Emotion is an important part of human experience, but also a difficult concept to quantify. In a world where machines are being harnessed to do just this, Mark’s practice has developed from a curiosity to understand these complex technologies, question their algorithmic biases and explore the breadth of our emotional spectrum as human beings.
Mark’s in depth exploration of text sentiment analysis technology serves as the basis for this recent body of work. The technology attempts to derive emotional content from written text. Much like facial emotion detection, it relies on a classical view of how emotions work in which there is a common belief that universal emotions are somehow innate in our behaviour and expression.
Through extracting data from multiple charged thematic texts, research papers and articles, his work aims to engage the viewer with this textual content, as well as encourage us to question the technology. In his debut solo show, collectors can generate outputs from this core research data set.
Image credit: (Detail) Mark Webster, Hypertype, 2022. Sample output. Image courtesy of the artist.
