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    PublicationAccess status: Open Access ,
    Defining digitalities II
    (2023)
    Haigh, Thomas 
    ;
    Although the distinction between digital and analog was first made in the context of automatic computers, the concepts were quickly broadened to apply to media and communication systems of all kinds. This working paper continues work on both fronts by looking at the his- torical broadening of the concept of digitality to include non-numerical systems of representation such as those used to encode text and pic- tures. This conception underlies the ability of computers to deal with things other than numbers, but it has its roots in communications the- ory, most famously in the work of Claude Shannon. In parallel with our historical description of the emergence of non-numerical conceptions of digitality we broaden our analytical treatment of digitality to en- compass more historical technologies and reading practices: not only adding machines and punched cards, but also musical boxes, weaving systems, movable type, and even alphabets and hand gestures.
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      7  22
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    PublicationAccess status: Open Access ,
    Defining digitalities III
    (2023)
    Haigh, Thomas 
    ;
    In this working paper we explore an alternative thread in the early development of media and medium as concepts: the origins of the idea of the storage medium in digital computing practices and communities of the 1940s and 1950s. While such practices were obscure at the time, they laid the technological foundation for today’s range of digital media. We discuss digitality as a feature of the practices used to read and write symbols from a medium, not a physical property of the medium itself. We then move on to a discussion of the alphabet as itself digital, grounded in the work of Nelson Goodman. Engaging with the contributions of Matthew Kirschenbaum, we explore the limited interchangeability of representations between different encodings of the same symbols, connecting the purported immateriality of digitality to this actual fungibility of material representations.
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      2  22
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    Identifizieren: Theorie und Geschichte einer Medienpraktik
    Registrieren, Identifizieren und Klassifizieren sind Praktiken, die in digitalen Kulturen kaum mehr zu trennen sind. Anhand der Mediengeschichte des Passes und der Kreditkarte geht der folgende Text der Frage nach, wie immer neue infrastrukturelle Kaskaden des Identifizierens entstehen und welche öffentliche Brisanz den entsprechenden Datenverarbeitungen innewohnt. Beim Identifizieren handelt es sich um eine ko-operative Medien- und Datenpraktik, an der stets mehr als eine Person beteiligt ist. Sie involviert von Anfang an menschliche Körper samt deren semiotischen Ressourcen und koppelt diese mit bürokratischen Aufschreibesystemen. Auch die neuesten digitalen Prozeduren greifen bevorzugt auf Gesichter und Fingerabdrücke zu: Biometrie versucht, den für das Identifizieren konstitutiven Abstand zwischen Konten, Körpern und Personen aufzuheben.
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      9  13
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    PublicationAccess status: Open Access ,
    The Multiple Returns of Connectionism: Theory and History of Artificial Intelligence
    In light of the recent boom in artificial intelligence, what future and what new environments should research in media and cultural techniques focus on? This article returns to a fundamental question posed by Marcel Mauss regarding the constitution of techniques between specific and general purposes. First, it offers a brief description of the current state of machine learning and recent AI developments between specialization and universalization. Second, I propose a genealogy of artificial intelligence between nature and cultural techniques. It inquires into the historical recurrence of connectionist practices, algorithms, and styles of thinking and acting as a condition of current AI technologies. How could biological neurons become artificial neural networks that work as the infrastructural foundation of artificial intelligence? Third, what is at stake here are the notions of media and mediation themselves. Due to the naturalization and habitualization of connectionist AI, they are becoming statistically operationalized, data-intensive networks.
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      132  69