In two fields that are currently of high political salience and strategic significance – the regulation of digital platforms, and the regulation of environmental and human rights impacts in global value chains – the EU has taken a strikingly similar regulatory approach. In the 2022 Digital Services Act and the 2024 Corporate Sustainability Due Diligence Directive, it has charged large companies with managing risks to various public values and concerns. In this contribution, we critique this shared regulatory approach. First, we argue that regulating dominant corporations via risk management obligations actually reinforces their power in three ways: it is inherently deferential to corporate power and profitability; it reinforces technocratic framings of policy problems which discourage political contestation of economic governance; and it allows corporations to evade responsibility by framing negative impacts of their activities as external problems against which they protect the public. Second, these problem framings shape the implementation as well as the content of regulations. Specifically, they direct compliance and enforcement efforts to procedure over substance; and create significant practical barriers to public and private enforcement. We conclude by discussing the implications of our analysis in the context of the EU’s current deregulatory agenda.

The increase in activities related to unmanned aircraft systems and the implementation of this new ecosystem have introduced new hazards, impacting the operational safety of air traffic, particularly near airports, creating risks and disruptions in the flow of aircraft. The establishment of airspace for unmanned traffic management has required the integration of this new airspace with the existing one, bringing the potential for issues from this integration. A method was identified as needed to guide the detection of hazards posed to air traffic control activities and the consequent implementation of required mitigation measures. The aim of this work is to propose a framework for identifying hazards introduced to air traffic control, with a view to ensure the safe transition of this process. The method involved consulting air traffic operational safety specialists via a questionnaire, presenting the hazards highlighted in the literature concerning the integration of new airspace concepts within air traffic control activities. The results, obtained through a Delphi consultation, were analysed based on the most frequently assigned scores (mode) to reflect expert consensus. The results were organised into the proposed framework, establishing a guide to risk management activities aimed at implementing the change. The resulting structure was re-submitted to specialists and validated based on the Delphi method. Contributions to society include a guide for this process and potential future implementations, while the literature gap was addressed by adding knowledge to the scientific process.

We examine the arguments made by Onitiu and colleagues concerning the need to adopt a “backward-walking logic” to manage the risks arising from the use of Large Language Models (LLMs) adapted for a medical purpose. We examine what lessons can be learned from existing multi-use technologies and applied to specialized LLMs, notwithstanding their novelty, and explore the appropriate respective roles of device providers and regulators within the ecosystem of technological oversight.

This paper presents two studies with packaging design engineers and quality and risk professionals in the pharmaceutical packaging industry, addressing the critical need for design support. The studies contribute to the development of a framework aimed at balancing risk management and multi-user experience in the context of product support. A review of prior work highlights the gap in tailored support for designers in this field. Using structured interviews and thematic analysis, seven key requirements were identified to guide the framework’s creation. A user persona was also developed, capturing the core responsibilities, challenges, and motivations of quality and risk professionals. These findings provide actionable insights to aid designers address complex regulatory and user-centric challenges, paving the way for innovation and improved outcomes in pharmaceutical packaging design.

This systematic literature review comprehensively assesses the risks associated with implementing Industry 4.0/5.0 technologies. It clusters these risks into six groups (strategic, financial, operational, technological, environmental, and sociocultural). Using a PRISMA-guided approach, the analysis of 83 peer-reviewed papers identified 36 unique risks out of a total of 811. The findings reveal critical challenges, including in cybersecurity threats, financial burdens, technological obsolescence, and workforce adaptation. These results provide a structured risk categorization that can assist enterprises, in effectively mitigating risks and aligning their strategies with Industry 4.0/5.0 transitions. This framework closes knowledge gaps and offers actionable insights for a robust and sustainable implementation.

To meet the upcoming sustainability challenges, aerospace manufacturers need to develop products that both address complex sustainability factors and ensure profitable realization. Furthermore, the sustainability perspective needs to be lifted from focusing on carbon emissions, and broadened to include a system-level socio-ecological view. Manufacturers are thus challenged to balance sustainability, manufacturability, and performance, but lack the methods and tools to make well-informed decisions. We propose a method for conducting multi-domain trade-off studies in the early design phase. A functional architecture modelling approach is utilized to model performance and manufacturing aspects. Together with a relative sustainability fingerprint conducted on design alternatives, design spaces can be explored with respect to performance, manufacturability, and sustainability.

The increasing complexity and connectivity of the mobility system and modern automotive systems, particularly connected autonomous vehicles, demand a paradigm shift toward resilience-by-design to address disruptions in dynamic environments. Unlike established safety and cybersecurity engineering in automotive, resilience engineering has yet to be systematically integrated into development processes. This paper defines resilience using a standard-based definition method, emphasizing disruption tolerance, adaptability, and recoverability. We identify action fields to advance the topic and propose a resilience-by-design framework extending safety and cybersecurity perspectives. Resilience-by-design offers strategies and methods to design robust, adaptive systems, ensuring reliability and availability of automotive systems, functions, and components in operation.

Unintended technical interactions across system interfaces can lead to costly failures and rework, particularly in the early design stages of complex products. This study examines how structured risk assessment tools influence teams’ ability to identify, evaluate and mitigate risks from such indirect interactions. In a controlled experiment, 14 engineering teams (comprising professionals and graduate students) engaged in simulated design decisions across three system configurations. Tool usage – including models of direct and indirect risk propagation and value-based trade-offs – was continuously logged and linked to outcomes. Teams that engaged earlier and more deliberately with the tools identified risks sooner and selected mitigation actions with more favourable cost–benefit profiles. Results show that strategic, not merely frequent, tool use improves risk management performance, particularly when addressing cascading effects from indirect physical interactions. These findings support the use of structured supports to enhance both the efficiency of early-stage risk evaluation and the efficacy of risk treatment.

This paper examines in what way providers of specialized Large Language Models (LLM) pre-trained and/or fine-tuned on medical data, conduct risk management, define, estimate, mitigate and monitor safety risks under the EU Medical Device Regulation (MDR). Using the example of an Artificial Intelligence (AI)-based medical device for lung cancer detection, we review the current risk management process in the MDR entailing a “forward-walking” approach for providers articulating the medical device’s clear intended use, and moving on sequentially along the definition, mitigation, and monitoring of risks. We note that the forward-walking approach clashes with the MDR requirement for articulating an intended use, as well as circumvents providers reasoning around the risks of specialised LLMs. The forward-walking approach inadvertently introduces different intended users, new hazards for risk control and use cases, producing unclear and incomplete risk management for the safety of LLMs. Our contribution is that the MDR risk management framework requires a backward-walking logic. This concept, similar to the notion of “backward-reasoning” in computer science, entails sub-goals for providers to examine a system’s intended user(s), risks of new hazards and different use cases and then reason around the task-specific options, inherent risks at scale and trade-offs for risk management.