Beyond Automation: Why Human-Centered Decision Making Remains Essential in Construction

Authors

  • Atul Prakash Lad Florida, USA Author

DOI:

https://doi.org/10.63282/3050-9246/ICRTCSIT-105

Keywords:

Artificial Intelligence (AI), Automation, Construction Management, Human-in-the-Loop (HITL), Ethical Oversight, Robotics, Digital Twins, Explainable AI (XAI), Safety Governance, Building Information Modeling (BIM), Human Judgment, Decision-Making, Accountability, Construction Ethics, Hybrid Intelligence

Abstract

The construction industry is undergoing a profound digital transformation as artificial intelligence (AI), robotics, and automation reshape traditional workflows. From AI-driven scheduling to robotic layout and computer vision-based safety monitoring, automation now touches nearly every phase of a project’s lifecycle. Yet despite these advances, construction remains a domain where uncertainty, accountability, and ethical decision-making cannot be fully automated. This paper examines the boundary between machine precision and human judgment through a qualitative framework that integrates professional field experience, regulatory standards, and recent academic findings. Using the Human-in-the-Loop (HITL) governance model, it identifies five domains technical, legal, ethical, managerial, and cultural where human oversight remains indispensable. The analysis demonstrates that while automation enhances speed and data accuracy, only human professionals can interpret intent, manage risk, and uphold safety and compliance. The study concludes that the future of construction lies not in full automation but in hybrid intelligence where digital tools inform and accelerate, and human judgment defines meaning, trust, and accountability. This collaboration between human expertise and AI-driven precision represents not the end of craftsmanship, but its evolution

Downloads

Download data is not yet available.

References

[1] ASTM International, “Standard Test Method for Surface Burning Characteristics of Building Materials,” ASTM E84-16, 2016. [Online]. Available: https://www.astm.org/e0084-16.html. doi:10.1520/E0084-16. (accessed Oct. 9, 2025).

[2] U.S. Dept. of Labor, Occupational Safety and Health Administration (OSHA),“DefinitionsCompetent person,” 29 CFR 1926.32(f). [Online]. Available: https://www.osha.gov/laws-regs/regulations/standardnumber/1926/1926.32 and “General safety and health provisions,” 29 CFR 1926.20(b). [Online]. Available: https://www.osha.gov/laws-regs/regulations/standardnumber/1926/1926.20 (accessed Oct. 9, 2025).

[3] The American Institute of Architects (AIA), “A2012017, General Conditions of the Contract for Construction,” AIA Document A201-2017, 2017. [Online]. Available: https://help.aiacontracts.com/hc/en-us/articles/1500010259162-Summary-A201-2017-General-Conditions-of-the-Contract-for-Construction (accessed Oct. 9, 2025).

[4] National Society of Professional Engineers (NSPE), “Code of Ethics for Engineers,” 2019. [Online]. Available: https://www.nspe.org/sites/default/files/resources/pdfs/Ethics/CodeofEthics/NSPECodeofEthicsforEngineers.pdf (accessed Oct. 9, 2025).

[5] Miami-Dade County, Dept. of Regulatory & Economic Resources (RER), Product Control Section,“Product Control Search Notice of Acceptance (NOA) database,” 2024. [Online]. Available: https://www.miamidade.gov/building/pc-search_app.asp (accessed Oct. 9, 2025).

[6] Royal Institution of Chartered Surveyors (RICS), “Artificial intelligence in construction report,” 2025. [Online]. Available: https://www.rics.org/news-insights/artificial-intelligence-in-construction-report (accessed Oct. 9, 2025).

[7] A. Monteiro and J. P. Martins, “A survey on modeling guidelines for quantity takeoff-oriented BIM-based design,” Autom. Constr., vol. 35, pp. 238–253, 2013, doi: 10.1016/j.autcon.2013.05.005. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0926580513000721 (accessed Oct. 9, 2025).

[8] M. Valinejadshoubi, O. Moselhi, I. Iordanova, F. Valdivieso, and A. Bagchi, “Automated system for high-accuracy quantity takeoff using BIM,” Autom. Constr., vol. 157, 105155, 2024, doi:10.1016/j.autcon.2023.105155. [Online]. Available: https://doi.org/10.1016/j.autcon.2023.105155 (accessed Oct. 9, 2025).

[9] M. A. Al-Sinan, A. A. Bubshait, and Z. Aljaroudi, “Generation of construction scheduling through machine learning and BIM: A blueprint,” Buildings, vol. 14, no. 4, 934, 2024, doi:10.3390/buildings14040934. [Online]. Available: https://www.mdpi.com/2075-5309/14/4/934 (accessed Oct. 9, 2025).

