Aug 2026· AI and Ethics· Vol 6· 1 citation· 57 references
Computer Science
TL;DR
An ethical framework for integrating AI into architectural practice is proposed, advocating for balanced and inclusive approaches that prioritise societal values, environmental stewardship, and professional integrity.
Abstract
Integrating artificial intelligence (AI) into architectural design introduces significant opportunities for innovation but raises profound ethical challenges related to data privacy, algorithmic bias, professional accountability, and environmental issues. This study contributes to understanding its ethical implications. A survey of architecture master’s students at European universities explores attitudes towards AI’s role in design processes, its potential benefits, and perceived risks. Key findings reveal a strong and consistent preference for AI as a supportive tool that augments rather than replaces human creativity and professional decision-making. Participants emphasised the importance of safeguarding privacy, eliminating bias, and ensuring transparency and accountability in AI systems. This paper also proposes an ethical framework for integrating AI into architectural practice, advocating for balanced and inclusive approaches that prioritise societal values, environmental stewardship, and professional integrity. These findings offer empirical evidence and practical ethical guidance for architects, educators, researchers, professional organisations and policymakers who seek to support the responsible integration of AI into architectural practice while upholding principles of transparency, accountability, fairness, privacy and sustainability.
A comprehensive model for integrating ethical standards into the phases of the Software Development Life Cycle (SDLC) is proposed, founded on the pillars of fairness, transparency, accountability, and sustainability, offering practical recommendations aimed at developers, organizations, and policymakers.
A. Alaswad· Al-Farooq Journal of Science...· 0 citations
This article critically examines existing ethical frameworks that address major principles such as fairness, transparency, accountability, and inclusivity by their origin–governmental, corporate, academic, and algorithmic–and compares their applicability across diverse contexts.
Divya Vetriveeran, S. Krishnan· SN Computer Science· 0 citations
The findings indicate that AI integration in research ethics oversight is shaped not only by technological feasibility but by institutional concerns regarding responsibility, legitimacy, and deliberative authority.
Daniel Wang, Marta Guix Arnau, Cristina Llop Julià et al.· Research Ethics· 0 citations
This conceptual paper argues that traditional technology governance models are insufficient and that leaders must develop an augmented moral compass to navigate algorithmic decision-making, data governance, and equity and proposes an original Moral Compass Model.
This paper proposes the ARCHON framework, a set of ten requirements derived from the technical architecture of AI systems, to facilitate ethical compliance of scientific research for experts and practicioners engaging in roles such as proposal evaluators, project officers, ethics board members, or research administrato...
Jesus Manuel Benitez Baleato· Open Research Europe· 0 citations
It is concluded that originality, authorship, integrity, fairness, and transparency are interdependent concerns rather than separate issues, and that responsible AI use is best understood as a disciplined, disclosed collaboration with a non-author tool.
K. A. Badaru· Interdisciplinary Journal of...· 0 citations
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