Show & Tell
Scientific representation, algorithmically generated visualizations, and evidence across epistemic cultures
How do scientists use new kinds of imagery to show what they know, and to convince diverse others to accept the evidence they offer? Images like brain scans and botanical illustrations are central to scientific practice. But today, accessible technologies can create lifelike algorithmically generated images – photo-like pictures made not with lenses but through the manipulation of digital data. These new kinds of images have introduced distinctive challenges to our ability to trust the things we can see with our own eyes.
Financed by the European Research Council (ERC Starting Grant, €1.5 million, 2021-2025)
Show & Tell is an in-depth ethnographic study of new digital methods for the documentation, analysis, and visualization of physical places with a focus on their movements between academic research, police and forensic work, and courtrooms. We will follow researchers and practitioners as they develop manipulable, immersive environments to document and analyze archaeological excavations and crime scenes alike. Show & Tell focuses on three interconnected research questions:
• How do scientific visualizations produce agreement across diverse epistemic cultures – what makes it possible for images be understood by and convince scientists from multiple disciplines as well as prosecutors and judges?
• How do old ways of seeing interact with new technologies when scientists use new kinds of imagery as evidence?
• How do specific formal and material qualities influence the credibility of new kinds of images as they move between science and the law?
Show & Tell uses a unique object of study to investigate the ways that scientists use new kinds of imagery to show what they know and how they go about the work of convincing others to know it themselves. The project will provide theoretical breakthroughs illuminating the processes that let us believe our eyes (or prompt us to question them) when we encounter new kinds of imagery, and will offer a new conceptual framework for understanding scientific visualizations as they move between epistemic cultures.