SPRINT ON
Artificial Intelligence and Data Science
for Economic Statistics


WEBINAR 1 - 7 Nov 2024
WEBINAR 2 - 12 Dec 2024
SYMPOSIUM - 20 - 22 Jan 2025 - Dubai, United Arab Emirates

WEBINAR 1 7 Nov 2024 Download report

This AI and Data Science Sprint for Economic Statistics plays an important role in the ongoing efforts of the statistical community to integrate advanced data science techniques within the framework of national and international statistical systems. By highlighting successful use cases and discussing the strategic integration of new technologies, the sprint will help in shaping the future of economic statistics production. This Sprint will also be an important step in the further development of the Data Science Leadership Network playbook and seeks to empower NSOs with cutting-edge tools and methodologies for statistical production.

The sprint has four main objectives: (1) Present a series of impactful AI and data science projects in statistical production utilizing reproducible analytical pipelines; (2) Present AI and data science projects for the compilation of economic indicators to inform economic policies; (3) Present the possible use of generative AI technologies for the dissemination and interpretation of statistics; and (4) Address strategic and cross-cutting issues.

Recording of Main Session (incl Session 3)

Recording of Parallel Session 4

07:50 Session 3 - Room 1 Watch Recording

AI and Data Science initiatives in statistical production
Moderator: Bertrand Loison, Director, Data Science Competence Center, FSO Switzerland

  • Reproducible Analytical Pipelines (RAP) strategy and implementation at ONS - Martin Ralphs, Head of Analysis Standards and Pipelines, ONS, UK Presentation
  • RAPs for the Swiss Federal Pension Fund - Christopher Sulkowski, Data Scientist, DSCC, FSO, Switzerland Presentation
  • 10 minutes break
  • RAPs example - PortWatch and UN Global Platform - Mario Saraiva and Alessandra Sozzi, IMF Presentation
  • Utilization of AIS Data for Transportation Statistics and Greenhouse Gas Emission - Setia Pramana, BPS Indonesia Presentation
  • Wrap up

07:50 Session 4 - Room 2 Watch Recording

AI and Data Science for the compilation of economic indicators to inform policies
Moderator: Marco Marini, Division Chief, Data Governance and Services, IMF

  • Earth Observations and ML for estimating agricultural activity - Abel Coronado Iruegas, Deputy Director of Research in Data Science, INEGI, Mexico Presentation
  • AI/ML for estimating firm-level supply chain network - Gert Buiten, Statistics Netherlands Presentation
  • Using Ortho-imagery and Neural Networks to detect the location of solar panels - Nina Hofer, Statistics Austria Presentation
  • 10 minutes break
  • AI/ML for estimating economic indicators - Hadi Susanto, BPS Indonesia Presentation
  • Shedding light on Economic Growth: GDP Nowcasting with Satellite Data - Iyke Maduako, IMF Presentation
  • Wrap up