Embarking on the innovative field of generative artificial intelligence (AI), a set of tools that redefine the boundaries of art and creativity, it presents both challenges and opportunities. Just as in the pioneering era of cinema, when the desire to creatively explore new technology extended beyond the laboratories of film inventors and the first experimental films began to appear. Filmmakers today are using generative AI tools to expand their knowledge of the medium, explore new ways of imagination and storytelling, and show audiences the wonders of the moving image. With more than a century of experience, the film industry has reinvented itself countless times and changed its ways almost every decade of its history. Today's techniques in filmmaking are no exception and are rooted in a shared spirit of innovation and a desire to create immersive experiences that transport audiences to new realities. 

Generative AI is revolutionising cinema by using algorithms to write scripts, compose music, model environments, and create characters, challenging traditional creative practices and economic models. While it offers cost-effective and accessible filmmaking, ethical concerns arise. It brings forth a wave of change that could reshape the very fabric of how ideas are conceived and realised. It prompts us to rethink traditional notions of art in light of these new technologies, which are having a transformative impact on creativity, authorship, and the notion of "medium" in art (Manovich & Arielli, 2024). As we integrate generative AI into our technological landscape, it is imperative that we adopt a methodical and thoughtful strategy. This approach should ensure that AI operates as an ethically-aligned augmentation of human ingenuity, contributing positively to our cultural diversity without eclipsing the intrinsic human essence that forms the core of all artistic endeavours.

The rise of generative AI is both a technological and a cultural leap that requires a comprehensive understanding of its implications. As we stand on the border between algorithms and art, it is necessary to consider not only the position of aesthetics but also the ethical aspects that accompany this shift. Along with the ongoing debate about the importance of context in the creation of meaning, our uniqueness in content creation, ourminteractions with AI systems that mimic human outcomes, and our interchangeability in the roles of content interpreters (Floridi, 2023), it is necessary to address the pre-existing risks that generative AI poses, including transparency, bias, privacy, or human oversight (European Commission Directorate-General for Research and Innovation, 2024), and to reflect on the rights of individuals and strive to achieve a balance that promotes progress by creating processes that enable open, inclusive, and timely exploration of innovation and its potential consequences (Piskopani et al., 2023). 

The opacity of AI operations raises concerns about the authenticity of AI-generated art. Potential bias in AI systems could mirror and intensify existing prejudices, leading to homogeneity in art and marginalisation of underrepresented voices. Privacy issues emerge when AI uses artworks without consent, causing artists to fear unauthorised use of their work for training of generative AI tools. The debate about human oversight of the use of AI in the arts is intense, and opinions vary on the level of human intervention that is necessary for the ethical use of AI in creation. Defining the boundaries of a medium that inherently transcends them remains a challenge.

To navigate these complexities, the art community might consider setting ethical standards for the use of generative AI in the creation and adopting transparent labelling to differentiate between work produced by AI and work created by humans. Taking steps to mitigate bias, where possible, could involve using diverse datasets for training and regularly auditing the AI’s outputs for bias. If AI is used to generate art based on personal data, artists should ensure that they have obtained the necessary permissions and that the data is stored and used securely. While AI can generate art or part of an artwork, the final decision on what is presented to the public should rest with a human. This ensures that the artwork aligns with the artist’s vision and ethical standards. The art community should foster open discussions about the ethical implications of AI in art. In this way, artists and audiences can better understand the issues at stake and contribute to the development of ethical guidelines that, in a complex techno-social world, help to keep the public good and human flourishing foremost in mind (Flick & Worrall, 2022). The common goal should be to achieve a new harmonious balance that honours artistic creation while enlighteningly welcoming the new possibilities of generative AI.

References

European Commission Directorate-General for Research and Innovation. (2024). Ethics Guidelines for Trustworthy AI. European Commission. https://research-and-innovation.ec.europa.eu/document/download/2b6cf7e5-36ac-41cb-aab5- 0d32050143dc_en?filename=ec_rtd_ai-guidelines.pdf

Floridi, L. (2023). AI as Agency Without Intelligence: on ChatGPT, Large Language Models, and Other Generative Models. Philosophy & Technology, 36 (1). https://doi.org/10.1007/s13347-023-00621-y

Flick, C., & Worrall, K. (2022). The Ethics of Creative AI. In Springer series on cultural computing (pp. 73–91). https://doi.org/10.1007/978-3-031-10960-7_5

Manovich, L., & Arielli, E. (2024). Artificial Aesthetics: Generative AI, art and visual media. http://manovich.net/index.php/projects/artificial-aesthetics

Piskopani, A. M., Chamberlain, A., & Holter, C. T. (2023). Responsible AI and the Arts: The Ethical and Legal Implications of AI in the Arts and Creative Industries. In Proceedings of the First International Symposium on Trustworthy Autonomous Systems (TAS '23). Association for Computing Machinery, New York, NY, USA, Article 48, 1–5. https://doi.org/10.1145/3597512.3597528

Michal Gladis is a PhD candidate whose research centers around ethics and human values in technology, as well as the impact of AI on human cognition, emotions, and behavior. His thesis explores the design of AI assistant technology ecosystems with a greater emphasis on human participation and value sensitivity. Michal holds degrees in Film Studies, as well as in Semiotics, Communication and Media from Charles University in Prague, Czech Republic.