SANTIAGO, Chile, CMC—The 24th meeting of the Executive Committee of the Statistical Conference of the Americas of the Economic Commission for Latin America and the Caribbean (ECLAC) is underway here. Delegates are discussing the progress made in using artificial intelligence in official statistics.
The meeting brought together representatives of regional and national statistics offices, regional and international organizations, United Nations agencies, funds, and programs, among other stakeholders.
“Statistics are one of our best assets for navigating an extremely complex scenario. We will not be able to achieve more productive, inclusive, and sustainable development if we do not have data to know where we are and how we can get to where we want to go,” said ECLAC’s Executive Secretary, José Manuel Salazar-Xirinachs.
He said that the region and the wider world are currently facing a critical situation that combines structural elements. These elements are summarized in the three development traps that ECLAC has been flagging: a trap of low capacity for growth, one of high inequality, low social mobility, and weak social cohesion, and a third trap of low institutional capacities and weak governance.
He said these structural traps are compounded by emerging challenges, such as the climate crisis and the fast-paced digital revolution, as well as geopolitical elements that exacerbate the atmosphere of uncertainty and volatility in which the governments of our region must design and implement public policies.
“In this complex scenario, reliable evidence is indispensable. We need timely, comparable, and transparent data produced with rigor and high ethical standards. That is the only way we can formulate effective policies that would truly transform the reality of our people.
“That is something ECLAC never forgets: at the center of our work, behind our models and projections, behind our studies and statistics, there are concrete people whose lives we are trying to improve,” Salazar-Xirinachs said.
The General Director of the National Office of Statistics of the Dominican Republic, Miosotis Rivas, who also serves as Chair of the Executive Committee of SCA-ECLAC, said that official statistics not only measure change but should also lead it.
She added that today, more than ever, the region’s countries have the opportunity to be the protagonists of transformation and to demonstrate that the future is not to be awaited but instead built.
The Director of the United Nations Statistics Division, Stefan Schweinfest, spoke of the urgency of having a robust statistical and global information system and praised the work of the Statistical Conference of the Americas for its valuable contribution to the sustainable development of Latin American and Caribbean countries.
In the framework of the meeting, a special session was held on the use of artificial intelligence in official statistics. This session sought to facilitate an active exchange between the participating countries regarding effective strategies and practical recommendations that can strengthen regional cooperation and maximize the benefits of using AI in national statistical systems.
During this session, the delegates highlighted practical experiences in implementing artificial intelligence in national statistics offices and other statistical entities in Latin America and the Caribbean.
Furthermore, they presented and discussed specific cases that illustrate the successful use and difficulties encountered in the practical adoption of advanced technologies such as automatic learning, natural language processing, and predictive analytics in different statistical contexts.
The Statistical Conference of the Americas is a subsidiary body of ECLAC and is the main forum for discussing the development of statistics in the region.
Its main mandates include promoting the development and improvement of national statistics and their international comparability, as well as international, regional, and bilateral cooperation between national offices and international and regional agencies.
and then 