Towards Requirements Engineering for GenAI-Enabled Software: Bridging Responsibility Gaps through Human Oversight Requirements

Abstract

Context: Responsibility gaps, long-recognized challenges in socio-technical systems where accountability becomes diffuse or ambiguous, have become increasingly pronounced in GenAI-enabled software. This study seeks to establish a coherent perspective for a systematic analysis of responsibility gaps from a human oversight requirements standpoint, encompassing how these responsibility gaps should be conceptualized, identified, and represented throughout the requirements engineering process. Methods: The proposed design methodology is structured across three analytical layers. At the conceptualization layer, it establishes a conceptual framing that defines the key elements of responsibility across the human and system dimensions and explains how potential responsibility gaps emerge from their interactions. At the methodological layer, it introduces a deductive pipeline for identifying responsibility gaps by analyzing interactions between these dimensions and deriving corresponding oversight requirements within established requirements engineering frameworks. At the artifact layer, it formalizes the results in a Deductive Backbone Table, a reusable representation that traces the reasoning path from responsibility gaps identification to human oversight requirements derivation. Results: A user study compared the proposed methodology with a baseline goal-oriented requirements engineering approach. Participant-perception results indicated generally favorable views of the enhanced approach across the evaluated dimensions, while expert ratings of the generated requirement artifacts showed higher mean scores for six of the seven artifact-quality items, with the strongest descriptive improvements observed for consistency and representational traceability.