Hochschule für Gestaltung und Kunst Basel FHNW
Dauerhafte URI für den Bereichhttps://irf.fhnw.ch/handle/11654/11
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Publikation KI als Medium und ›message‹ und die (Un-)Möglichkeit einer queeren Antwort(Transcript, 2022) Bruder, Johannes; Michael Klipphahn-Karge; Ann-Kathrin Koster; Sara Morais dos Santos BrussJohannes Bruder untersucht in seinem Beitrag die konstitutiven Ein- und Ausschlüsse von autistischer Subjektivität und Kognition im Kontext von künstlicher Intelligenz. Während autistische Kognition in Fantasien von zukünftiger KI als konstitutives Anderes fungiert, waren und sind autistische Individuen essenzieller Bestandteil der kognitiven Infrastruktur von real existierender KI - ob als Testobjekte, Coder, oder Data Worker. Diese Dynamiken von Ein- und Ausschluss sind nicht neu, sondern gesellschaftlich fest verankert; autistische Aktivist*innen haben dementsprechend Strategien entworfen, sich selektiven Ein- und Ausschlüssen performativ zu entziehen. Im Text versucht Johannes Bruder diese Strategien für eine Antwort auf die Medientheorien zeitgenössischer AI fruchtbar zu machen.04A - Beitrag SammelbandPublikation 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 Letter from the editors: Lost & Found(Continent, 2016) Bruder, Johannes; Gerloff, Felix; Allen, JamieThis issue was found in the lost conversations of continent.’s Jamie Allen and guest editors Johannes Bruder and Felix Gerloff. It is the crystallization of interests in the empirical, in notions of ‘evidence’, and the act of ‘returning’ something from a site of investigation. Developed through the Swiss National Science Foundation project Machine Love?[1], a project by researchers from the Institute of Experimental Design and Media Cultures at the Academy of Art and Design FHNW[2] (Claudia Mareis, Johannes Bruder and Felix Gerloff), these articles and artefacts stem in part from a workshop (All Eyes on Method in Basel on the 4th and 5th of June 2015) attended by contributing authors Sarah Benhaïm, Hannes Krämer, Luis-Manuel Garcia, Priska Gisler and Stefan Solleder. We also sought to expand the constituency of this continent. issue through a discussion of the role that media artefacts and material objects play in empirical research more generally. We have reached out to thinkers and doers who have developed ways of productively navigating the ambiguities of losing and finding, forgetting and remembering, capturing and deleting. Works by Geraldine Juarez, Mara Mills, Verena Paravel and Lucien Castaing-Taylor with a response by Nina Jäger and Bronwyn Lay, Natasha Schüll, and the Times of Waste research team further elaborate the thematic of ‘Lost & Found’ for this issue. We (re)present here attempts to (re)create experience, waving our flag of surrender at a world that is forever slipping through our fingers.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Why Is It So Hard To Describe Experience? Why Is It So Hard To Experience Description?(MIT Press, 2016) Allen, Jamie; Bruder, Johannes; Mareis, Claudia; Latour, BrunoThe Reset Modernity! exhibition was collaboratively designed and curated by a group consisting of people from the aIMe Research Team, the Critical Media Lab of the Academy of Art and Design FhnW in Basel, and the ZKM | Center for Art and Media Karlsruhe. Invited to contribute their thoughts on this process to this catalogue, Jamie Allen, Claudia Mareis, and Johannes Bruder of the Critical Media Lab have opted to trace and reflect on the far from equilibrium entanglements that emerge between the various modes of history and tradition, scholarly inscription and description, experimental design practices, and impossible scenographies in such processes. The authors describe the practice and thinking of the Critical Media Lab (Basel), dedicated to continuous questioning and critique that is “associated with more, not with less, with multiplication, not subtraction” (Latour, “Why Has Critique” 248), intertwining praxis-led art and design research with historical and theoretical reflection.04A - Beitrag SammelbandPublikation The Rewrite Collaborative Framework Browser Extension(15.02.2022) Bruder, Johannes; Sobecka, Karolina; Granzotto, Alberto; Frei, Fabian; Suess, Solveig; Kolb, LucieA browser extension, based on the open access framework hypothes.is, which allows for collective reading and annotation of complex texts (e.g. policy texts, legal texts, international treaties). The extension can be used for teaching & research, consensus-building and negotiation, reviewing or rewriting. Please consult the manuals before installing and using the extension.09 - SoftwarePublikation Optimal Brain Damage. Theorizing our Nervous Present(Culture Machine, 2021) Bruder, Johannes; Halpern, Orit01A - Beitrag in wissenschaftlicher ZeitschriftPublikation 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 ZeitschriftPublikation Enjoy the Creepy Naked Cybergirl(Continent, 2016) Bruder, Johannes; Benhaïm, Sarah01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Letter from the Editors(Continent, 2016) Bruder, Johannes; Allen, Jamie; Gerloff, Felix01A - Beitrag in wissenschaftlicher Zeitschrift