Vacancy: PhD on Interfaces of Intelligence: How Generative AI Reshapes Knowledge, Media, and Interpretation

Models (LLMs) and other generative AI systems integrate into everyday practices. Society is transitioning from an information retrieval paradigm, where search engines provide specific sources relevant to specific queries, to an interrogation and interpretation paradigm, in which knowledge is embedded within AI models through extensive, often opaque training processes and configurations. AI is also increasingly integrated into agentic systems – designed for specific contexts, goals, and degrees of autonomy – reconfiguring how knowledge is produced, validated, and operationalized across domains such as journalism, research, and education. This shift raises critical questions about authority, transparency, and the evolving role of human expertise in AI-mediated workflows.

To critically assess and learn from such shifts, our project takes a two-pronged approach: first, we examine how research methods are embedded within AI tools, adopting a digital methods perspective to explore their affordances and limitations. Second, we analyze how AI-driven software changes interfaces, influencing how users access and interact with knowledge. Both approaches aim to understand how knowledge is constructed, accessed, and made usable – both in digital research and everyday digital interactions.