[10] A. A. Khan, A. O. Bello, M. Arqam, and F. Ullah, “Integrating Building Information Modelling and Artificial Intelligence in Construction Projects: A Review of Challenges and Mitigation Strategies,” Technologies, vol. 12, no. 10, 185, 2024. doi: 10.3390/technologies12100185. [Online]. Available: https://www.mdpi.com/2227-7080/12/10/1851 (accessed Oct. 9, 2025).

[11] V. Singh, N. Gu, and X. Wang, “A theoretical framework of a BIM-based multi-disciplinary collaboration platform,” Autom. Constr., vol. 20, no. 2, pp. 134–144, 2011. doi: 10.1016/j.autcon.2010.09.011. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0926580510001408 (accessed Oct. 9, 2025).

[12] K. Ammon, “The Role of Human-in-the-Loop in AI-Driven Data Management,” TDWI Articles, Sept. 3, 2025. [Online]. Available: https://tdwi.org/articles/2025/09/03/adv-all-role-of-human-in-the-loop-in-ai-data-management.aspx (accessed Oct. 9, 2025).

[13] Y. Fu, S. Foell, X. Xu, and A. Hiniker, “From Text to Self: Users’ Perception of AIMC Tools on Interpersonal Communication and Self,” in Proc. CHI ’24: CHI Conf. on Human Factors in Comput. Syst., Honolulu, HI, USA, May 11–16, 2024, Art. no. 977, 17 pp. doi: 10.1145/3613904.3641955. [Online]. Available: https://faculty.washington.edu/alexisr/aimc.pdf (accessed Oct. 9, 2025).

[14] B. C. Lee and J. J. Chung, “An empirical investigation of the impact of ChatGPT on creativity,” Nat. Hum. Behav., vol. 8, pp. 1906–1914, 2024, doi: 10.1038/s41562-024-01953-1. [Online]. Available: https://www.nature.com/articles/s41562-024-01953-1 (accessed Oct. 9, 2025).

[15] A. Rudniy, “Artificial intelligence for automated scoring and feedback in chemistry courses,” J. Writing Anal., vol. 7, 2024, doi: 10.37514/JWA-J.2024.7.1.02. [Online]. Available: https://wac.colostate.edu/docs/jwa/vol7/rudniy.pdf (accessed Oct. 9, 2025).

[16] McKinsey & Company, “Building AI trust: The key role of explainability,” Nov. 26, 2024. [Online]. Available: https://www.mckinsey.com/capabilities/quantumblack/our-insights/building-ai-trust-the-key-role-of-explainability (accessed Oct. 9, 2025).

[17] N. Emaminejad and R. Akhavian, “Trust in Construction AI-Powered Collaborative Robots: A Qualitative Empirical Analysis,” arXiv:2308.14846, 2023. [Online]. Available: https://arxiv.org/abs/2308.14846 (accessed Oct. 9, 2025).

[18] J. I. Dingel and B. Neiman, “How Many Jobs Can Be Done at Home?,” NBER Working Paper 26948, Apr. 2020 (rev. Jun. 2020). [Online]. Available: https://www.nber.org/papers/w26948 (accessed Oct. 9, 2025).

[19] C. P. Pathirage, D. G. Amaratunga, and R. P. Haigh, “Tacit knowledge and organisational performance: Construction industry perspective,” J. Knowl. Manag., vol. 11, no. 1, pp. 115–126, 2007, doi: 10.1108/13673270710728277. [Online]. Available: https://doi.org/10.1108/13673270710728277 (accessed Oct. 9, 2025).

[20] A. Lawani, R. Flin, R. F. Ojo-Adedokun, and P. Benton, “Naturalistic decision making and decision drivers in the front end of complex projects,” Int. J. Proj. Manag., vol. 41, no. 6, 102502, Aug. 2023, doi: 10.1016/j.ijproman.2023.102502. [Online]. Available: https://doi.org/10.1016/j.ijproman.2023.102502 (accessed Oct. 9, 2025).

[21] ConsensusDocs, “The Hidden Risks of Using AI on Construction Projects,” July 10, 2025. [Online]. Available: https://www.consensusdocs.org/news/the-hidden-risks-of-using-ai-on-construction-proje/ (accessed Oct. 9, 2025).

[22] American Society of Safety Professionals (ASSP), “Defining the Role of AI in Safety,” Dec. 1, 2024. [Online]. Available: https://www.assp.org/news-and-articles/defining-the-role-of-ai-in-safety (accessed Oct. 9, 2025).

[23] M. Thibault, “Builders slow to adopt AI despite perceived benefits,” Construction Dive, Oct. 1, 2025. [Online]. Available: https://www.constructiondive.com/news/builders-ai-survey-adoption-gap-construction/761632/ (accessed Oct. 9, 2025).

[24] H. Luo, J. Chen, P. E. D. Love, and W. Fang, “Explainable transfer learning for modeling and assessing risks in tunnel construction,” IEEE Trans. Eng. Manage., vol. 71, pp. 8339–8355, 2024. doi: 10.1109/TEM.2024.3369231.

