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Ethics in Spatial Analysis

When: February 9, 2021

Where: Online

Info: https://aag-geoethics-series.secure-platform.com/a/solicitations/10/sessiongallery/206

Register: https://aag-geoethics-series.secure-platform.com/a/solicitations/10/home?field.webinarchoice=W1Goodchild

      

 As part of its annual workshop series, the Spatial Analysis Research Center (SPARC) at Arizona State University is presenting a webinar on Ethics in Spatial Analysis Analytics. This event will also be the inaugural webinar in a broader, multi-year initiative on ethics in geographic research being jointly organized by The American Association of Geographers, Esri, the University of California, Santa Barbara, and SPARC.

 
Join us, Tuesday February 9th 11am – 1:30pm Eastern Standard Time for an expert-led discussion of ethical challenges and opportunities at the frontier of geographic research. Featured speakers will include:
 
• Mia Bennett (University of Hong Kong) and Luis Alvarez Leon (Dartmouth College) who will discuss the ethical implications and property regimes of remote sensing
 
• Peter Rogerson (University at Buffalo) – who will present ethical paradoxes that arise when attempting to make decisions based on inferences informed by spatial statistical decision making
 
• Renee Sieber (McGill University) – who will discuss ethical implications of GeoAI and locational big data
 
• Jacqueline Vadjunec (Oklahoma State University) – who will discuss ethical dimensions of spatial analyses based on data generated during citizen science projects, an ongoing need for mixed methods research, and implications of both for reproducibility
 
An interactive panel discussion hosted by Peter Kedron, Amy Frazier, and Michael Goodchild will follow the remarks of the speakers. We will also introduce a series of follow-up activities, preview forthcoming lectures, and provide further information on how to engage with the ongoing AAG initiative on Ethics in Geographic Research. The event takes place on February 9, 2021 from 11:00 AM - 1:30 PM Eastern Time.