Proposal Description

Statistical literacy has long been recognised as a foundational element for ensuring the quality of official statistics, supporting informed interpretation, transparent communication and public trust. The Invited Paper Session organised at the ISI World Statistics Congress 2025 highlighted how statistical literacy underpins key dimensions of quality, including relevance, accuracy, coherence, accessibility and integrity, reinforcing the idea that literacy and quality are intrinsically linked.
Since then, the rapid adoption of artificial intelligence (AI) tools in statistical production, analysis, interpretation and communication has introduced new opportunities, but also significant challenges. AI-assisted processes can enhance efficiency, timeliness and analytical capacity; however, they may also reduce transparency, obscure methodological choices and introduce new ethical risks, including bias, lack of explainability and diminished accountability. Moreover, the growing reliance on AI-generated outputs raises important questions regarding users’ capacity to critically assess statistical information, understand underlying assumptions and limitations, and maintain independent analytical judgement.
In this evolving landscape, statistical literacy becomes even more essential. It must extend beyond the ability to interpret statistical outputs to include the capacity to question, contextualise and critically assess results produced with the support of AI, as well as to understand their ethical implications. Preserving good statistical practice therefore requires not only technical rigour, but also a strong ethical framework guiding the production, communication and use of official statistics.
This Invited Paper Session aims to advance this discussion by examining the evolving relationship between statistical literacy, critical thinking, quality and ethics in an AI-mediated environment. Contributions will explore how core principles of good statistical practice can be maintained when AI tools are embedded in statistical workflows; how ethical considerations are being integrated into official statistical systems; which new competencies are required for statisticians, educators, decision-makers and citizens; and how communication and education strategies must adapt to safeguard understanding, integrity and trust.
By bringing together perspectives from official statistics, statistical literacy research, education, methodology and ethics, the session will foster a critical and forward-looking dialogue on how to harness the benefits of AI while preserving the human judgement, ethical responsibility and statistical understanding that underpin high-quality and trustworthy statistics.