Following the completion of the training series “AI in Artistic Practice: Rights, Protection, Opportunities”

2025-12-16

The training series “AI in Artistic Practice: Rights, Protection, Opportunities” took place in October-November 2025. In response to the rapidly changing innovations and regulations in generative artificial intelligence (GenAI), the aim was to strengthen the legal and professional awareness of artists so that their work would not only be innovative but also protected. It also looked at various non-creative aspects of GenDI that could help contemporary culture makers in their work routines. To ensure wider accessibility and effectiveness of the training, we are sharing a series of teaching materials.

The training program consisted of:

• October 21: Justinas Drakšas’ presentation “Authorship of AI-generated works and AI-related copyright infringements,” which discussed the new challenges posed by GenAI tools to the traditional copyright protection system and how this is relevant to authors dealing with GenAI.
• On October 27, Agnė Gintalaitė’s artist talk “Notes from the Synthetic Field: From the Poetics of Error to the Cannibalism of Algorithms,” in which Agnė presented her practice and spoke about the dangers of trying to give GenAI human characteristics. She pointed out that the widespread use of GenAI generates a lot of model-generated data, which is then used to train new models, creating curious entities that are no longer close to reality.
• November 5, Ignas Pavliukevičius’ artist talk “Me, You, and Robots: New Forms of Intimacy with Digital Beings,” in which Ignas presented his dissertation research “Thinking and Feeling Technologies in Art” and spoke about cases where GenAI’s deceptively human qualities are accepted, triggering emotional attachment (e.g., GenAI romantic partners).
• On November 19 and 25, during workshops led by Ignas Pavliukevičius, participants had the opportunity to familiarize themselves with the GenAI tools used by the artist (3D, video, images, sound) and create their own AI model assistant. The workshop was based on Ignas’s dissertation research and a digital copy of Ignas Pavliukevičius, Ignas Dern, was created.
• On November 28, Paulius Briedis, founder of the Robotics School, presented a remote presentation “AI in my studio. My enemy, my thief, my assistant, my voice.” The session was dedicated to sharing tips on how AI models can help with creative experiments, administrative, communication, or legal tasks, and discussing cases where GenAI can become an enemy by reworking artists’ content.

Advice from Justinas Drakšas, a doctoral student at the Faculty of Law of Vilnius University, for authors dealing with GenAI:

1. If you want to use GenAI for your creative work
   In order to increase the likelihood that works created with the help of GenAI will be eligible for copyright protection, it is necessary to ensure sufficient creative input and control by the author (human) during the creative process.
   To this end, it is important to assess whether the inputs provided are sufficiently detailed and creative, whether (and how) the parameters for generating the work were limited (set),
   whether the work was additionally edited (with or without the help of AI),
   whether it was the author (human) who made decisions about the form, structure, content, and essential elements of the work, how else the author’s (human) contribution to the work was manifested.
   The more essential creative decisions are made by a human being, the more likely it is that the work will be considered the result of human creative activity and will be eligible for protection.
2. If you want to check whether GenAI was trained using your work
   To assess whether your works were used to train the GenAI model, it is useful to check unofficial tools designed for this purpose, such as haveibeentrained.com,
   to familiarize yourself with summaries of the content used to train AI models, which, in accordance with EU legislation, should soon be published by GenAI platforms (however, these summaries will only provide generalized information and will not name all specific pieces of content used).
   If GenAI is able to reproduce at least part of the work in its responses, this could also be an indication that GenAI was trained using this work (although this may not be the case in all instances).
3. If you do not want GenAI to use your works
   If you do not want your works published on the internet to be used for training GenAI models, consider exercising your right to opt out of text and data mining.
   Authors can use computer-readable means (e.g., metadata) to clearly indicate that they reserve the right to use their works; in this case, AI model developers cannot use such works without the author’s permission.
   Furthermore, even if you have not exercised your right to opt out, this does not necessarily mean that GenAI platforms do not require your consent for their activities. Early court rulings in the EU indicate that consent must be obtained for the training of GenAI platforms when, for example, song lyrics are memorized and later presented in GenAI responses.

An audio recording of Justinas Drakšas’ lecture can be found here (in Lithuanian): https://youtu.be/TP7MftqFEsk
Slides from Justinas Drakšas’ presentation updated in line with the latest regulatory changes (in Lithuanian): Justinas Drakšas. DI generuojamų kūrinių autorystė ir su DI susiję autorių teisių pažeidimai

The speakers invited to the training series shared reading recommendations that would help develop a critical relationship with GenAI and AI models:

• AI: Toupin, Sophie. “Shaping feminist artificial intelligence.” New Media & Society 26, no. 1 (2024): 580-595.
• Bridle, James. 2022. Ways of Being: Animals, Plants, Machines: The Search for a Planetary Intelligence. New York: Farrar, Straus and Giroux.
• Delacroix, Sylvie. “Sustainable Data Rivers? Rebalancing the Data Ecosystem That Underlies Generative AI.” Critical AI 2, no. 1 (2024).
• Manovich, Lev, and Emanuele Arielli. “Artificial Aesthetics.” 2024. https://manovich.net/index.php/projects/artificial-aesthetics.
• “AI Decolonial Manyfesto.” manyfesto.ai 

You can view the slides from Ignas Pavliukevičius’ workshop (in Lithuanian):  Igno Pavliukevičiaus dirbtuvės „Aš, tu ir robotai: naujos intymumo formos su skaitmeninėmis būtybėmis“

Photo by Jonas Balsevičius.
The project is financed by the Lithuanian Council for Culture.