TY - GEN
T1 - Value-based Requirements Engineering for Human-Centred AI
T2 - 34th IEEE International Requirements Engineering Conference Workshops, REW 2026
AU - Dkhil, Nour
AU - Bennaceur, Amel
AU - Benzarti, Imen
N1 - Publisher Copyright:
© 2026 IEEE.
PY - 2026
Y1 - 2026
N2 - Artificial intelligence (AI) systems are increasingly central to decisions that impact individuals and society, showing the need for these systems to align with stakeholder values. However, traditional engineering approaches often relegate values to implicit considerations or early design phases, which diminishes their influence on system behaviour and operational decision-making. This paper investigates how Value-based Requirements Engineering (VBRE) can facilitate the development of human-centred AI systems that uphold stakeholder values, especially within dynamic and collaborative human-AI contexts. We propose that VBRE serves as a foundational framework for integrating stakeholder values as first-class artefacts throughout the entire AI system lifecycle. Our analysis consolidates existing research and identifies three core challenges: (1) the multilevel operationalisation of values from abstract principles to measurable system behaviours, (2) closing the gap between design-time value specification and runtime system behaviour, and (3) enabling shared value-driven decision-making between humans and AI at runtime. This paper analyses these challenges and proposes a research agenda for advancing VBRE to support the development of value-aligned, transparent, and accountable human-centred AI systems.
AB - Artificial intelligence (AI) systems are increasingly central to decisions that impact individuals and society, showing the need for these systems to align with stakeholder values. However, traditional engineering approaches often relegate values to implicit considerations or early design phases, which diminishes their influence on system behaviour and operational decision-making. This paper investigates how Value-based Requirements Engineering (VBRE) can facilitate the development of human-centred AI systems that uphold stakeholder values, especially within dynamic and collaborative human-AI contexts. We propose that VBRE serves as a foundational framework for integrating stakeholder values as first-class artefacts throughout the entire AI system lifecycle. Our analysis consolidates existing research and identifies three core challenges: (1) the multilevel operationalisation of values from abstract principles to measurable system behaviours, (2) closing the gap between design-time value specification and runtime system behaviour, and (3) enabling shared value-driven decision-making between humans and AI at runtime. This paper analyses these challenges and proposes a research agenda for advancing VBRE to support the development of value-aligned, transparent, and accountable human-centred AI systems.
KW - Human-centred AI
KW - Shared Human-AI Decision-Making
KW - Stakeholder Values
KW - Value Alignment
KW - Value-based Requirements Engineering
UR - https://www.scopus.com/pages/publications/105052153491
U2 - 10.1109/REW72749.2026.00077
DO - 10.1109/REW72749.2026.00077
M3 - Contribution to conference proceedings
AN - SCOPUS:105052153491
T3 - Proceedings - 2026 IEEE 34th International Requirements Engineering Conference Workshops, REW 2026
SP - 452
EP - 459
BT - Proceedings - 2026 IEEE 34th International Requirements Engineering Conference Workshops, REW 2026
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 August 2026 through 21 August 2026
ER -