
This article argues that criticism’s aversion to obviousness is rooted in its construction of the particularly skilled author as the possessor of an informal, extralegal kind of intellectual property over a distinctive and nonobvious idea, technique, or style rather than simply over a specific text. This property form is distinct from the rights of authorship found in copyright law and more akin to the logic of patent law, with its formalized nonobviousness requirement that assesses whether a certain idea, technique, or method is unique enough to be protectable as private property. I begin with a new reading of Robert Hooke’s writings, arguing that Hooke coined a new usage of obvious in order to both assert his principled right to a disputed patent as well as authorship over his valuable, tacit knowledge and articulations of scientific method. My reading shows that invocations of obviousness structure attempts to explicate and own one’s tacit knowledge, particularly the special skill of noticing things that others overlook. I then apply these insights in a new reading of Northrop Frye’s Anatomy of Criticism, arguing that judgments of obviousness are foundational to criticism because criticism both assesses distinctiveness by a test of obviousness and must invoke obviousness to articulate its tacit knowledge. My article questions recent thinking in literary criticism that equates obviousness with manifestness, instead revealing obviousness to be a complex structure underlying critical judgments about value, skill, and intellectual property.
Media scholars traditionally understand computation as a process of sorting the world into a few reductive categories, such as a grid of potential values for race and gender. But in the last seven years, large language models have gone in another direction: they now assemble petabytes of unsorted data without categorizing them first. This essay provides a genealogical overview of this approach, which creates what is known to mathematicians as the multiset or bag. I argue that the creation of multisets or bags derives from early modern techniques for gathering and summarizing the singularities and oddities of the world (particularly people) into a single representation. By focusing on the period between 1600–1665 and on still-life paintings that produce a statistical sense of summary out of botanical specimens and ethnographic recordings, I explore how the disordered, jumbled dataset emerges as the verso to orderly grids and Linnaean taxonomies. Because multisets and bags have historically been constructed out of alterity—out of automata, indigenous bodies, and Asian languages—they also indicate a different way of understanding the operations of race inside a large language model.
his essay tells the story of how nineteenth-century artificial memory systems came to be understood as autonomous machines that produced random-access memory. It examines how the 1730 creation of a new hexametric mnemonic system sparked a philosophical crisis by popularizing an alternative means of remembering via nonsense associations. Tracing this discourse reveals that Samuel Taylor Coleridge’s Biographia Literaria (1817) offers the first modern conceptualization of external mechanical random-access memory (RAM). Coleridge represents mnemonics as destroying the innate memory and replacing it with a separate machine, the artificial memory system. He describes mnemonics as enacting a form of recall that 1950s computer scientists would later term random access. By the 1840s, Victorian proponents and critics universally understood mnemonics as memory machines: autonomous recall technologies that were embedded in the mind but not of it. Freed from the constraints of logical relations between ideas, artificial memory systems created a new form of recall that was instantaneous, virtually infinite, and readily purchasable. Yet surprisingly, this new mnemonic technology was lauded by radical working-class liberation movements—Chartism in Britain and abolitionism in the United States. For them, artificial memory systems offered a revolutionary means of democratizing knowledge to produce greater socioeconomic and racial equity. This new picture positions mnemonics as an exciting new literary dimension in the expanded histories of computing(s). Recovering the historical existence of more democratic alignments with emerging artificial technologies also provides valuable strategies for today’s humanists as they formulate critical responses to the contemporary AI boom.
This essay explores the place of apparently nonsexual perversions and develops an analytic that allows for a textual repositioning of sex in the theory of Leo Bersani.
The essay confronts the work of Greek modernist painter Yannis Tsarouchis, claiming as a new model for understanding modernism his work’s intentional anachronisms. Central to the essay’s claims is Tsarouchis’s dialogue with surrealism in the 1930s, the larger platform for a rethinking of modernism in terms of the anachronic itself.
The dialogue between Vilém Flusser and Harun Farocki was captured in a thirteen-minute video that featured the two men sitting in a café on Leipziger Straße in Berlin, analyzing the cover layout of Bild Zeitung. However, Flusser and Farocki’s conversation extended far beyond this single video. Flusser is best known for his technical image trilogy: Towards a Philosophy of Photography (1983), Into the Universe of Technical Images (1985), and Does Writing Have a Future? (1987), and Farocki often cited Flusser in his writings. Both were interested in the 1989 Romanian revolution, which was largely televised (Flusser lectured and wrote on the subject and Farocki and Andrei Ujicǎ made the film Videograms of a Revolution [1992]). Later Farocki works are infused with Flusser’s ideas. Both shared the conviction that philosophy can be done in images, as well as text, and that technical images shape rather than merely document or represent political and cultural events, an idea that has become increasingly accepted in the age of social media, the internet, algorithms, cryptocurrency, and artificial intelligence.