Ordnance Survey: Navigating the Role of AI and Ethical Considerations in Geospatial Technology

As we step into a new year filled with promise and possibilities, the landscape of technology, particularly artificial intelligence (AI) and machine learning (ML), is on the cusp of significant transformation. In this article, Manish Jethwa, CTO at Ordnance Survey (OS), shares his insights on what we can expect from these advancements and their implications for the geospatial sector.

Breaking Down Barriers with AI

Looking ahead, Jethwa anticipates continued significant progress in AI and machine learning, particularly with the push towards Gen AI. He explains that the integration of large language models (LLMs) with more sophisticated agents will not only perform complex tasks on behalf of users but also further reduce barriers to interaction. This shift, especially in the geospatial field, means that translating natural language into precise data queries will become more seamless, ultimately making geospatial datasets more accessible, mainstream, and user-friendly.

Benefits of AI Integration

The integration of AI and machine learning has several benefits for the geospatial sector:

• Reduced barriers to interaction: AI can perform complex tasks on behalf of users, reducing the need for manual intervention.
• Increased accessibility: AI-powered tools can make geospatial datasets more accessible and user-friendly.
• Improved efficiency: AI can automate routine tasks, freeing up time for more strategic activities.

Challenges Ahead

While AI has the potential to revolutionize the geospatial sector, there are several challenges that need to be addressed:

• Technical complexity: AI requires significant technical expertise, which can be a barrier to adoption.
• Data quality: AI is only as good as the data it’s trained on. Poor-quality data can lead to inaccurate results.
• Bias and ethics: AI systems can perpetuate biases if not designed carefully.

Training for Complex Tasks

Beyond LLMs, Jethwa is optimistic about progress in the broader category of machine learning, driven by greater access to graphics processing units for training. He explains:

"At Ordnance Survey (OS), we’ll leverage this capability to train models for specific, complex tasks such as automatic feature extraction from imagery."

Future Developments

Some potential future developments in AI and geospatial technology include:

• Increased use of cloud-based platforms: Cloud-based platforms can provide greater flexibility and scalability for AI-powered tools.
• Improved data quality: Advances in data management and quality control can help ensure that AI systems are trained on high-quality data.
• Greater emphasis on ethics: As AI becomes more pervasive, there will be a growing need for ethical considerations in its development.

The Ethical Frontier

The rapid evolution of AI brings with it an urgent need for ethical considerations. Jethwa explains:

"I would like to see a greater emphasis on ethical AI and responsible technology development," including creating AI systems that are "transparent, fair, and unbiased" while also considering their environmental and societal impact.

OS’s Responsible AI Charter

Ordnance Survey has developed a Responsible AI Charter that guides their approach to integrating new techniques safely. The charter emphasizes the importance of:

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