Work on Artificial Intelligence writ large has moved past laudatory excitement to one of vast critique. This recent scholarship has demonstrated the various racist and sexist biases embedded within algorithmic systems (Benjamin, 2017; Browne 2015; Noble, 2018). More recently, scholarship into AI has sought to define AI as part of longer histories of colonial exploitation and extraction (Couldry and Mejias, 2019). Others have argued for postcolonial or decolonial AI which is “about interrogating who is doing computing, where they are doing it, and, thereby, what computing means both epistemologically (that is, in relation to knowing) and ontologically (that is, in relation to being)” (Ali 2016, 20). Geographer Louise Amoore also defines AI not as the objective and all-encompassing thinking machine AI proponents claim, but instead an always already partial aperture. This method of doing ethics is not about claiming transparency, but about acknowledging the ways in which ethics, for humans and algorithms, is always emplaced and partial (Amoore, 2020). (read more...)