AI ETHICS BY DESIGN: INTEGRATING ETHICAL CONSTRAINTS INTO AI MODELS FOR ENGINEERING APPLICATIONS
Abstract
This review paper studied ethical restriction integration within artificial intelligence (AI) models which engineers use in their applications. The research adopted a secondary qualitative method to evaluate recent documents and case studies from sectors including civil engineering and renewable energy with smart systems. The research established that organizations increasingly endorse ethics by design yet practical execution of these principles remains scattered across various domains. Core ethical principles such as fairness and transparency and accountability emerged frequently but received varied implementation throughout different processes. The research emphasized the need to build specialized ethical frameworks along with collaborative teamwork between different fields and objective ethical assessment methods to promote ethical AI development in engineering.
Keyword : AI Ethics, Engineering Applications, Ethics by Design, Responsible AI, Transparency, Accountability, Fairness, Interdisciplinary Collaboration, Ethical Frameworks, Sustainability, Explainability, Ethical Evaluation.

This work is licensed under a Creative Commons Attribution 4.0 International License.
References
1. AJAILIA, N., ZERAI, M., DEBBABI, N., DAMERGI, A. and DCHICHA, M., ETHICS, AI, AND SOCIETY: SHAPING RESPONSIBLE AI ENGINEERS WITH CDIO FRAMEWORK. Tsvetkova, Anastasia; Morariu, Andrei-Raoul; Hellström, Magnus; Bolbot, Victor; Virtanen, Seppo Investigation of student perspectives on curriculum needs for autonomous shipping, p.253. 2. Badini, S., Regondi, S. and Pugliese, R., 2023. Unleashing the power of artificial intelligence in materials design. Materials, 16(17), p.5927. 3. Habbak, H., Mahmoud, M., Metwally, K., Fouda, M.M. and Ibrahem, M.I., 2023. Load forecasting techniques and their applications in smart grids. Energies, 16(3), p.1480. 4. Jenis, J., Ondriga, J., Hrcek, S., Brumercik, F., Cuchor, M. and Sadovsky, E., 2023. Engineering applications of artificial intelligence in mechanical design and optimization. Machines, 11(6), p.577. 5. Jenis, J., Ondriga, J., Hrcek, S., Brumercik, F., Cuchor, M. and Sadovsky, E., 2023. Engineering applications of artificial intelligence in mechanical design and optimization. Machines, 11(6), p.577. 6. Krishna Prasad Buravelli, S. (2024). Analyzing Skill Development in the Context of Automotive Digital Transformation. Global Journal of Business and Integral Security. Retrieved from https://gbis.ch/index.php/gbis/article/view/479 7. Mallinger, K. and Baeza-Yates, R., 2024. Responsible AI in Farming: A Multi-Criteria Framework for Sustainable Technology Design. Applied Sciences, 14(1), p.437. 8. Manzoor, B., Othman, I., Durdyev, S., Ismail, S. and Wahab, M.H., 2021. Influence of artificial intelligence in civil engineering toward sustainable development—a systematic literature review. Applied System Innovation, 4(3), p.52. 9. Miller, T., Durlik, I., Kostecka, E., Kozlovska, P., Staude, M. and Sokołowska, S., 2025. The Role of Lightweight AI Models in Supporting a Sustainable Transition to Renewable Energy: A Systematic Review. Energies, 18(5), p.1192. 10. Nosrati, H. and Nosrati, M., 2023. Artificial intelligence in regenerative medicine: applications and implications. Biomimetics, 8(5), p.442. 11. Paolanti, M., Tiribelli, S., Giovanola, B., Mancini, A., Frontoni, E. and Pierdicca, R., 2024. Ethical framework to assess and quantify the trustworthiness of artificial intelligence techniques: Application case in remote sensing. Remote Sensing, 16(23), p.4529. 12. Pastor-Escuredo, D., Treleaven, P. and Vinuesa, R., 2022. An ethical framework for artificial intelligence and sustainable cities. Ai, 3(4), pp.961-974. 13. Ucar, A., Karakose, M. and Kırımça, N., 2024. Artificial intelligence for predictive maintenance applications: key components, trustworthiness, and future trends. Applied Sciences, 14(2), p.898. 14. Weber-Lewerenz, B., 2021. Corporate digital responsibility (CDR) in construction engineering—ethical guidelines for the application of digital transformation and artificial intelligence (AI) in user practice. SN Applied Sciences, 3, pp.1-25.