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Carlos Reolon, representing Brazil and ABES, participates in the event 2024 ISO/IEC JTC 1/SC 42, an international plenary session focused on the technical standardization of Artificial Intelligence (AI) systems. Held from October 7 to 11 in France, the event brings together delegations from dozens of countries. A highlight on the agenda is the meeting of representatives of the delegations with UNESCO, scheduled for Thursday (10/10), which will address the environmental footprints of AI.

Organized in collaboration by the International Organization for Standardization (ISO) and the International Electrotechnical Commission, the 2024 ISO/IEC JTC 1/SC 42 plenary session seeks to develop international standards and technical reports for the growing field of AI. Reolon is also among the participants in Working Group 1, where he will discuss the addition of Generative AI concepts to the documents (ISO/IEC 22989) and the Framework for Artificial Intelligence Systems using Machine Learning (ISO/IEC 23053), among other items on the agenda.

“The importance of standardization includes the creation of a common terminology that ensures clear communication and informed decisions. The collection of requirements and best practices will drive the safe and efficient development of technology, while the standardization of algorithms will favor interoperability and large-scale use,” explains Reolon, who coordinated the work of translating international standards on AI into Portuguese, carried out by ABNT – Brazilian Association of Technical Standards.

With multiple stakeholders, including industry, academia, and policymakers, a global effort with dedicated AI experts is a key step to improving trustworthiness and its development. Standards are needed to enable the mass deployment and adoption of AI across a variety of sectors. As a foundation, it will be important to have a common terminology for use by all stakeholders, which will enable clear communication and sound decision-making. Gathering use cases, their requirements, and best practices for applying the technology will guide the development of the technology. “Like other transformational IT technologies, AI will be pervasive, and it is necessary to address trustworthiness issues from the outset. Finally, looking at the core of AI, standardizing algorithms and computational techniques will enable a higher level of adoption, use, and interoperability,” reiterates Reolon.

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