The Runtime Dimension of Ethics in Self-Adaptive Systems
Marco Autili, Gianluca Filippone, Mashal Afzal Memon, Patrizio Pelliccione
TL;DR
The paper addresses the problem of ethics at runtime in self-adaptive systems operating in ethically sensitive, multi-stakeholder environments, where decisions have social, environmental, and regulatory consequences. It proposes shifting from fixed, design-time ethical rules to runtime ethical reasoning by treating ethical preferences as runtime requirements and embedding ethics-based Multi-$\ast$ Negotiation within the adaptation loop. A five-part research agenda (RD1–RD5) with concrete research questions is outlined to enable representation, reasoning under uncertainty, conflict management, scalable negotiation, and accountability. Through a running drone example and a design-sci, empirical, and assurance-focused methodology, the work aims to enable ethically adaptive, socially legitimate, and auditable behavior in real-world deployments, i.e., systems that operate with runtime ethics under hard-ethics constraints while accommodating soft-ethics variation.
Abstract
Self-adaptive systems increasingly operate in close interaction with humans, often sharing the same physical or virtual environments and making decisions with ethical implications at runtime. Current approaches typically encode ethics as fixed, rule-based constraints or as a single chosen ethical theory embedded at design time. This overlooks a fundamental property of human-system interaction settings: ethical preferences vary across individuals and groups, evolve with context, and may conflict, while still needing to remain within a legally and regulatorily defined hard-ethics envelope (e.g., safety and compliance constraints). This paper advocates a shift from static ethical rules to runtime ethical reasoning for self-adaptive systems, where ethical preferences are treated as runtime requirements that must be elicited, represented, and continuously revised as stakeholders and situations change. We argue that satisfying such requirements demands explicit ethics-based negotiation to manage ethical trade-offs among multiple humans who interact with, are represented by, or are affected by a system. We identify key challenges, ethical uncertainty, conflicts among ethical values (including human, societal, and environmental drivers), and multi-dimensional/multi-party/multi-driver negotiation, and outline research directions and questions toward ethically self-adaptive systems.