As artificial intelligence continues to advance, the geospatial sector stands to benefit significantly from its applications. Ordnance Survey (OS), the national mapping agency for Great Britain, is poised to incorporate AI and machine learning technologies into its operations. This strategic move is expected to enhance data accessibility and streamline complex geospatial tasks, positioning OS at the forefront of technological integration within the industry.
How Will AI Enhance Geospatial Data Accessibility?
“At Ordnance Survey (OS), we’ll leverage this capability to train models for specific, complex tasks such as automatic feature extraction from imagery,”
stated Manish Jethwa, CTO at OS. This advancement will allow users to execute precise data queries using natural language, making geospatial datasets more user-friendly and widely accessible.
What Ethical Standards Guide OS’s AI Implementation?
OS is committed to developing AI responsibly, as outlined in its Responsible AI Charter.
“Transparent, fair, and unbiased”
AI systems, alongside consideration of their environmental and societal impacts, are emphasized by Jethwa. This focus ensures that new technologies are integrated into OS’s workflows with ethical integrity.
How Is OS Addressing Workforce Development Amid AI Integration?
“Retraining and upskilling employees to prepare them for the impact of AI and digital transformation,”
stated Jethwa. This initiative is crucial to maintaining the “personality, creativity, and emotion” within the workplace. By equipping the workforce for digital transformation, OS aims to harmonize technological progress with human elements.
In previous implementations, AI in geospatial fields primarily focused on data analysis and visualization. The current strategies at OS expand to more interactive and automated processes, reflecting a broader industry trend towards enhancing user interaction and operational efficiency.
The integration of AI at Ordnance Survey underscores a comprehensive approach that merges advanced technologies with ethical considerations and workforce development. By focusing on specific tasks like automatic feature extraction and ensuring data validation, OS enhances data reliability and usability. These initiatives offer a model for other organizations aiming to adopt AI in geospatial technology while upholding ethical standards and operational integrity.