[25] S. Yoon, T. Chang, and S. Chi, “Developing an integrated construction safety management system for accident prevention,” J. Manag. Eng., vol. 40, no. 6, 04024112, 2024. doi: 10.1061/JMENEA.MEENG-6074. [Online]. Available: https://ascelibrary.org/doi/10.1061/JMENEA.MEENG-6074 (accessed Oct. 9, 2025).

[26] National Institute of Standards and Technology (NIST), AI Risk Management Framework (AI RMF 1.0), NIST AI 100-1, 2023. [Online]. Available: https://nvlpubs.nist.gov/nistpubs/ai/nist.ai.100-1.pdf (accessed Oct. 9, 2025).

[27] National Society of Professional Engineers (NSPE), “Use of Artificial Intelligence in Engineering Practice,” Board of Ethical Review Case, Jul. 18, 2025. [Online]. Available: https://www.nspe.org/career-growth/ethics/board-ethical-review-cases/use-artificial-intelligence-engineering-practice (accessed Oct. 9, 2025).

[28] F. Zahedi, H. Alavi, J. Majrouhi Sardroud, and H. Dang, “Digital Twins in the Sustainable Construction Industry,” Buildings, vol. 14, no. 11, 3613, 2024. doi: 10.3390/buildings14113613. [Online]. Available: https://www.mdpi.com/2075-5309/14/11/3613 (accessed Oct. 9, 2025).

[29] F. Forest, H. Porta, D. Tuia, and O. Fink, “From classification to segmentation with explainable AI: A study on crack detection and growth monitoring,” Automation in Construction, vol. 165, 105497, Sep. 2024. doi: 10.1016/j.autcon.2024.105497. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0926580524002334 (accessed Oct. 9, 2025).

[30] McKinsey Global Institute (MGI), “Reinventing construction: A route to higher productivity,” Feb. 2017. [Online]. Available: https://www.mckinsey.com/~/media/mckinsey/business%20functions/operations/our%20insights/reinventing%20construction%20through%20a%20productivity%20revolution/mgi-reinventing-construction-a-route-to-higher-productivity-full-report.pdf (accessed Oct. 9, 2025).

[31] McKinsey & Company, “The next normal in construction: How disruption is reshaping the world’s largest ecosystem,” June 2020. [Online]. Available: https://www.mckinsey.com/~/media/McKinsey/Industries/Capital%20Projects%20and%20Infrastructure/Our%20Insights/The%20next%20normal%20in%20construction/The-next-normal-in-construction.pdf (accessed Oct. 9, 2025).

[32] Dusty Robotics, “Mechanical layout with FieldPrinter,” 2025. [Online]. Available: https://www.dustyrobotics.com/solutions/mechanical (accessed Oct. 9, 2025).

[33] Trimble, “C.D. Smith Case StudyRobotic Total Station (RTS) Layout,” Aug. 19, 2020. [Online]. Available: https://fieldtech.trimble.com/resources/case-studies/c-d-smith-case-study-rts-layout (accessed Oct. 9, 2025).

[34] H. Salama and A. Elshafey, “Comparison of robotic and traditional interior construction layout methods,” J. Build. Eng., vol. 96, 108604, 2025. doi: 10.1007/s41693-025-00163-z. [Online]. Available: https://link.springer.com/10.1007/s41693-025-00163-z (accessed Oct. 9, 2025).

[35] D. Ruan, P. Long, and M. Johnson-Roberson, “Reducing uncertainty in multi-robot construction through adaptive coordination,” in Proc. ISARC 2023, 2023, pp. 1–8. [Online]. Available: https://deepblue.lib.umich.edu/bitstream/handle/2027.42/177311/004_ISARC%202023_Paper_226.pdf (accessed Oct. 9, 2025).

[36] A. Batool and A. Abbas, “Robotics in construction: Opportunities and challenges,” Int. J. Recent Technol. Eng., vol. 8, no. 2S11, pp. 119–125, 2019. [Online]. Available: https://www.ijrte.org/wp-content/uploads/papers/v8i2S11/B12420982S1119.pdf (accessed Oct. 9, 2025).

[37] JE Dunn, “Exploring robotics’ potential for mapping more accurate, efficient layouts,” Oct. 1, 2024. [Online]. Available: https://jedunn.com/blog/exploring-robotics-potential-for-mapping-more-accurate-efficient-layouts/ (accessed Oct. 9, 2025).

[38] M. Golparvar-Fard, F. Peña-Mora, and S. Savarese, “Automated Progress Monitoring Using Unordered Daily Construction Photographs and IFC-Based Building Information Models,” J. Comput. Civ. Eng., vol. 29, no. 1, 2015, doi: 10.1061/(ASCE)CP.1943-5487.0000205. [Online]. Available: https://ascelibrary.org/doi/abs/10.1061/(ASCE)CP.1943-5487.0000205 (accessed Oct. 9, 2025).

