current research

Digital Photography: mediation, memory & visual communication

This project aims to address the social impact of major shifts in the production, distribution, viewing and storage of photographic images which have profoundly altered their everyday use. By adopting an interdisciplinary, user- centred approach to digitally networked photography, the project will provide a more holistic understanding of how photographs mediate communication, sociality and memory in the present. Expected outcomes include generating original empirical data, building international collaboration, and creating a new conceptual framework for assessing contemporary photographic practices. The research will provide community benefit by enabling insight into the social and ethical tensions affecting photography in the present.Funded by ARC Linkage Grant


An ongoing collaboration between Jasmin Pfefferkorn and Emilie K. Sunde.

Our everyday activities are increasingly co-produced by machine learning (ML), as the computational enters areas of creative production, urban spaces, and cultural institutions. We explore and provide insights into how the digital is operationalized – in text to image AI, in computational photography, in natural language processing, biometric surveillance, among other processes.

The generative potential of code is taking new forms. This has positioned us within a paradigmatic shift, which asks us to navigate new ways of seeing and making sense of sense-making. Our research is guided by two core questions:

How are aesthetic processes – sense-making and world-building – emerging in the computational era?

What interventions and insights can critical humanities scholars offer in exploring and contextualising these processes?

CODED AESTHETICS aims to encourage transdisciplinary forms of knowledge sharing and production. There is a distinct two-way delay between the knowledge produced in the field of computer science (CS) and HASS disciplines. More than this, there is a gap between the knowledge produced by academics researching computational aesthetics, and knowledge accessible to the general public.

Machine learning has created new epistemic boundaries. CODED AESTHETICS works to provide a comprehensive review of how computational perceptions inform and are informed by aesthetics.

    Decentering Ethics with AI Art

    Technological change always out-paces ethical governance, producing an uncertain space between what machines can do, and what is considered acceptable by diverse publics. This forthcoming edited volume argues that artists and cultural institutions are vital to the construction of a public ethics of human-machine assemblages. Working quickly, speculatively, and often provocatively, artists articulate ethical tensions as they emerge in the cultural domain, feeding the development of ethical governance. Observing a shift in public discourse that has spanned AI’s logical capability, to AI’s creative capability, we are now at a moment in time where AI’s ethical capability is coming to the forefront of discussion and debate.
    Funded by CAIDE

    Generative technology uptake in museum practice

    Generative technologies – machine learning, deep learning – are increasingly entering into museum practice. Their uptake raises ethical questions for institutions that play a significant role in our collective cultural memory. Exploring generative technology across curation, conservation, communication, communities, and collections, this research aims to unpack the role of emerging technologies within the museum assemblage, and the ethical tensions that arise as a result. 
    Funded by The University of Melbourne, Melbourne Postdoctoral Fellowship Scheme