Viola Schiaffonati

Camilla Quaresmini, Valentina Breschi, Jessica Leoni et al.

Fairness in online advertising is often formalized as a distributive justice problem, aiming to ensure that impressions, opportunities, or outcomes are allocated comparably across protected groups. Yet online advertising can still produce harms arising from ads' content and from how recipients interpret and uptake them. To capture this dimension, we draw on Miranda Fricker's notion of hermeneutical injustice. We model ad delivery as a mechanism that distributes interpretative resources and can fail in two ways: relevant concepts can be withheld through systematic under-exposure, leading to hermeneutical deprivation; and recipients may experience hermeneutical distortions when saturated with low-uptake or skewed framings. Grounded in exploratory correlational patterns from the AIDS Advertising Evaluation surveys (1986-1987), we introduce a group-level hermeneutical fairness constraint and a hermeneutically aware utility cost. We integrate them into a benchmark, utility-driven ad allocation framework that already enforces distributive justice, yielding a distributively fair, hermeneutically aware framework that prevents deprivation and distortion from concentrating within protected groups. Through controlled simulations, we explore trade-offs between economic utility, classical distributive fairness constraints, and hermeneutical cost. The results show that purely utility-based allocation drives under-delivery to the disadvantaged group. When the hermeneutical stakes of withholding ads are high, distributive constraints reduce hermeneutical cost at modest utility loss. Conversely, weighting hermeneutical cost without distributive constraints can yield policies concentrated on the disadvantaged group. These findings motivate expanding fairness analyses of online advertising beyond distributive notions to include epistemic conditions of interpretation and uptake.

Milad Leyli-abadi, Ricardo J. Bessa, Jan Viebahn et al.

The interaction between humans and AI in safety-critical systems presents a unique set of challenges that remain partially addressed by existing frameworks. These challenges stem from the complex interplay of requirements for transparency, trust, and explainability, coupled with the necessity for robust and safe decision-making. A framework that holistically integrates human and AI capabilities while addressing these concerns is notably required, bridging the critical gaps in designing, deploying, and maintaining safe and effective systems. This paper proposes a holistic conceptual framework for critical infrastructures by adopting an interdisciplinary approach. It integrates traditionally distinct fields such as mathematics, decision theory, computer science, philosophy, psychology, and cognitive engineering and draws on specialized engineering domains, particularly energy, mobility, and aeronautics. Its flexibility is further demonstrated through a case study on power grid management.

Agnese Chiatti, Sara Bernardini, Lara Shibelski Godoy Piccolo et al.

The rapid adoption of Vision Language Models (VLMs), pre-trained on large image-text and video-text datasets, calls for protecting and informing users about when to trust these systems. This survey reviews studies on trust dynamics in user-VLM interactions, through a multi-disciplinary taxonomy encompassing different cognitive science capabilities, collaboration modes, and agent behaviours. Literature insights and findings from a workshop with prospective VLM users inform preliminary requirements for future VLM trust studies.

Agnese Chiatti, Lara Piccolo, Sara Bernardini et al.

With the growing deployment of Vision-Language Models (VLMs), pre-trained on large image-text and video-text datasets, it is critical to equip users with the tools to discern when to trust these systems. However, examining how user trust in VLMs builds and evolves remains an open problem. This problem is exacerbated by the increasing reliance on AI models as judges for experimental validation, to bypass the cost and implications of running participatory design studies directly with users. Following a user-centred approach, this paper presents preliminary results from a workshop with prospective VLM users. Insights from this pilot workshop inform future studies aimed at contextualising trust metrics and strategies for participants' engagement to fit the case of user-VLM interaction.