Litteraturvidenskab: Forskningsemne: Forventningsæstetik

In this course, we will explore the implications of algorithmic technology and culture on the concept of aesthetics and its anticipative manifestations in the generation of cultural objects and narratives. We will delve into the research topic of “anticipative aesthetics,” tracing its philosophical roots to technocultural entanglements and practical implications.

Anticipation, a concept that refers to thinking and living towards the future, is a defining characteristic of our current era (Adams, Murphy, and Clarke 2009). The influence of data-driven algorithmic technologies on the cultural dynamics of anticipation has profound implications for aesthetic production. From the anticipatory logics embedded in the algorithms that drive aesthetic filters on Instagram to the predictive text suggestions in our everyday digital communications, we have recently observed how Large Language Models (LLMs) automate and amplify the generation of aesthetic materials such as text, images, and videos. This automation is based on algorithmic processes that incorporate anticipative logics and functionalities into aesthetic materials, objects, and infrastructures.

With the recent algorithmic conditions of aesthetic production and experience in mind, we can pursue a dual interpretation of aesthetics: as a theory of perception, but also as a theory rooted in rationality (Jacques Rancière; Yuk Hui; Keren Gorodeisky and Eric Marcus). Drawing from aesthetics as the philosophical study of the essence of art, we begin with philosophical explorations into time, perception, and experience (Henri Bergson; Martin Heidegger; Hannah Arendt; Elizabeth Grosz; Sandra Lee Bartky) before transitioning into technophilosophical perspectives on the impact of digital technology on the production of today’s (digital) aesthetic objects.

Through these readings—and by engaging with emerging research fields such as Critical AI, Critical Future Studies, Algorithmic Aesthetics, and Algorithmic Culture—we will develop a shared vocabulary around various concepts of anticipation while distinguishing their differences: prediction, foreseeing, expectation, contemplation, forecasting, imagination, and prospection. We aim to identify these variations within cultural practices involving algorithmic technology and learn about the algorithmic functionality behind aesthetics.

The course is structured through a combination of theoretical inquiry, practical exercises, and meta-reflexive exercises. A consistent objective is to develop effective learning strategies when working with Large Language Models. This includes critical considerations about the role of algorithms as co-creators in content generation, reflecting on the choices made during the use of algorithms in aesthetic production, and metacognitive reflections on the process of knowledge generation for each student’s individually written final paper—a key component of the assessment.