Lukas Nöhrer

Working Title

Artificial Intelligence and the Useful Art Museum: A Cross-Disciplinary Approach Towards Machine Learning and its Implications in the Museum Sphere

Supervisors


Dr Abigail Gilmore (Institute for Cultural Practices) https://www.research.manchester.ac.uk/portal/abigail.gilmore.html

Dr Caroline Jay (Department of Computer Science)

https://www.research.manchester.ac.uk/portal/caroline.jay.html

50/50 split supervision between ICP and CS

 

Funding Body:

EPSRC

 

Overview of PhD

My project explores the contribution of Artificial Intelligence (AI) to art museums. Through practice-based, collaborative research with my partner institutions – the Manchester Art Gallery, The Whitworth, the National Gallery London and the Smithsonian – this project will develop knowledge of the role of AI in a cultural environment and understand what impact AI will have on public trust. Specifically, this research will investigate the following key questions: What is the role and potential use of Recommender Systems (RS) as a curatorial strategy? How can RS be used to interpret and classify existing collections, inform acquisition and meaningfully translate data? In what ways will the use of RS in museums challenge and/or enhance the public’s and the professional’s perception of emerging technologies? This PhD project combines a variety of aspects through researching machine learning techniques as experienced through their cultural engagement in a public museum. The public museum will therefore function as an interactive laboratory. This approach will not only foster human-computer interaction but will further investigate the applicability and usability of algorithmic outputs in a cultural setting – addressing trust issues, testing new strategies, exploring content creation and the policies of its future use in a technically informed society. I will question how machine learning may inform curatorial practice and whether it will introduce bias or as yet unpredictable and currently unknown patterns. This aims to push the art historical discourse beyond common boundaries, gathering knowledge with the help of algorithms and creating new connections between objects, their meanings and their place within collections. Furthermore, this project strives to then examine how audiences of the future work alongside AI to co-create meaning and understanding. It will investigate how AI informs museum audiences’ behaviour and their perception and understanding of the generated content.

Biography

I hold a BA in Art History and Philosophy (University of Vienna) and I studied Art and Digital Media at the Academy of Fine Arts Vienna. In December 2018, I graduated in Art Gallery and Museum Studies (MA) with Distinction at the University of Manchester, where I started my cross-disciplinary PhD in Museology + Computer Science in September 2019. My PhD research project was awarded an EPSRC studentship. I held several research positions at various universities. Currently I am working as a Research and Teaching Assistant at the Department of Computer Science of the University of Manchester. I further represent the university at the AI&Arts Group of the Alan Turing Institute.