LEVERAGING ARTIFICIAL INTELLIGENCE IN THE OPERATIONS OF NATIONAL STATISTICAL OFFICES IN ANGLOPHONE WEST AFRICA
Ghana Statistical Service (GSS)
• Gambia Bureau of Statistics, The Gambia • Liberia Institute of Statistics and Geo-Information Services (LISGIS), Liberia • Nigeria Bureau of Statistics, Nigeria • Statistics Sierra Leone, Sierra Leone • Amaris Institute of Statistics and Economic Research
Fundamental to the work of NSOs are human capacity, IT infrastructure, independence, rate of adaptation to evolutions, governance and regulation, and policy impacts of data and statistics. These fundamentals underscore the performance, relevance and sustainability of NSOs. This commitment aims to align the fundamentals outlined in the work of NSOs and the indispensable vertical and horizontal implications of AI. Specifically, the objectives are to;
· Profile the status of engagement with AI by NSOs in Anglophone West Africa sub-region,
· Map the fundamentals of the work of NSOs with the implications of AI, and
· Offer guidelines for developing country-specific roadmaps for integrating AI.
The on-going discourses on Artificial Intelligence (AI) within the data and statistics eco-system have focused on its implications on official statistics. Limited reflection has been accorded to the operations of national statistical systems and their preparedness in accommodating the indispensable influence of AI.
A desktop review of the response of NSOs to AI suggests that only a handful are exploring the scope of influence and how to incorporate AI in their statistical production processes and operations. For most NSOs in developing economies, the anecdotal evidence suggests that such discussions are either non-existent or nascent, with national-level AI regulation agendas only emerging.
KEY ACTIVITIES:
Key activities include webinar Series and Stakeholder Dialogue.
In collaboration with partners, the Ghana Statistical Service aims to organise Webinar series and stakeholder dialogue(s) on leveraging AI in NSOs’ operations.
This includes discussions exploring the potentials and pitfalls of leveraging AI in the operations of NSOs and a review of the current AI technologies available and applicable to the national statistical production processes.
The commitment considers supporting the development of a framework outlining the use of AI in the activities of NSOs while safeguarding public trust.
STRATEGIES:
1. Identify knowledge gaps of the subject within NSOs
2. Collaborative engagement and sharing of knowledge to help build partnerships and unlock the full potential of AI.
3. Develop a strategic roadmap for the onboarding of AI in technical and operational frameworks of NSOs
INTENDED OUTCOMES: The expected outcome is to support NSOs in drafting a roadmap for onboarding AI in their technical and operational frameworks. As AI becomes pivotal in our work, this guidance would ensure that NSOs are well-equipped to leverage AI effectively.
Continuous monitoring, establishing Key Performance Indicators (KPIs), and progress reviews will be implemented to track the progress of the commitment.
Activity1: Collaborative Engagements
Sub-Activities: Webinars
Monitoring Method: Review webinar report
KPIs/Metrics · Number of Webinars held
· Number of stakeholders participated
· Diversity of stakeholders participated
· Number of partnerships formed
Activity2: Knowledge Sharing
Sub-Activities: Workshops with NSOs, Technology Firms, and other stakeholders
Monitoring Method: Review event reports
KPIs/Metrics: · Number of case studies shared
· Potential and Risks of AI identified
· Number of Workshops held
· Number of AI tools relevant to NSOs identified
· Ethical considerations identified/best practices documented
Activity3: Support the development of a strategic roadmap
Sub-Activities: Conduct Stakeholder consultation to align roadmap to NSOs’ goals
Monitoring Method: Review of meeting minutes and reports
KPIs/Metrics: · Number of stakeholder consultations held
· Completion of roadmap