Labour, Justice and the Mechanization of Interpretation
Trabajo, justicia y la mecanización de la interpretación

The biggest frontier of mechanization of the past ten years has been the automation, broadly speaking, of that particular type of human labour known as interpretation.

This includes the mechanization of recognition (for example, image recognition technologies used by security services), of translation (Google Translate), of searching for information (Bing or Google search engines), of understanding ("predictive algorithms" that know what books or movies you will like or what kind of propaganda will appeal to you, as used by Amazon, Netflix, or the Donald Trump campaign), of trust (blockchain technologies such as Bitcoin), and of negotiation ("smart contracts" as pioneered by firms such as Ethereum).

How do these technologies benefit business and why have they come to prominence now? In what ways are they a continuation of older business strategies for extracting as much value as possible from labour via mechanization, such as steam-powered manufacture? Why are they inextricably entangled with the degradation and exhaustion of the work of both humans and nonhumans? And why are they adding to threats to the earth's climate?

In seeking to address these questions, this article for a special issue of the journal Development on technology justice (for the published version see https://rdcu.be/bRQtQ) also suggests some possible pathways for future environmental and social movements. The article is available here in both English and Spanish.