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Data Quality Top Priority for Adopting Pragmatic Approach to AI

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Artificial intelligence (AI) is an opportunity to improve efficiency but data quality must be maintained to ensure accuracy is not compromised, say national providers of geospatial information.

More than half of the participants in the third joint EuroGeographics โ€“ EuroSDR workshop said they were testing AI, or confirmed its small-scale or moderate use within their organizations.

They also identified machine learning as the most relevant technology for their activities and cited security and accuracy as key issues that AI policy frameworks should consider.

โ€œThere is no doubt that AI is a technological game changer; the majority of delegates agreed that it is inevitable that they would be using it extensively in the near future,โ€ said Carol Agius, Head of Representation and Stakeholder Engagement, EuroGeographics which represents Europeโ€™s National Mapping, Cadastral and Land Registry Authorities (NMCAs).

โ€œAs trusted providers of official geospatial information, the challenge for our members is to balance efficiency benefits with measures to ensure the continued accuracy, high quality, and reliability of their data. Our discussions show that they are taking a prudent and pragmatic approach to using AI rather than falling for the hype.โ€

Joep Crompvoets, Secretary General of EuroSDR added, โ€œThe workshopโ€™s discussions show that AI is not a silver bullet but a complementary tool for the traditional methods used by NMCAs. To gain maximum benefit, they should invest in and use the technology by adopting a culture of GeoAI throughout their organization.โ€

The 2023 workshop was organised by not-for-profit organisations, EuroGeographics, and EuroSDR, the European Spatial Data Research network that links NMCAs with Research Institutes and Universities.

It continued the conversation of AI within the context of NMCAs from events held in 2021 and 2022. It brought together producers, users, academia, and software suppliers to debate spatial data quality, with a particular focus on the impact of new technologies.