The emergence of generative AI, such as machine-learning Large Language Models (LLMs), is transforming search by providing concise answers or summaries instead of ranked links as results. This change raises important questions about the complex information infrastructures that influence search results and how they can be comprehended and studied.
This interdisciplinary research delves into the ethics and politics of search ecosystems, investigating (open source) alternatives to dominant platforms and also sheds light on the environmental and social impacts of information/telecommunications networks and data centers.
By examining these knowledge infrastructures, this project aims to gain a better understanding of their influence on digital citizenship and their broader implications for society.
Situated at the interstices of web search, critical data/AI/infrastructure/surveillance studies and Feminist Science and Technology Studies, the project explores alternatives in search knowledge production through ethical and technical explorations. The project follows new protocols and alternatives, combining methods from the humanities and social sciences (interviews, (auto) ethnographies, data collection, document analysis) with artistic and design practices (screenshotting, data visualisations, dynamic webplatform) to reach diverse audiences (academic, student, layperson).
Results from the research will facilitate conversations around search, as well as offering solutions by designing, building and implementing public-facing infrastructures that enhance digital citizenship. Additionally, the project examines alternative knowledge infrastructures of search that are collaborative in nature, merging insights, expertise and experience from academics, artists, engineers, programmers, ethical experts and concerned citizens.
