Denis Chivanov,
Institute of Radio and Information Systems (IRIS), Vienna, Austria,
iris@media-publisher.eu
DOI: 10.36724/2664-066X-2024-10-3-17-23
SYNCHROINFO JOURNAL. Volume 10, Number 3 (2024). P. 17-23.
Abstract
Tools that use artificial intelligence (AI) technologies have been growing rapidly in recent years, including in the geospatial industry. Any kind of geospatial tool involves huge amounts of data, and the best insights are obtained by merging different data sources. Analyzing the data to find these important insights takes a significant amount of time. Powerful AI and machine learning algorithms can significantly reduce the time and amount of manual work. The task of processing data sets – sometimes including hundreds of thousands or millions of points – Is where AI can shine. This article looks at the types of AI models that are dominating the geospatial industry. This, of course, deviates from the general trends around generative AI, such as large language models and image generators, which is how AI is commonly used in the geospatial industry today. An analysis of the institutional models, functions and existing international normative frameworks of the UN system applicable to AI governance is presented to help understand how the system has adapted not only its strategy and programmatic implementation over the past few decades to the changing realities and geopolitics of the world, but also its experience as a trusted forum for consensus-building through normative and multilateral processes, as well as the development of tailored capacity development programs to support Member States in complex and challenging areas.
Keywords: communication technologies, artificial Intelligence, Geospatial Industry, machine learning
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