Description
Our fuel is the desperation of screen-saturation and lack of connectedness that this weird year has set in our bodies, so many things happening, and us, seeing each other framed by little screens…
- Carbon intensity of online connections. How not to die in another ethics webinar.
Further information
The physical/mental intensity and many varied costs of digital existence. The impacts this way of living has upon the earth and nature, including ourselves as interconnected nodes in the ecosystem. The ways we manufacture and use technologies currently, come with huge environmental and human costs. A goldrush tends to happen, where a new innovation is given infinite green lights, to pollute, to extract data, to displace peoples, and to bypass regulations, if such regulations even exist. As Crawford and Joler point out, ‘at every level contemporary technology is deeply rooted in and running on the exploitation of human bodies’ (2018). Even the efforts to mitigate the planetary harms, reducing carbon emissions of AI are funnelled through the same logics that created our current crises.
And yet, I have no choice but to let Microsoft mediate my professional interactions. We are being forced to collectively investigate the sustainability of our online lives, the impact on our mental health, our connections to others, and the kinds of realities we seek and experience.
Making something sustainable is about more than mitigation. A whole nexus of interactions, infrastructure, and procedures are at play, and not every part is equally visible. Quantifying carbon emissions is an increasingly hard task that, ironically, only an AI could do. The carbon footprint of a single machine learning network depends upon ‘the location of the training server and the energy grid it uses, the length of the training procedure, and the hardware on which the training takes place’ (Dhar, 2020, p. 424). The supposed neutrality of carbon intensive AI creates a spiralling situation, in which an ‘exponentially larger model is required, which can come in the form of increasing the amount of training data or the number of experiments, thus escalating computational costs, and therefore carbon emissions’ (ibid., p. 425)
Tweaking existing models of production and usage cannot be sufficient, and can lead a supposed green initiative to conceal greater planetary abuses. We must reconceive our collective relationships to the earth, to its ecosystems, and its materials.
Resources
- Crawford, Kae and Vladan Joler, “Anatomy of an AI System: The Amazon Echo As An Anatomical Map of Human Labor, Data and Planetary Resources,” AI Now Institute and Share Lab, (September 7, 2018) https://anatomyof.ai