Artificial intelligence and institutional critique 2.0: unexpected ways of seeing with computer vision

Algorithmic epistemologies and methodologies: Algorithmic harm, algorithmic care and situated algorithmic knowledges

“…The examples I have elaborated on here, Pereira and Moreschi's (2020) work which aimed to see art from an AI's perspective and Giaccardi's (2016; work on things as co-ethnographers, show the value of 'working with algorithms' and taking their viewpoint seriously for research. There is more work in this area but my selection of these examples highlights the possibilities for geographers.…”

“…By asking what it sees, we can potentially glimpse inside its black box but more than that we also are offered a different perspective. Pereira and Moreschi (2020) are not the first to position the glitch as a means to seeing in different ways. The glitch is at the core of Russell's (2013; 'glitch feminism', which reframes glitches as errata or corrections, 'happy accidents', that resist existing structural binaries.…”

“…Harnessing ‘their “glitchy” capacity to level and reimagine’, Pereira and Moreschi (2020: 1) argue that these misinterpretations ‘can also serve as a new way of reading art’. Being interested in the way the AI views art brings a ‘fresh denaturalised set of “eyes”’ to art, and because AIs can only interpret the world based on their experiences, could its interpretations of art tell us something about its experiences (Pereira and Moreschi, 2020: 2)? By asking what it sees, we can potentially glimpse inside its black box but more than that we also are offered a different perspective.…”

“…In Pereira and Moreschi’s work, the AI’s glitchy perspective illuminates different conceptualisations of the world that can productively unsettle ‘the relations between what we see and what we know in new ways’ (Cox, 2017: 14; Pereira and Moreschi, 2020: 3). Here, Pereira and Moreschi have essentially used the AI as a co-researcher, asking how it sees art, and by extension, how its perspective could help us see the world in different ways.…”

“…We can ask things of it, to which it can respond in a manner that we understand. In an exploratory work, Pereira and Moreschi (2020) ran an image identifying AI through an art collection to see how the AI interpreted the artworks. Based on the assumption that these types of AI have been trained in a product-focussed and profit driven sociotechnical system, they understood that its responses would be informed by its training background (Pereira and Moreschi, 2020: 1).…”