AI Relies on Quality Data

The quality of data used to train AI models significantly impacts the effectiveness of resulting policies and insights. Official statistics are vital for shaping public life through AI, but these statistics must be accurate and reliable to avoid flawed outcomes. AI can enhance the quality of official statistics by automating processes like data cleaning and correction. AI approaches can also assist in the analysis and comparison of data across diverse sources, helping to reduce errors and ensure accuracy.

However, challenges remain in ensuring data readiness for AI. Machine-readability and metadata availability are essential elements that determine whether data can be used by AI applications and whether AI can be used to improve data use and re-use. National statistical organisations (NSOs) should focus on improving metadata and open data practices to leverage AI effectively. This includes investing in tools, skills, and data management to ensure transparency, reliability, and compliance in their work. Generative AI offers unprecedented capabilities, but also brings in new challenges. Addressing these challenges is crucial for decision-makers and the public to obtain reliable information from NSOs.