Join assistant professor, Cindy Lin, for an IST Research Talk titled "Data and the Shifting Science of Seeing Fire in Indonesia".

About This Talk 

How can we comprehend rapidly shifting environments that exceed both longstanding patterns and historical trends? In Indonesia, environmental scientists and computer engineers in government and industry have turned to data science to broaden their range of emergency responses to fires they can no longer control. This talk draws on more than three years of ethnographic fieldwork with government and industry scientists to argue that environmental governance practices are shifting in the Global South. These changes bear important lessons for ongoing attempts to secure livable futures in the West. 

Prior technologies were designed to monitor and map large-scale shifts in fire patterns and land conditions from afar. However, data science in land mapping and fire prediction has opened new frames of reference for observing and preventing volatile fires. These shifts have shattered public and professional expectations of how environmental disasters can be handled. 

I will discuss recent attempts to integrate data science into fire and land mapping and prediction in Indonesia and demonstrate how competing methods to measure environmental change have altered the legitimacy of government science and engineering institutions, with universal claims to cartographic exactitude narrowly pitted against data science, rather than a broader understanding of emergent environmental risks. 

About the Speaker

Cindy Lin is an assistant professor in the social and organizational informatics area of the Penn State College of Information Sciences and Technology. 

Lin’s research draws on long-term fieldwork with environmental scientists, computer engineers, and cloud architects in government and industry to examine the politics of computational labor and data architectures for subterranean peatland fire control in Indonesia. 

She is currently working on a book that examines ground truth within the history of machine learning as a shifting political and scientific category. This book asks how ground truth and its claim to accuracy and evidentiality have shaped and been shaped by transnational exchanges of mapping, surveying, and computing expertise between Southeast Asia and the United States. 

As an information scholar, Lin’s work is located at the intersection of postcolonial and feminist science and technology studies, critical data studies, the history of computing, and environmental justice. Her work has been published in leading computing venues, including ACM CHI, DIS, and PD, and has been featured in Social Text and CoDesign. Her graduate studies and research have been funded by the National Science Foundation, Dow Sustainability Fellows Program, Rackham Graduate School, and the International Institute at the University of Michigan. 

Lin is the co-author of Technoprecarious, a multigraph written with Precarity Lab analyzing the role of digital technology in multiplying precarity. She was also the co-director of DoIIIT, an interactive design and making studio. 

Before joining Penn State, Lin was a postdoctoral fellow at the Cornell Atkinson Center for Sustainability, affiliated with the Department of Information Science. She was also a Digital Life Initiative visiting fellow at Cornell Tech. She holds a doctoral degree from The University of Michigan School of Information and a graduate certificate from The University of Michigan’s Science, Technology, and Society Program.