling. If society – or say, an employer – pressures certain people to wear makeup, is it a real choice? And though Sanas frames its technology as opt-in, it’s not hard to envision a future in which this kind of algorithmic “makeup” becomes more widely available – and even mandatory.