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Spv: Anna-Kaisa Kaila

Anna-Kaisa Kaila
Anna-Kaisa Kaila doctoral student

Project 1: Ethical analysis and harm mitigation in creative-AI

Background

This project explores socio-ethical aspects of the current creative-AI (music, visual arts, performing arts, etc.) development or use practices. Artificial intelligence (AI) plays an increasingly important role in various types of creative media and art productions, but the study of the ethical implications is just getting started, and new ideas for interventions are needed to mitigate risks and harms.

Task

The purpose of this project is to provide a proposal for an intervention to steer the creative-AI field towards a more ethical and inclusive future. It can be, for instance, an ethical analysis tool for creative-AI developers, a method for artists to protect their work against unauthorised data scraping, an analysis of a dataset typically used for training generative AI models, a set of criteria for a (future) AI-fairness certification, or some other initiative for mitigating harm and promoting ethical and socially sustainable development and use practices in creative-AI domains. The proposal can be targeted at creative-AI developers, artist communities, or other relevant stakeholder groups.

The project will address questions of authorship/ownership in data and in art, access/exclusion, enrichment/exploitation, fairness, and diversity, among others.

Methods

To ground your proposal in the current state of affairs, the project starts with an analysis or mapping of a selection of suitable AI-tools and/or their developer or user communities. The applicable methodology could include interviews and surveys, (n)ethnographies, or workshops, among others. You will then use this data to form your intervention proposal and evaluate the conditions in which it may be adopted. Critical reflection on the political, economic, technological, and ideological contexts of AI tools and AI art production and reception is encouraged, where applicable.

Initial references

  • Selection of creative AI tools and services available at www.futurepedia.io/

  • Harry H. Jiang, Lauren Brown, Jessica Cheng, Mehtab Khan, Abhishek Gupta, Deja Workman, Alex Hanna, Johnathan Flowers, and Timnit Gebru. 2023. AI Art and its Impact on Artists. In Proceedings of AIES '23. DOI: doi.org/10.1145/3600211.3604681

  • Anna-Kaisa Kaila, Petra Jääskeläinen and Andre Holzapfel. 2023. Ethically Aligned Stakeholder Elicitation (EASE): Case Study in Music-AI. In Proceedings of the International Conference on New Interfaces for Musical Expression (NIME). www.nime.org/proceedings/2023/nime2023_18.pdf

  • Fabio Morreale. 2021. Where Does the Buck Stop? Ethical and Political Issues with AI in Music Creation. Transactions of the International Society for Music Information Retrieval, 4(1), pp. 105–113. DOI: doi.org/10.5334/tismir.86

Supervisor: Anna-Kaisa Kaila

Project 2: Reception studies of AI art

Background

Research on the use side of AI art has been under-explored in comparison to the development of tools for AI content generation. This project focuses on the reception and critique of AI art, taking a specific AI artwork or performance as a case study. Looking closely into the values presented in connection to presenting and critiquing of AI art provides critical understanding of how creative-AI tools and their output enters the social world of the art institutions and audiences. Analysis of the tensions inherent in these discourses will furthermore expose negotiations about questions of authorship, authenticity and algorithmic (co-)creativity.

Task

In this project, you will explore the cultural context of AI art reception. The purpose is to analyse the reception and critique, taking into various analytical perspectives (e.g. historical, economical, geographical, political, critical, legal, labor-related, technological, scientific, aesthetical, mythological, bodily, narrative, or symbolic). The reception can be contrasted for example with marketing narratives of AI tools, with process descriptions of the AI systems provided by the artists and developers (see Gotham et al 2022, Colton et al 2022), or with perspectives from producers, curators, and other gatekeepers of art institutions.

Methods

You can use for example content analysis of published critiques, online ethnographies, interviews or surveys. The case study examples could include the AI-musical Beyond the Fence, the KTH-produced opera The Tale of the Great Computing Machine, or any other relatively recent static, performative or musical artwork you find interesting.

In the analysis of the media texts, you could pay attention to aspects such as the topics discussed and arguments presented; agencies, patterns, and styles of the discourse; meanings and narratives expressed and negotiated; and values presented (or missing!). Pay close attention to the wider political, economic, technological, and ideological contexts of AI tools and AI art production and reception.

Initial references

  • Gotham, M. et al. 2022. Beethoven X: Es könnte sein! (It could be!). Proceedings of the 3rd Conference on AI Music Creativity 2022. DOI: doi.org/10.5281/zenodo.7088335

  • Colton, Simon, et al. 2022. The beyond the fence musical and computer says show documentary. arXiv preprint arxiv.org/abs/2206.03224

Supervisor: Anna-Kaisa Kaila