Spv: Anna-Kaisa Kaila

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

Background

Artificial intelligence (AI) plays an increasingly important role in various types of creative media and art productions. While there is increasing awareness of the risks inherent in these technologies, the mitigation efforts are in their infancy, and there are few established ethical and legal frameworks available specifically for the creative use of AI tools. Richly situated case studies in various creative domains (music, visual arts, performing arts) of AI are needed to identify vulnerabilities and risks of creative-AI, to mitigate the current and projected harms, and to support various creative industry stakeholders adopt ethical working practices for the future.

Task

This project explores ethical and/or legal aspects of the current creative-AI production and development practices. Questions addressed could include, for instance, authorship/ownership, access/exclusion and control/exploitation, or fairness and diversity. Drawing from an analysis of existing creative-AI tools, you will develop a proposal for ethical analysis, a specific self-regulation measure, or other harm mitigation practices. You could, for example, map the current state of affairs in the industry, provide real or speculative tools for artists to protect their work against malicious data use, propose options for AI-content watermarking or fairness certifications, or explore further the ethics analysis tool introduced in Kaila et al (2023). These proposals can be targeted for creative-AI developers, for artist communities, or for other relevant stakeholder groups.

Methods

A selection of suitable AI-tools, artworks or training datasets will be selected as the starting point of the project. Applicable methodology could include user studies, interviews, surveys, ethnographies, workshops, or (online) content analysis. 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

• AI Artists.org
• Selection of creative AI tools and services available at www.futurepedia.io/
• Mark Coeckelbergh. 2020. AI Ethics. MIT Press.

• 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. Examples could include the AI-musical Beyond the Fence, the KTH-produced opera The Tale of the Great Computing Machine, or other recent static, performative or musical artworks. 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

Rather than running a Turing Test on AI art audiences, you will explore the cultural context of AI art reception. This situates the reception and critique in their wide social contexts, 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 e.g. with marketing narratives, with process descriptions of the AI systems by the artists and developers (see Gotham et al 2022, Colton et al 2022), or with perspectives from producers, curators, and other (art) institutional gatekeepers.

Methods

The reception of the selected artwork may be studied using content analysis of published critiques, online ethnographies, interviews or surveys, specific art analytical methods (e.g. semiotic analysis), or by other qualitative or mixed methods. 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!).

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