Many years ago, artist Carla Gannis traveled to the Scrovegni Chapel in Padua, Italy. In the 1300s artist Giotto di Bondone painted the entire interior of this chapel with the most stunning frescoes, including seven depictions of Virtues and seven depictions of Vices. Good and evil were quite clearly delineated in these paintings, however Giotto's style as an artist represented a hybrid moment in western history, as Medieval philosophies, centered on strict religious and spiritual ideology, began to be challenged by a more human-centered view of life on the planet. Humanism was dawning and the Renaissance was on the horizon.
In Virtues and Vices seven absurd and comical post-human embodiments appear as animated altar piece figures -- developed using Unity from Gannis’s After Arcimboldo series, through a combination of uncanny mannerist painting and the popular networked language of Emoji.
In the twenty-first century, as the world faces biological, environmental, political, and technological crises, humankind is at a new crossroads. An anthropogenic worldview has failed the planet, and notions of good and evil, truth and fiction, exist in a state of socially mediated moral relativism. Posthumanism, a theory with at least seven different definitions currently, is no longer a fringe concept, and there has been an emergence of churches and religious sects who now worship "AI" as a deity.
These moving-image "virtues and vices" represent the strange theater of life we live in today and present a pantheon for the century – figures of virtuosity and sin for a decolonized, post-human, feminist future – and, in this work, they act as guides and tricksters through virtual worlds beyond. The patterns lining each of the altarpiece cabinets have been generated by training an AI on the themes each "actor" represents.
Virtues and Vices 2 features Lady Ava Interface, a machine learning assistant to cultural institutions; Lucille Trackball, an AI stand-up comedian; C.A.R.L.A. G.A.N., Crossplatform Avatar for Recursive Life Action Generative Adversarial Network, 2021