Georgy Ègor Kraft: Content Aware Studies Series
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- Content Aware Studies Series
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Content Aware Studies series initiate an inquiry into the possibilities of AI and particularly Machine Learning to reconstruct and generate lost antique greek and roman friezes and sculptures by the means of algorithmic analysis of 3D scans of antiquity. It concerns about the potentialities of methods involving data, ML, AI and other forms of automations turning into semi-and-quasi–archeological knowledge production and interpretations of history and culture in the era of ubiquitous computation. Some of these algorithmic out- puts are turned into new machine-fabricated sculptures uncanny in their algorithmic integrity. They render the work of synthetic agency that lends a faithful authenticity to the forms, while also producing bizarre errors and algorithmic normalisations of forms previously standardised and regulated by the canon of Hellenistic and Roman art.
These speculative forms of restoration, museology, and historiography provide a case study for critical examination of misleading trajectories in knowledge production and epistemic focal biases that occur at the level of computational software operations. Preoccupied with ontologies derived from biases, misleading guises, seeming authenticities and mixed-up materialities it seeks to highlight and warn about epistemological issues of computationally accelerated studies. The series focuses on questions: what are the ethical, philosophical, and historical challenges we’re facing when using computationally automated means of knowledge production and investigation? What epistemics do such methodologies hold by uncovering deeper and sharply unsuspected new knowledge or instead masking unacknowledged biases?
In the optics of a non-human agency of the AI-investigator, what of our historical knowledge and interpretation encoded into the datasets will survive this digital digestion? How are historical narratives, documents, their meaning, and function perverted when their analysis has been outsourced to machine vision and cognition? In other words, what happens to historical knowledge and documentation in the age of information-production epidemic and computational reality-engineering?
