Some enlightenment regarding the project to mechanise reason. The assembly line of machine learning: data, algorithm, model. The training dataset: the social origins of machine intelligence. The history of AI as the automation of perception. The learning algorithm: compressing the world into a statistical model. All models are wrong, but some are useful. World to vector: the society of classification and prediction bots. Faults of a statistical instrument: the undetection of the new. Adversarial intelligence vs. statistical intelligence: labour in the (...) age of AI. (shrink)

This article argues against the conflation of digital and computational that ails contemporary critical discourse. Searching for a common logic among the three modes of computing (namely analog, digital, and quantum), it ends up finding an answer in the individuating backbone that runs through histories of postal, civic, and technological addresses. Borrowing the concept of addressability from computer science and adapting it to explain procedures of identificatory mapping at large, the article theorizes addressability as a cultural technique that can be (...) traced back to the origins of the modern disciplinary state. In doing so, it not only posits addressability as one of the core operational logics for all computation and an alternative analytic to the digital but also suggests a longer arc of computation that considers the ubiquitous digitality as a mere subset of modern state apparatuses and their urban infrastructures. The article concludes by reflecting on this computational addressability and its relationship with ideological interpellation, proposing computation as a multiscalar assemblage of political techniken. (shrink)

Scholars in both digital humanities and media studies have noted an apparent disconnect between computation and the interpretive methods of the humanities. Alan Liu has argued that literary scholars employing digital methods encounter a “meaning problem” due to the difficulty of reconciling algorithmic methods with interpretive ones. Conversely, the media scholar Friedrich Kittler has questioned the adequacy of hermeneutics as a means of studying computers. This paper argues that that this disconnect results from a set of contingent decisions made in (...) both humanistic and mathematical disciplines in the first half of the nineteenth century that delineated, with implications that continue to resonate in the present day, which aspects of human activity would come to be formalized in algorithms and which would not. I begin with a discussion of Nicolas de Condorcet, who attempted, at the height of the 1789 revolution, to turn algebra into a universal language; his work, I argue, exemplifies the form of algorithmic thinking that existed before the Romantic turn. Next, I discuss William Wordsworth’s arguments about the relationship of poetry and science. While Wordsworth is sometimes viewed as a critic of science, I argue that his polemic is specifically targeted at highly politicized projects like Condorcet’s that sought to supplant existing modes of thought with scientific rationality. Finally, I demonstrate the importance of Romantic thought for George Boole, creator of the logic system that would eventually form the basis of digital electronics. The reason Boole was able to succeed where Condorcet had failed, I argue, was that Romantic notions of culture enabled him to reconcile a mechanical view of mathematical reasoning with an organic view of the development of meaning—a dichotomy that remains a key assumption of computer interfaces in the twenty-first century. (shrink)