A New Science for Future

Abstract

Building on concepts from Science & Technology Studies, Simon David Hirsbrunner investigates practices and infrastructures of computer modeling and science communication in climate impact research. The book characterizes how scientists calculate future climate risks in computer models and scenarios, but also how they circulate their insights and make them accessible and comprehensible to others. By discussing elements such as infrastructures, visualizations, models, software and data, the chapters show how computational modeling practices are currently changing in light of digital transformations and expectations for an open science. A number of inventive research devices are proposed to capture both the fluidity and viscosity of contemporary digital technology.

From critical technical practice to reflexive data science

“…HCI and computer-supported cooperation work scholars have argued that digital cooperative work typically involves more fluid objects that do not only enable cooperation beyond boundaries of social worlds but also the negotiation of these boundaries (Bertelsen and Bødker, 2002;Lee, 2007). In the context of learning, we have also argued elsewhere (Hirsbrunner, 2021) that digital objects such as dynamic data visualizations can serve as anchoring devices enabling the discursive negotiation of complex matters of concern. Our own practice, then, showed that such objects can also be made productive for learning and reflection in the context of AI research.…”

“…RDS employs a comprehensive network of (digital or analog) tools that enable discursive negotiations, the analysis of socio-technical (re-)positionings, and other ways of reflection. This may include anchoring devices (Hirsbrunner, 2021) for discursive negotiation of programming code such as Jupyter Notebooks, software versioning systems comparing different states of the technology, but also video-meeting software, (auto-)ethnographic notes and visual mapping tools. A promising direction for further research in an STS context would be to investigate whether we could actually speak of reflexivities in AI infrastructure or even of reflexive AI infrastructures.…”