Short abstract

Generative AI models fine-tuned on Swedish Romantic fiction, the William Blake Archive, and Swedish medical periodicals generate “synthetic pasts.” We propose synthetic hermeneutics to examine how such machine co-produced histories reshape cultural patterns and historicity.

Long abstract

This presentation examines how generative AI models trained on historical corpora produce synthetic pasts that both reproduce and reconfigure cultural patterns.

Empirically, we work with multimodal datasets spanning Swedish Romantic fiction (Claes Livijn), the William Blake Archive, and postwar Swedish medical periodicals (SweMPer). These datasets are used to fine-tune state-of-the-art language and image diffusion models, generating non-existent historical texts and images such as completed nineteenth-century novels, Blakean poems and plates, synthetic medical case reports, and era-specific medical advertisements.

Treating these outputs as a form of synthetic data, we analyze them through posthumanist media theory, media archaeology, and Hayden White’s notion of the practical past. This allows us to explore how AI-generated materials function as epistemic probes into latent temporalities, genre conventions, and biases sedimented in large-scale cultural datasets. We argue that, in this context, synthetic data do not merely “fix” problems of access or bias. Rather, they enact the very question of a politics of representation—a question that cannot be adequately addressed without first understanding how technical systems co-produce historical knowledge.

By foregrounding the ways in which these systems participate in constructing historical knowledge, we raise new questions about authorship, authenticity, and the status of machine-generated historiography in both scholarly and artistic practice. We propose the notion of synthetic hermeneutics to describe how synthetic pasts operate as epistemological tools, using machine-generated history to probe, contest, and reconfigure what is permitted to count as historical knowledge.