Project knole: an autocosmic approach to authoring resonant computational characters

Project knole, consisting of this thesis and a mixed reality installation artwork centred around a computational simulation, is a practice-based response to the question of how a character in a work of computational narrative art might maintain their defining quality of dynamic agency within a system (arguably one of the key potentials of the form), while achieving the ‘resonant’ qualities of characters in more materially-static artforms. In all aspects of this project, I explore a new design philosophy for achieving this balance; between the authorship of a procedural computational system, and the ability of that system to ‘resonate’ with the imagination of an audience. This philosophy, which I term the ‘autocosmic’, seeks inspiration for the curation of audience response outside the obvious boundaries of artistic discipline, across the wider spectrum of human imaginative engagement; examples often drawn from mostly non-aesthetic domains. As well as defining the terms ‘resonance’ and ‘autocosmic’, and delineating my methodology more generally, this thesis demonstrates how the ‘autocosmic’ was employed within my creative work. In particular, it shows how some of the perennial problems of computational character development might be mediated by exploring other non-aesthetic examples of imaginative, narrative engagement with personified systems. In the context of this project, such examples come from the historio-cultural relationship between human beings and the environments they inhabit, outside of formal artistic practice. From this ‘autocosmic’ launchpad, I have developed an artwork that starts to explore how this rich cultural and biological lineage of human social engagement with systemic place can be applied fruitfully to the development of a ‘resonant’ computational character

Music composition in the 21st Century: exploring concertgoers’ aesthetic response to AI-generated music.

Masters degree. University of KwaZulu-Natal, Durban.We live in the information age where digitisation and computational technology have become integral and indispensable to our daily activities. Artificial intelligence (AI), quantum computing, and other such technologies increasingly impact and disrupt our lives as we connect with our world. Within the arts, a field once dominated by human creation, we now experience a penetration of AI and deep learning technologies. The researcher, a practising musician, became interested in how our ubiquitous interaction with AI technology affects our decision-making and how it relates specifically to the field of music composition. The manifestation of AI’s impact on music-making was met with the researcher’s excitement and trepidation. Given the researcher’s apprehension, he proposed investigating (1) the quality of AI creativity in the field of music composition and (2) how transparency of this AI creative employment affects aesthetic judgement. He designed his research using a mixed methods approach, comprising a quantitative phase in the form of an online questionnaire (based on the original AESTHEMOS instrument), followed by a qualitative phase of in-depth interviews. The researcher’s objectives were twofold: (1) to establish if a sample of concertgoers could discern aesthetically between compositions generated by humans and AI and (2) how knowledge of AI use during the compositional process affects our aesthetic appreciation of the artefacts. The researcher partly hypothesised that participants could not discern aesthetically between human and AI-generated compositions because of current available AI technology (through machine and deep learning). However, when AI employment is disclosed, aesthetic responses to compositions yield a negative response. To test his hypothesis, the researcher engaged thirty concertgoers in Amsterdam, The Netherlands, to evaluate aesthetically five symphonic works via an online questionnaire. During the follow-up interview process, the AI generation of two of the five compositions was disclosed, and general attitudes toward AI creativity was probed. Using data analytic tools such as the Mann-Whitney U test, the researcher confirmed his hypothesis and concluded that participants interact aesthetically with AI-generated compositions if they appear to be human-composed. Transparency of AI involvement, however, affects the aesthetic value of AIgenerated compositions. As AI weaves itself deeper into the human story, the familiarity of AI creativity will profoundly affect our notion of creativity, meaning and art creation of the future