application of artificial intelligence in construction and its relative impact on human behavior
Abstract
A digital shift and transformation have arrived in the construction industry with the sole purpose of increasing efficiency and sustainability and production. This paper seeks to find out how the construction industry can fully close the gap between potential and harvested benefits associated with artificial intelligence. This research suggests that it is indeed possible to gain experience from the implementation of digital tools when implementing artificial intelligence. However, it is essential to note that when it comes to artificial intelligence, human-artificial intelligence trust is a very crucial factor as far as the success of implementation is concerned. This paper investigates the application of artificial intelligence in construction and its relative impact on human behavior.
Literature review
The construction industry is transforming digital and more autonomous construction. Evidence shows that a digital shift is taking place, and the change is happening fast that the industry is struggling to keep up. According to (…), the construction industry is claimed to be undigitized, something that has been indicated by low productivity as far as development is concerned when compared to other sectors. However, upon implementation of digitization, it is expected that efficiency increases as well. With artificial intelligence in the realm, stakeholders in this particular industry must take advantage of and incorporate AI in the construction process.
According to (….), implementing change is a somewhat hectic process, and as such, through time, commitment to the process may be severely damaged when the right measures are not put into place.
Artificial intelligence is regarded as the unique ability of a machine to mimic intelligent human behavior by using algorithms inspired by human behavior. In the construction industry, implementation of Ai is considered as a digital transformation. Various benefits have been associated with artificial intelligence not only in the construction industry but also in others. Some of the advantages associated with artificial intelligence include; improved end user’s experience and reduced errors as well as maximizing value and minimizing waste.
Artificial intelligence will help the construction industry in overcoming some of its most significant challenges, including safety issues, scheduling, and increased costs. However, for artificial intelligence to finally take root in the construction industry, it has to address the industry’s fundamental issues and problems. Here, the longer an Ai system takes to gather data, the more effective it becomes. When using data-analyzing artificial intelligence systems, every step and process in construction becomes many points of data. The data is then customized by machine-learning algorithms to identify possible mistakes in the process and take corrective measures where possible.
AI-human interaction is also a very significant issue in the implementation of AI in construction. Just like human-human cooperation requires defined responsibility and tasks, so does human-AI collaboration. Even though functions and responsibilities are well distributed between humans and AI, it is often complicated for humans to trust artificial intelligence outputs. How artificial intelligence arrives at specific predictions and recommendations before considering other relevant variables and what-ifs that are likely to occur in the process. As such, AI systems should be fully supported by human intervention not only to oversee AI operations in construction projects but also to enhance the effectiveness and efficiency of an AI system.
According to (…), artificial intelligence in construction is likely to reduce the probability of possible accidents and other risks. The construction industry is considered to be among one of the most traumatic sectors because of the numerous risks associated with it. AI, however, through artificial intelligence, accidents possible cases of accidents cannot only be tracked but also predicted, thus reducing accident rates in the industry.