The concept of Corporate Social Responsibility (CSR) has evolved since Milton Friedman’s 1970 assertion that a business’s sole responsibility is profit. Today, global frameworks like the UN Global Compact and EU regulations emphasize corporate accountability, particularly regarding social and environmental impacts. Corporate Social Responsibility (CSR) has become central in discussions of firm behavior, governance, and public goods provision. CSR however varies across firms. Some adopt basic strategic CSR (b-CSR), considering social and environmental issues only to the extent that they affect consumer demand and profitability. Others practice environmentally committed CSR...

The challenge of climate change and the impact of human activity on the environment is undoubtedly one of the most pressing and urgent issues of our time. For years, efforts have been directed towards the reduction of the direct impact of systems, particularly with regard to energy consumption, through the optimisation of systems and the application of persuasive design techniques (DiSalvo et al., 2010). Nevertheless, these attempts have thus far proved inadequate (Blair, 2020). An increasing number of researchers are acknowledging the complexity of sustainability (Silberman et al., 2014), the necessity for structural change to move beyond the growth paradigm (Sharma et...

Cet article présente une nouvelle approche pour le contrôle d'une flotte de drones qui peuvent suivre la position d'une cible volante à l'aide de caméras omnidirectionnelles embarquées. Les drones utilisent l'apprentissage par renforcement multi-agents (MARL) pour apprendre des stratégies décentralisées qui optimisent leur formation et leur mouvement autour de la cible, en minimisant l'incertitude sur la position triangulée. Nous définissons une fonction de récompense qui encourage les suiveurs à minimiser la trace de la matrice de covariance de la position triangulée, dérivée d'un modèle analytique de propagation de l'incertitude. Nous utilisons Multi-Agent PPO (MAPPO)...

Uncrewed Aerial Systems (UAS) mishaps are partially attributable to mental fatigue during long endurance missions. Mental fatigue decreases cognitive flexibility resulting in a decreased performance when switching between sub-tasks. Solutions include adaptive interfaces. We propose a technical proof of concept that launches visual alerts to mitigate operator mental fatigue by estimating future performance based on brain activity (EEG). The proposed solution uses flying and detection tasks, and includes an online classification pipeline. The method is designed to work in an intra-user and inter-session manner, i.e. the solution is tuned to a user and works without...

<div><p>This article presents an interpretable approach to binary image classification using Genetic Programming (GP), applied to the PatchCamelyon (PCAM) dataset, which contains small tissue biopsy patches labeled as malignant or benign. While Deep Neural Networks (DNNs) achieve high performance in image classification, their opaque decision-making processes, prone to overfitting behavior and dependency on large amounts of annotated data limit their utility in critical fields like digital pathology, where interpretability is essential. To address this, we employ GP, specifically using the Multi-Modal Adaptive Graph Evolution (MAGE) framework, to evolve end-to-end image...

In the past years, the use of drones has been increasingly introduced to firefighting operations. Drawing on concrete examples from interviews with Thai firefighting professionals and recent field trials, as well as prior research, this paper examines the challenges of integrating (partially) autonomous, AI-enhanced drones into firefighting operations. Our findings reveal that, despite the promise of automation, on-field operators still prefer communication via a dedicated drone pilot-a preference driven by unresolved trust issues and concerns over information overload. We discuss challenges such as trust in automation and adaptive take-over. These inform our proposals...

Radio Frequency Interference (RFI), such as jamming and spoofing, represents a growing threat to GNSS receivers, especially in civil aviation, which requires a high level of accuracy, integrity, continuity, and availability. Although jamming and spoofing interference signal models have been extensively studied in the literature, and GNSS observables are commonly used in spoofing detection, the exact impact of spoofing on these observables remains relatively unexplored. Understanding the impact of jamming and spoofing on GNSS receivers is essential for enhancing their resilience and facilitating the development of more sophisticated detection methods. Developing a model of...

The DICE model claims that technological progress can prevent global warming at low cost. However, many uncertainties about climate damages and backstop technologies are not taken into account in this model. Our analysis is based on a very large number of scenarios to account for the possible range of the climate damage function and the level of efficiency of future backstop technologies, as well as their financial costs. We show that if DICE's assumptions turn out to be less optimistic, it's a very risky bet to rely on technology alone to tackle climate change, with 82% of our scenarios leading to economic collapse. Then we introduce in the DICE model a social lever...

<div><p>À l’image de ses aéroports, des espaces où se matérialisent une multitude d’enjeux, économiques, sociaux, environnementaux, le transport aérien, dans son ensemble, est profondément enchevêtré dans le fonctionnement des sociétés humaines actuelles. Au-delà du moyen de transport, de l’outil au service de la mobilité, l’activité aérienne a infiltré toutes les composantes de la vie en société. Elle est par certains égards l’un de ses piliers organisateurs, et même d’un mode vie à part entière. À l’heure d’une réflexion sur le devenir de l’aviation au prisme du dérèglement climatique, il s’agit de mesurer et d’établir une vue globale sur ses implications sociétales...