SMEs

The prEN AI Trustworthiness Framework Standard specifies trustworthiness requirements aligned with European culture and society. Whereas, the prEN AI System Risk Management standard enables to control risks not only on the individual and company level but also on the level of the society.

EN AI Trustworthiness Framework provides requirements for trustworthy AI systems that align with European stakeholders and regulation and European values. Enable the design and management of trustworthy AI systems that proactively respect European norms and values and fundamental rights.

My fellowship contributes to the following societal impact within the two standardisation projects:
Firstly, EN AI Trustworthiness Framework provides requirements for trustworthy AI systems that align with European stakeholders and regulation and European values. Enable the design and management of trustworthy AI systems that proactively respect European norms and values and fundamental rights. It also indicates the need for holistic risk management taking into account the risks to users and society. The requirements for logging, transparency, human oversight, accuracy and robustness account for managing the risks to affected users and society at large.
Secondly, The EN AI Risk Management standard enables us to control risks not only on the individual level but also on the level of the society (e.g., misinformation and disinformation risks, risks to democratic processes, …). The scope of the standard indicates that risks covered include both risks to health and safety and risks to fundamental rights which can arise from AI systems, with impact for individuals, organisations, market and society. The risk policy (section 5.1.2), the risk management plan (section 5.1.4), the risk evaluation (section 5.2.1.4) specify requirements on consultation with potentially affected stakeholders (or their proxies, including civil society organisations). The implementation and verification of risk control measures (section 5.2.2.2) and the evaluation of residual risk (section 5.2.3) refer to the test of necessity and proportionality in a democratic society, for risks pertaining to a potential interference with a fundamental right that permits qualifications.

The information chunks that convey conceptual information will conform to the “Intelligent information for use” metadata scheme, so that they provide meta-information about their semantics and hence become machine-readable and semantically interoperable with other information, e.g., in other submodels of the AAS. Which is, on the other hand, a prerequisite for their accessibility via differing sensory modalities in humans and therefore for barrier-free communication. This aspect has gained in importance with the imminent entry into force of the European Accessibility Act in June 2025.

Technical documentation increasingly turns into a set of fine-grained technical information assets featuring semantics via metadata on context of use parameters. These information assets hence become machine-readable and semantically interoperable with other information, e.g., AAS or DPP submodels. Which is, on the other hand, a prerequisite for their accessibility via differing sensory modalities in humans and therefore for barrier-free communication. This aspect has gained in importance with the imminent entry into force of the European Accessibility Act in June 2025.

Given the EU choice for the USB-C interface for charging and connection, it is now essential to make its use easy, successful and efficient, and reduce the risk of mismatch, unnecessary negative experiences and safety issues. A wide adoption will support the EU's initiative, and will increase the benefits beyond 'just' the Smartphone and Tablet domain, and enter the general rechargeable domain as the preferred standard.

This technical report (TR) will provide information and guidance on what is required to apply Circular-Economy Principles (CEP) to ICT equipment, services and usage. Applying Circular-Economy Principles is much more than being a bit Green, e.g. some reduction in the operational power consumption of network equipment.All parties involved, including the users, will have to make contributions to the realisation of CEP.Moreover, this TR is intended to be the basis for a set of standards on the implementation of Circular-Economy Principles to ICT equipment, services and usage.

The targeted impact includes:
increased effective economic life time of products
reduced resource consumption, including energy and scarse materials
better management of usage and recycling of materials, including scarse resources

The CWA will also benefit European society by supporting economic actors to understand how DPPs can support their activities by enabling new information generation mechanisms and sharing for a circular economy.

Cybersecurity is elementary for every digital asset and very important also for AI-Systems as a digital asset to be secure, safe, healthy and respecting fundamental rights.

The proposed activity aims to answer the official EU standardization request for the EU AI Act and specifically No. 8 Cybersecurity. Thrustworthy Metaverse solutions are based on trustworthy AI solutions. Trust and cybersecurity of AI and Metaverse can be ensured with well developed standards from cybersecurity and AI experts with business background. In case of the European Union harmonized standards as presumption of conformity to the EU Regulation are requested, in this case the request is for the AI Act and CRA as an essential fundament for a trustworthy and secure web 4.0 with virtual world and Metaverse with the specific EU focus on safety, fundamental rights, health and data protection.

The AI Act has the goal to avoid or mitigate negative impact on people and society regarding Fundamental Rights, Health and Safety. All harmonized standards for the AI Act support this goal and request of the AI Act including the standard for Cybersecurity specifications for AI Systems.

The AI Trustworthiness Framework will reinforce social trust in AI systems, by providing companies, consumers and ultimately citizens with a clear understanding of the fundamental requirements for trustworthy AI.

Trustworthiness fosters social acceptance. One of the outstanding barriers in the deployment of innovative technologies is social acceptance. This barrier damages both the economic benefits and the social benefits of designing innovative AI systems. The AI Trustworthiness Framework will reinforce social trust in AI systems, by providing companies, consumers and ultimately citizens with a clear understanding of the fundamental requirements for trustworthy AI.

By clarifying what makes AI trustworthy and aligning it with EU values, the project increases public trust and supports responsible innovation. It also helps make ethics a professional role, reinforcing societal oversight over AI technologies.