Hochschule für Gestaltung und Kunst Basel FHNW
Dauerhafte URI für den Bereichhttps://irf.fhnw.ch/handle/11654/11
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Publikation From the ashes. Towards an honest museum(Hochschule für Gestaltung und Kunst Basel FHNW, 2023) Sipos, Hanna Júlia; Wenger, Andreas; Scheel, Ruth; Ehleiter, Martina"From the Ashes" is an interactive AI driven installation that explores the concept of generating audience interaction through an open, speculative knowledge generation process, targeting missing information regarding a collection of artworks. The pieces in question are from the Modern Artworks from Germany, that were destroyed following the “Entartete Kunst” (Degenerate Art) exhibition series. In my work, I am using prompt-to-image AI generating models to create speculative recreations of these lost artworks, based on the information they left behind – such as artist, title, medium and style. “In my work, I am using prompt-to-image AI generating models to create speculative recreations of the lost artworks, based on the information they left behind – such as artist, title, medium and style. To achieve this, I have created a digital database from the remaining information about these pieces and wrote a code that generates a prompt that can be understood by an AI program.”11 - Studentische ArbeitPublikation Marks insist on being words. Asemic writing and the struggles of AI in generating meaningful text(Hochschule für Gestaltung und Kunst Basel FHNW, 2023) Galika, Kornilia; Ahn, Jinsu; Käser, Susanne; Savic, SelenaThere is more work in interpreting interpretations than in interpreting things; and more books about books than on any other subject; we do nothing but write glosses on one another. — Montaigne, Essais, quoted in Michel Foucault’s “The Order of Things” Asemic writing is a wordless open semantic form of writing that does not attempt to communicate any message other than its own nature as writing and doesn’t necessarily convey information. The open nature of asemic works allow for meaning to occur across linguistic understanding, and multiple interpretations can arise which can be polysemantic or have zero meaning. Any writing, legible or not, carries with it the expectation that it is intended to be read and can become a fascinating desire for the reader to elucidate a cryptic text. Recently, advancements in artificial intelligence have led to the development of models capable of generating text that resembles human language. However, these models often struggle in generating meaningful text and this often results in gibberish or distorted text that is difficult to read or completely illegible. While we expect to see a series of recognizable shapes representing vocal sounds when we look at text, AI does not possess this understanding. Instead, it perceives text as a series of shapes, angles, and curves, attempting to replicate patterns without comprehending the symbolic meaning underlying those shapes. AI relies solely on statistical information for text generation, thus both asemic writing and AI image generators inherently lack semantic content. "Marks Insist on Being Words" in an attempt to explore and provide information on how the absence of semantic content in asemic writing compares to the struggles of AI generators in generating coherent and meaningful text. My intention is to use this technological limitation in order to explore the asemic writing from a new perspective and by doing so, I aim to challenge visual communication’s principles and suggest new ways of reading and looking. Drawing inspiration from fictional and fantasy worlds, as well as alienese languages like Kryptonian (associated with Superman’s home planet) or “chicken-scratch” speech used by Woodstock in the “Peanuts” comic strips, this project aims to create an encyclopedia that encourages imagination and focuses on the visual process rather than linguistic meaning. The book serves as a metalanguage, prompting readers to activate their imagination and conceptualize what they see. It liberates readers from the linear constraints of writing systems, immersing them in a non-sequential approach to engaging with writing. By deconstructing language, the encyclopedia offers fresh perspectives while teasing the possibility of legibility and simultaneously denying it. Asemic writing draws attention to the visual qualities inherent in written form and surpasses linguistic meaning, urging readers to appreciate aesthetic and visual elements beyond conventional languages. This encyclopedia is designed precisely for this purpose, inviting readers to imagine its potential meanings.11 - Studentische ArbeitPublikation Making Arguments with Data: Resisting Appropriation and Assumption of Access / Reason in Machine Learning Training Processes(Weizenbaum Institute for the Networked Society, 30.10.2023) Savic, Selena; Martins, Yann PatrickThis article presents an approach to practicing ethics when working with large datasets and designing data representations. Inspired by feminist critique of technoscience and recent problematizations of digital literacy, we argue that machine learning models can be navigated in a multi-narrative manner when access to training data is well articulated and understood. We programmed and used web-based interfaces to sort, organize, and explore a community-run digital archive of radio signals. An additional perspective on the question of working with datasets is offered from the experience of teaching image synthesis with freely accessible online tools. We hold that the main challenge to social transformations related to digital technologies comes from lingering forms of colonialism and extractive relationships that easily move in and out of the digital domain. To counter both the unfounded narratives of techno-optimismand the universalizing critique of technology, we discuss an approachto data and networks that enables a situated critique of datafication and correlationism from within.