Auli Viidalepp

Recently, there have been significant advances in the development of language-transformer models that enable statistical analysis of co-occurring words (word prediction) and text generation. One example is the Generative Pre-trained Transformer 3 (GPT-3) by OpenAI, which was used to generate an opinion article (op-ed) published in “The Guardian” in Septem- ber 2020. The publication and reception of the op-ed highlights the difficulty for human readers to differentiate a machine-produced text; it also calls attention to the challenge of perceiving such a text as a synthetic text even when its origins are made explicit. This article offers a critical examination of the process behind the generation and the interpretation of a synthetic text, framing it as an example of generative literature. Lotman’s concept of the text and its sociocommunicative functions offers a framework for understanding how and why the output of a natural language generator may be interpreted as a (human-written) text. This article also inquires whether the generative output can be called a text in a Lotmanian sense and how the output is textualized (attributed meaning) in the process of interpretation.

The thesis introduces and criticizes the discourse on technology, with a specific reference to the concept of AI. The discourse on AI is particularly saturated with reified metaphors which drive connotations and delimit understandings of technology in society. To better analyse the discourse on AI, the thesis proposes the concept of “Expected AI”, a composite signifier filled with historical and sociocultural connotations, and numerous referent objects. Relying on cultural semiotics, science and technology studies, and a diverse selection of heuristic concepts, the thesis delves beneath the surface of AI discourse and demonstrates the hidden political, social, cultural, and ecological dangers of AI. The entanglement of the discourse(s) with (science) fiction, folklore, myth, and religion impacts how AI is perceived and received, as well as the expectations to AI-enabled technologies now and in the future. The thesis also proposes a more ethical and comprehensive ontological model for AI systems. The model describes AI systems as complex figurations, considering their socio-material organisation, global economic-material becoming, and impact on the environment, social institutions, and the semiosphere. The dissertation argues that AI should be understood not just as an object or sociotechnical system, but as its entire product chain encompassing people and cultures, as well as the used resources and impact (both material-ecological and semiotic) on a planetary scale.

Recent science fiction has brought anthropomorphic robots from an imaginary far-future to contemporary spacetime. Employing semiotic concepts of semiosis, unpredictability and art as a modelling system, this study demonstrates how the artificial characters in four recent series have greater analogy with human behaviour than that of machines. Through Ricoeur’s notion of identity, this research frames the films’ narratives as typical literary and thought experiments with human identity. However, the familiar sociotopes and technoscientific details included in the narratives concerning data, privacy and human–machine interaction blur the boundary between the human and the machine in both fictional and real-world discourse. Additionally, utilising Haynes’ scientist stereotypes, the research puts the robot makers into focus, revealing their secret agendas and hidden agency behind the artificial creatures.

The interpretation of many texts in the everyday world is concerned with their truth value in relation to the reality around us. The recent publication experiments with computer-generated texts have shown that the distinction between true and false, or reality and fiction, is not always clear from the text itself. Essentially, in today’s media space, one may encounter texts, videos or images that deceive the reader by displaying nonsensical content or nonexistent events, while nevertheless appearing as genuine human-produced messages. This article outlines certain problems with artificial intelligence (AI)-generated content, and frames the issue as a problem of recognising its proper referential reality. Examples include generative texts, deepfakes and their functioning in contemporary culture. The article makes use of the concepts of mimicry and nonsense to reveal the elements and counterparts in the communicative processes involving generated media.

The use of AI-generated videos centered on the face raises various concerns among professionals and audiences due to the difficulty of providing coherent descriptive tools of their cultural significance. At the same time, the focus of artists and their audiences shifts from the art as a text to the collaboration process between artificial intelligence (AI) and the involved social actors. This raises significant concerns between policymakers and other social actors looking for guidelines for the appropriate use of AI as a tool, collaborator or substitute for creative workers, which can have immediate and long-term impacts on society and culture. Semiotics of culture provides descriptive tools for understanding and evaluating artistic texts and their role in semiotic space, the semiosphere. This article addresses how Lotman’s theory can contribute to the methodology for analyzing AI-generated texts as dynamic models. The theoretical framework developed by Lotman in his research on artistic text, dynamic systems and culture can be applied to the studies of current shifts related to AI-generated arts. This paper looks at the reception of AI-generated videos focused on face representations. In doing so, it analyses the dynamic processes in the creation process of AI-generated videos through their reception in related texts. The findings of this article highlight how Lotman’s theoretical framework can contribute to the methodology to analyze the cultural dynamics evoked by AI-generated artistic texts.