On emerging paradigm of teaching measurement science and technology in times of ubiquitous use of AI tools

TL;DR

This paper advocates modernizing measurement science and technology education by integrating AI tools, emphasizing mathematical modeling and ethics to meet technological and societal challenges in various measurement applications.

Contribution

It proposes a new paradigm for teaching MST that incorporates AI, mathematical modeling, and ethics, addressing emerging technological and societal needs.

Findings

AI integration enhances MST teaching methods.

Curricula should include mathematical modeling and ethics.

AI tools are essential for safe measurement applications.

Abstract

The ubiquitous use of the tools of artificial intelligence (AI) in techno-science, in higher education and in other existing and potential fields of measurement application generates new challenges for teaching measurement science and technology (MST). The aim of this article is to encourage its readers to modernize their approach to teaching MST in a way as to meet these challenges, in particular - to profit from new technological opportunities, and to respond to the needs of our civilization, identified within a humanistic reflection over its development. First, the state of the art in applications of AI in higher education is briefly characterized. Next, a methodology for using AI tools in MST, referring to the author's meta-model of measurement, is outlined. Finally, conclusions concerning an emerging paradigm of teaching MST are summarized. The most important of them are as follows. The challenges implied by the ubiquitous use of AI tools cannot be effectively faced without enhancing, in the corresponding curricula, of the contents related to mathematical modelling of material entities, on the one hand, and of the contents related to ethics of research and engineering, on the other. Knowledge and skills related to the art of mathematical modelling are indispensable for extensively profiting from the convergence of various technologies around IT tools, including AI tools. The knowledge and skills related to ethics of research and engineering are indispensable for developing safe applications of measurement in such domains as autonomous vehicles, social robots, biomedical engineering or automated manufacturing.