-----------------------------------------------------------------------
A discipline in its own right -----------------------------
Statistics is a branch of mathematics in that it draws on mathematical foundations such as probability theory, algebra, geometry and analysis to develop and validate methods for data analysis, inference and forecasting.
Yet it also has distinctive features not found in other branches of mathematics, including the collection, analysis and interpretation of data. This aspect has gained prominence with the need to address the interpretability problems posed by the complex methods used in artificial intelligence.
Statistics can therefore also be seen as a discipline in its own right. In the United States, for example, statistics laboratories are often separate from mathematics laboratories.
Today, statistics is being bolstered by the rise of artificial intelligence, which relies on statistical methods combined with large-scale computing architectures. Deep learning, which has enjoyed enormous practical success, is a typical example. But behind these successes, mathematics—and more specifically mathematical statistics—has a key role to play in understanding and validating the algorithms on which artificial intelligence relies.
The role of the SFdS ------------------
The French Statistical Society (SFdS) is an association officially recognized as serving the public interest and specializing in statistics. Its mission is to promote the use and understanding of statistics and foster methodological advances. It provides a key forum for all researchers, engineers, teachers and users of statistics. The SFdS's activities range from organizing specialized conferences and public evening debates open to all to publishing articles and books and providing training…
To advance their discipline, statisticians now work, more than ever, in a highly multidisciplinary environment. The technical aspects come to mind first, epitomized by computing in the broadest sense of the term. But because statistics has an extraordinary impact on human society via the large-scale deployment of artificial intelligence, it also requires much stronger connections with disciplines outside the technical sphere: the humanities and social sciences, and fields related to law or ethics… The SFdS is involved in all these debates. What is at stake is society's acceptance of the major changes now under way and still to come.
Towards less energy-hungry AI --------------------------------------
Like every branch of mathematics, statistics faces numerous theoretical, methodological and practical challenges. Artificial intelligence (AI) consumes vast amounts of energy because of the computing time and massive data storage it requires.
One major challenge—if we must single out just one—is to be kinder to our planet: can we store data more efficiently or store less of it, and train models more effectively or train them less often, while meeting society's needs as effectively as possible?