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Auflistung Künstliche Intelligenz 37(2-4) - Dezember 2023 nach Schlagwort "Explainable AI"
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- ZeitschriftenartikelCurrent topics and challenges in geoAI(KI - Künstliche Intelligenz: Vol. 37, No. 1, 2023) Richter, Kai-Florian; Scheider, SimonTaken literally, geoAI is the use of Artificial Intelligence methods and techniques in solving geo-spatial problems. Similar to AI more generally, geoAI has seen an influx of new (big) data sources and advanced machine learning techniques, but also a shift in the kind of problems under investigation. In this article, we highlight some of these changes and identify current topics and challenges in geoAI.
- ZeitschriftenartikelPragmatic GeoAI: Geographic Information as Externalized Practice(KI - Künstliche Intelligenz: Vol. 37, No. 1, 2023) Scheider, Simon; Richter, Kai-FlorianCurrent artificial intelligence (AI) approaches to handle geographic information (GI) reveal a fatal blindness for the information practices of exactly those sciences whose methodological agendas are taken over with earth-shattering speed. At the same time, there is an apparent inability to remove the human from the loop, despite repeated efforts. Even though there is no question that deep learning has a large potential, for example, for automating classification methods in remote sensing or geocoding of text, current approaches to GeoAI frequently fail to deal with the pragmatic basis of spatial information, including the various practices of data generation, conceptualization and use according to some purpose. We argue that this failure is a direct consequence of a predominance of structuralist ideas about information. Structuralism is inherently blind for purposes of any spatial representation, and therefore fails to account for the intelligence required to deal with geographic information. A pragmatic turn in GeoAI is required to overcome this problem.