Paola Inverardi

Gianluca De Ninno, Paola Inverardi, Francesca Belotti

This study investigates a novel approach to eliciting users' moral decision-making by combining immersive roleplaying games with LLM analysis capabilities. Building on the distinction introduced by Floridi between hard ethics inspiring and shaping laws-and soft ethics-moral preferences guiding individual behavior within the free space of decisions compliant to laws-we focus on capturing the latter through contextrich, narrative-driven interactions. Grounded in anthropological methods, the role-playing game exposes participants to ethically charged scenarios in the domain of digital privacy. Data collected during the sessions were interpreted by a customized LLM ("GPT Anthropologist"). Evaluation through a cross-validation process shows that both the richness of the data and the interpretive framing significantly enhance the model's ability to predict user behavior. Results show that LLMs can be effectively employed to automate and enhance the understanding of user moral preferences and decision-making process in the early stages of software development.

Costanza Alfieri, Paola Inverardi, Patrizio Migliarini et al.

The development and the spread of increasingly autonomous digital technologies in our society pose new ethical challenges beyond data protection and privacy violation. Users are unprotected in their interactions with digital technologies and at the same time autonomous systems are free to occupy the space of decisions that is prerogative of each human being. In this context the multidisciplinary project Exosoul aims at developing a personalized software exoskeleton which mediates actions in the digital world according to the moral preferences of the user. The exoskeleton relies on the ethical profiling of a user, similar in purpose to the privacy profiling proposed in the literature, but aiming at reflecting and predicting general moral preferences. Our approach is hybrid, first based on the identification of profiles in a top-down manner, and then on the refinement of profiles by a personalized data-driven approach. In this work we report our initial experiment on building such top-down profiles. We consider the correlations between ethics positions (idealism and relativism) personality traits (honesty/humility, conscientiousness, Machiavellianism and narcissism) and worldview (normativism), and then we use a clustering approach to create ethical profiles predictive of user's digital behaviors concerning privacy violation, copy-right infringements, caution and protection. Data were collected by administering a questionnaire to 317 young individuals. In the paper we discuss two clustering solutions, one data-driven and one model-driven, in terms of validity and predictive power of digital behavior.

Danny Weyns, Nelly Bencomo, Radu Calinescu et al.

Providing assurances for self-adaptive systems is challenging. A primary underlying problem is uncertainty that may stem from a variety of different sources, ranging from incomplete knowledge to sensor noise and uncertain behavior of humans in the loop. Providing assurances that the self-adaptive system complies with its requirements calls for an enduring process spanning the whole lifetime of the system. In this process, humans and the system jointly derive and integrate new evidence and arguments, which we coined perpetual assurances for self-adaptive systems. In this paper, we provide a background framework and the foundation for perpetual assurances for self-adaptive systems. We elaborate on the concrete challenges of offering perpetual assurances, requirements for solutions, realization techniques and mechanisms to make solutions suitable. We also present benchmark criteria to compare solutions. We then present a concrete exemplar that researchers can use to assess and compare approaches for perpetual assurances for self-adaptation.

Marco Autili, Vittorio Cortellessa, Paolo Di Benedetto et al.

Ubiquitous networking empowered by Beyond 3G networking makes it possible for mobile users to access networked software services across heterogeneous infrastructures by resource-constrained devices. Heterogeneity and device limitedness creates serious problems for the development and deployment of mobile services that are able to run properly on the execution context and are able to ensures that users experience the "best" Quality of Service possible according to their needs and specific contexts of use. To face these problems the concept of adaptable service is increasingly emerging in the software community. In this paper we describe how CHAMELEON, a declarative framework for tailoring adaptable services, is used within the IST PLASTIC project whose goal is the rapid and easy development/deployment of self-adapting services for B3G networks.