Ethics of Artificial Intelligence and Robotics in the Architecture, Engineering, and Construction Industry
This research paper systematically reviews AI and robotics literature in the architecture, engineering, and construction (AEC) industry through the lens of ethics. It identifies nine key ethical issues including job loss, data privacy, data security, data transparency, decision-making conflict, acceptance and trust, reliability and safety, fear of surveillance, and liability. Furthermore, it outlines thirteen relevant research topics and provides specific future research directions to promote safer and more efficient technology adoption.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Researchers, developers, and industry practitioners looking to understand the ethical challenges and future research directions of AI and robotics adoption in the AEC sector.
What the document contains
The document provides a systematic review of AI and robotics research in the architecture, engineering, and construction (AEC) industry through an ethical lens. It categorizes existing literature into thirteen research topics and details nine specific ethical issues alongside recommended future research directions.
The text does not provide binding regulatory rules, legal enforcement mechanisms, or direct corporate policy mandates, focusing instead on an academic review of literature and ethical frameworks.
- The integration of AI and robotics in the AEC industry creates critical ethical implications that have not received sufficient attention in academic research.
- Nine main ethical issues were identified: job loss, data privacy, data security, data transparency, decision-making conflict, acceptance and trust, reliability and safety, fear of surveillance, and liability.
- Data transparency and acceptance and trust are among the most frequently highlighted ethical concerns in the existing literature.
- Future research must prioritize human-robot collaboration safety, explainable AI, trust-building, cybersecurity, bias and fairness, and standardized responsibility frameworks.
· Introduction · Research Methodology · Ethics of AI and Robotics · Systematic Review and Scientometric Analysis · Ethical Issues of AI and Robotics in AEC Industry · Discussion · Future Research Direction · Conclusion
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
3/5Clear responsibility for AI outcomes
Liability refers to the responsibility of an individual or group that might be held accountable
5.9. Liability
screening score · 2026-10-23
Fairness
3/5Non-discrimination and equitable treatment
AI systems can also be biased in making decisions due to the training data, which emphasizes the need for fair AI systems
5.5. Decision-making Conflict
screening score · 2026-10-23
Human Oversight
3/5Humans remain in control of consequential decisions
Before arriving at a final decision, human workers can assess the suggestions made by the AI system at each step and provide comments to improve them.
5.5. Decision-making Conflict
screening score · 2026-10-23
Enforcement
0/5Consequences and compliance mechanisms with real force
Abstract
screening score · 2026-10-23
Impact Assessment
2/5Required assessment of an AI system's risks/impacts before or during use
Ethical risks should be assessed and measured when designing robots, which is similar to the safety assurance in robot design.
3. Ethics of AI and Robotics
screening score · 2026-10-23