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Show and Tell: Scientific representation, algorithmically generated visualizations, and evidence across epistemic cultures

Periodic Reporting for period 2 - SHOW AND TELL (Show and Tell: Scientific representation, algorithmically generated visualizations, and evidence across epistemic cultures)

Periodo di rendicontazione: 2022-08-01 al 2024-01-31

Scientific representations like maps, brain scans, and botanical drawings are crucial to the practice of science and its dissemination, but we know little about the ways that visualizations are circulated within, understood by, and convince nonscientists. New kinds of imagery further complicate the picture: today, widely accessible technologies can create photorealistic algorithmically generated images. These new kinds of images have introduced distinctive challenges to our ability to trust the things we can see with our own eyes. How do scientists use new kinds of imagery to show that they know the things that they know? How do they use images to convince diverse others to accept the evidence they offer?

This project is a multisited ethnographic study of the study of new 3D and 4D digital methods as they move between academic, practitioner, and public contexts, with a special emphasis on movements between science and the law. Show & Tell uses this unique object of study to answer three interconnected research questions, each offering both empirical and theoretical leverage on issues of scientific representation and scientific communication:

How do scientific visualizations produce agreement across diverse epistemic cultures – what makes it possible for images to 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?

This project offers unique purchase on both basic- science theoretical issues and contemporary social problems. It uses a multisited ethnographic research design to allow for an inquiry into scientific representation as it is developed for, and moves across, distinct communities. Show & Tell’s emphasis on algorithmically generated images will offer important insights into the ways that we might continue to use visual evidence and enhance its power in an era of deceptive image technologies. With the opportunity to witness the birth of new forms of scientific visualization and their movement between restricted scientific fields and varied practitioner and public contexts, this project will provide insight both on basic theoretical questions – how we use new kinds of visualizations to know what we know, and how we use images to prove it to others – as well as critical and timely questions on the relationships between scientific communication and public understanding.
As planned, fieldwork is still in progress and iterative analysis is underway. The scope of our empirical interests have expanded in line with empirical findings and initial analyses, and our project’s main achievements so far are those associated with fieldwork. Our collective dataset – thousands of pages of fieldnotes, dozens of transcribed interviews, documentary and archival data – is the primary achievement of the first years of this project, and is necessary for the public-facing outputs that will be the focus of the project’s final years. The majority of the team is now in their last year of fieldwork, and will move into full-time writing by the end of this academic year.

Our team has also organized generative and collaborative opportunities for scholarly exchange, and we regularly present our work for large and small scholarly audiences as well as practitioners and varied publics. Our early conceptual and empirical work has led to three distinct analytical threads thus far: A first thread revolves around the identification and analyses of the social processes behind valuation and evaluation; a second has focused on surprise and breakdown and their role in technoscientific processes; and a third asks fundamental questions about the relationships between representation and reality in digitally-inflected evidence.
Show & Tell uses a unique object of study to investigate the ways that we use new kinds of imagery to show what we know, and how we go about the work of convincing others to know it themselves. The project takes a generative step beyond the scientific community to carefully trace new scientific representations’ reception and uses as evidence and proof in the law, allowing for a theoretical inquiry into the relationships between visualization for inquiry and communication as well as a nuanced empirical analysis of the ways that scientific representations are used and understood across epistemic cultures. Further, with attention to the relationships between image cultures and the ways that scientific visualizations draw on and manipulate visual literacies built on the affordances of photography and other traditions, the project aims to offer new insights on the relationships between formal qualities and evidentiary value in a new and digitally inflected landscape of images.

As planned, we have developed working papers, conference presentations, and materials for workshops, and several articles are now under review or accepted for publication. The project will produce primarily peer-reviewed scholarship: articles, chapters, a doctoral dissertation, and a monograph. In our work we will aim to 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.
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