Artificial Intelligence

The 1st IEEE International Conference on Engineering Reliable Autonomous Systems (ERAS) was held on May 29-30, 2025 in the USA (Worcester, Massachusetts). ERAS offered a space for all stakeholders across autonomous system reliability to come together to discuss the key challenges and present progress made towards solving them. Along with the presentations of the original, selected, peer-reviewed papers, three keynote talks from Academia, Industry, and Government each, were invited. The conference also hosted one tutorial delivered by IBM, and one workshop organized by MIT, MA, USA.

Are you an expert in AI System accuracy and/or robustness? Then join CEN/CENELEC JTC 21, WG 4 Foundational and Societal Aspects or WG 3 Engineering Aspects!

The IETF draft titled "Artificial Intelligence (AI) for Network Operations" (https://datatracker.ietf.org/doc/draft-king-rokui-ainetops-usecases/) explores how AI and machine learning (ML) can be integrated into network operations—a concept referred to as AINetOps. The primary aim is to automate and optimize network management tasks, thereby improving efficiency, reliability, and scalability. This approach is relevant to both single-layer (IP or Optical) and multi-layer (IP/Optical) networks and is intended to tackle the growing complexity of modern network infrastructures.

I am proud to have contributed as a StandICT fellow call 4 to the working draft of the prEN AI Trustworthiness Framework standard, produced by CEN/CENELEC, JTC 21, WG 4 Societal and Foundational Aspects, Task Group 3 (WI=JT021008).

The working draft was circulated to experts of the national standardization bodies on November 12th 2024 (WD prEN AI trustworthiness framework (Doc. N 830)).

Please provide your comments as a national expert on the WD prENAI Trustworthiness Framework standard by December 10th 2024.

AI systems can have positive impacts but at the same time they can also bring risks to safety, health and fundamental rights.

The AI Act, art. 9 requires that high-risk AI Systems are subject to a risk management system.

AI systems can have positive impacts but at the same time they can also bring risks to safety, health and fundamental rights.

The AI Act, art. 9 requires that high-risk AI Systems are subject to a risk management system.

As AI is omnipresent and impacting everyones life, ensuring that AI systems are trustworthy is quintessential.

The AI Act is a European regulation on artificial intelligence (AI) promoting the uptake of human-centric and trustworthy artificial intelligence (AI), while ensuring a high level of protection of health, safety, fundamental rights. One way for companies to prove conformity with the AI Act is to meet the underlying harmonized standards.

The EN AI Trustworthiness Framework is one of these harmonized standards.

In today's rapidly evolving digital landscape, the integration of Artificial Intelligence (AI) into 5G and beyond networks has reached a critical juncture. While the potential of such integration offers great opportunities for innovation, efficiency, and service enhancement, it is not without its challenges. The primary obstacle lies in the complexity of the underlying network infrastructure, compounded by the lack of standardized guidelines for AI integration.

Progress in the harmonization of clinical information interoperability standards such as HL7 FHIR, ISO 13606, and ISO 13940 (as the ISO 24305 project does) should be joined with new AI standards such as the reference framework (next versions for ISO/IEC23053) and ISO/IEC AWI TR 18988 "Artificial intelligence - Application of AI technologies in health informatics," as well as for the security and effective use of standards for language models in the Electronic Health Record.

I've been involved in contributing to the development of standards (International, Regional & National) for over ten years.

Recently, its become evident that Artificial Intelligence (AI) could have an impact on the standards development process and procedures.  A list of issues, and where available, the resolution of those issues, would be a useful resource within all Standard Development Organisations (SDO).

Please find below an extract, derived from a paper written by AI ethicist Alessio Tartaro

Recall and withdrawal of AI systems

According to the AI Standardization Request from the European Commission to CEN/CENELEC, European standards or standardisation deliverables shall provide suitable organisational and technical solutions to ensure that AI systems are resilient against attempts to alter their use, behaviour, or performance or compromise their security properties, by malicious third parties, exploiting vulnerabilities of AI systems.