Institute of Experimental Design and Media Cultures

Dauerhafte URI für die Sammlunghttps://irf.fhnw.ch/handle/11654/19

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  • Vorschaubild
    Publikation
    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 Patrick
    This 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 Zeitschrift
  • Vorschaubild
    Publikation
    Making Arguments with Data
    (Weizenbaum Institute for the Networked Society - The German Internet Institute, 02/2023) Savic, Selena; Martins, Yann Patrick; Herlo. Bianca; Irrgang, Daniel
    Whether 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 Konferenzschrift
  • Vorschaubild
    Publikation
    Donkey Kong's Legacy. About Microprocessors as Model Organisms and the Behavioral Politics of Video Games in AI
    (Universität Bern, 2021) Bruder, Johannes
    The 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 Zeitschrift
  • Publikation
    The Cognitive Agent
    (17.02.2021) Bruder, Johannes
    Zooming 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 - Präsentation
  • Vorschaubild
    Publikation
    The Algorithms of Mindfulness
    (SAGE, 22.06.2021) Bruder, Johannes
    This 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