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Making Arguments with Data(Weizenbaum Institute for the Networked Society - The German Internet Institute, 02/2023) Savic, Selena; Martins, Yann Patrick; Herlo. Bianca; Irrgang, DanielWhether we are discussing measures in order to "flatten the curve" in a pandemic or what to wear given the most recent weather forecast, we base arguments on patterns observed in data. This article presents an approach to practicing ethics when working with large datasets and designing data representations. We programmed and used web-based interfaces to sort, organize, and explore a community-run archive of radio signals. Inspired by feminist critique of technoscience and recent problematizations of digital literacy, we argue that one can navigate machine learning models in a multi-narrative manner. We hold that the main challenge to sovereignty comes from lingering forms of colonialism and extractive relationships that easily move in and out of the digital domain. Countering both narratives of techno-optimism and the universalizing critique of technology, we discuss an approach to data and networks that enables a situated critique of datafication and correlationism from within.04B - Beitrag KonferenzschriftPublikation Donkey Kong's Legacy. About Microprocessors as Model Organisms and the Behavioral Politics of Video Games in AI(Universität Bern, 2021) Bruder, JohannesThe article discusses forms of contamination between human and artificial intelligence in computational neuroscience and machine learning research. I begin with a deep dive into an experiment with the legacy microprocessor MOS 6502, conducted by two engineers working in computational neuroscience, to explain why and how machine learning algorithms are increasingly employed to simulate human cognition and behavior. Through the strategic use of the microprocessor as “model organism” and references to biological and psychological lab research, the authors draw attention to speculative research in machine learning, where arcade video games designed in the 1980s provide test beds for artificial intelligences under development. I elaborate on the politics of these test beds and suggest alternative avenues for machine learning research to avoid that artificial intelligence merely reproduces settler-colonialist politics in silico.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Distracted Attention: Mindful Algorithms and the Algorithms of Mindfulness(05.09.2019) Bruder, Johannes06 - PräsentationPublikation Donkey Kong is not a circuit. A psychogram of contemporary neural media(16.03.2019) Bruder, Johannes06 - PräsentationPublikation The Cognitive Agent(17.02.2021) Bruder, JohannesZooming in on the design of machine learning algorithms, he discusses characteristics of the post-anthropocentric figure that is “the cognitive agent” and elaborates on leakages and cross-contaminations between North American social science, psychology and computing.06 - PräsentationPublikation The Algorithms of Mindfulness(SAGE, 22.06.2021) Bruder, JohannesThis paper analyzes notions and models of optimized cognition emerging at the intersections of psychology, neuroscience, and computing. What I somewhat polemically call the algorithms of mindfulness describes an ideal that determines algorithmic techniques of the self, geared at emotional resilience and creative cognition. A reframing of rest, exemplified in corporate mindfulness programs and the design of experimental artificial neural networks sits at the heart of this process. Mindfulness trainings provide cues as to this reframing, for they detail each in their own way how intermittent periods of rest are to be recruited to augment our cognitive capacities and combat the effects of stress and information overload. They typically rely on and co-opt neuroscience knowledge about what the brains of North Americans and Europeans do when we rest. Current designs for artificial neural networks draw on the same neuroscience research and incorporate coarse principles of cognition in brains to make machine learning systems more resilient and creative. These algorithmic techniques are primarily conceived to prevent psychopathologies where stress is considered the driving force of success. Against this backdrop, I ask how machine learning systems could be employed to unsettle the concept of pathological cognition itself.01A - Beitrag in wissenschaftlicher Zeitschrift