[39] Y. Turkan, F. Bosché, C. T. Haas, and R. Haas, “Automated progress tracking using 4D schedule and 3D sensing technologies,” Autom. Constr., vol. 22, pp. 414–421, 2012. doi: 10.1016/j.autcon.2011.10.003. [Online]. Available: https://doi.org/10.1016/j.autcon.2011.10.003 (accessed Oct. 9, 2025).

[40] W. Fang, L. Ding, B. Zhong, P. E. D. Love, and H. Luo, “Computer vision applications in construction safety assurance,” Autom. Constr., vol. 110, 103013, 2020. doi: 10.1016/j.autcon.2019.103013. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S0926580519301487 (accessed Oct. 9, 2025).

[41] U.S. Dept. of Labor, OSHA, “Fall protection systems criteria and practices,” 29 CFR 1926.502 (Controlled Access Zones). [Online]. Available: https://www.osha.gov/laws-regs/regulations/standardnumber/1926/1926.502 and eCFR, “29 CFR Part 1926 Subpart MFall Protection (definitions; CAZ),” [Online]. Available: https://www.ecfr.gov/current/title-29/subtitle-B/chapter-XVII/part-1926/subpart-M (accessed Oct. 9, 2025).

[42] ASTM International, “Standard Test Method for Fire Tests of Penetration Firestop Systems,” ASTM E814-13a (2017). [Online]. Available: https://www.astm.org/Standards/E814.htm (accessed Oct. 9, 2025).

[43] UL Standards & Engagement, “UL 1479Fire Tests of Penetration Firestops,” 4th ed., Apr. 18, 2024. [Online]. Available: https://www.shopulstandards.com/ProductDetail.aspx?UniqueKey=46315 (accessed Oct. 9, 2025).

[44] International Firestop Council (IFC), “Guidelines for Evaluating Firestop Systems in Engineering Judgments (EJs),” 2018 (reaffirmed 2024). [Online]. Available: https://firestop.org/resources/engineering-judgment-guidelines/ (accessed Oct. 9, 2025).

[45] Organisation for Economic Co-operation and Development (OECD), “OECD AI Principles Recommendation of the Council on Artificial Intelligence,” 2019 (updated 2022). [Online]. Available: https://oecd.ai/en/ai-principles (accessed Oct. 9, 2025).

[46] Lean Construction Institute (LCI), “Introduction to Last Planner System®,” LCI Congress slides, Oct. 15, 2019. [Online]. Available: https://www.lcicongress.org/pdfs/2019/TAM9-Introduction%20to%20Last%20Planner%20System.pdf (accessed Oct. 9, 2025).

[47] Lean Construction Institute (LCI), “Last Planner System®,” Lean Topics page, 2025. [Online]. Available: https://leanconstruction.org/lean-topics/last-planner-system/ (accessed Oct. 9, 2025).

[48] ASTM International, “Standard Test Method for Determining Relative Humidity in Concrete Floor Slabs Using In Situ Probes,” ASTM F2170-19a, 2019. [Online]. Available: https://www.astm.org/f2170-19a.html (accessed Oct. 9, 2025).

[49] ASTM International, “Standard Test Method for Determining Fire Resistance of Perimeter Fire Barrier Systems Using Intermediate-Scale, Multi-Story Test Apparatus,” ASTM E2307-20, 2020. [Online]. Available: https://www.astm.org/e2307-20.html (accessed Oct. 9, 2025).

[50] UL Standards & Engagement, “UL 2079 Tests for Fire Resistance of Building Joint Systems,” current ed. [Online]. Available: https://www.shopulstandards.com/ProductDetail.aspx?productId=UL2079 (accessed Oct. 9, 2025).

[51] U.S. Dept. of Labor, OSHA, “Scaffolds,” 29 CFR 1926.451 (work during storms/high winds; personal fall arrest). [Online]. Available: https://www.osha.gov/laws-regs/regulations/standardnumber/1926/1926.451 (accessed Oct. 9, 2025).

[52] International Code Council (ICC), “2024 International Building Code (IBC) ICC Digital Codes,” 2024. [Online]. Available: https://codes.iccsafe.org/content/IBC2024V1.0 (accessed Oct. 9, 2025).

Published

2025-10-10

How to Cite

1.
Lad AP. Beyond Automation: Why Human-Centered Decision Making Remains Essential in Construction. IJETCSIT [Internet]. 2025 Oct. 10 [cited 2025 Dec. 16];:28-40. Available from: https://ijetcsit.org/index.php/ijetcsit/article/view/419

Similar Articles

1-10 of 370

You may also start an advanced similarity search for this article.