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1201

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Civil Engineering

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Dec 6, 2023

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Uploaded by GeneralQuailMaster915

Mobayode O. Akinsol, (2023). Applied artificial intelligence in manufacturing and industrial production systems: PEST considerations for engineering managers. IEEE Engineering Management Review , 51(1), 52-62. https://doi.org/10.1109/EMR.2022.3209891 Mobayode O. Akinsol, (2023) discusses how most new AI has been used for long data analysis and for replacing repetitive jobs in the field of engineering such as designing complex models. Furthermore, AI has also impacted manufacturing of these raw materials meaning that civil engineers can find new and safer ways on how to acquire raw materials in the most ethical and economical way. Which leads the article to also focus on how AI is now being used in the industrial and manufacturing side of engineering. The true purpose of this article is to aid engineers that do not fully understand AI databases or how AI implications work but are experienced in manufacturing and in design. This helps engineers learn crucial details about how AI is changing the industry of engineering. The article describes the political, economic, social, and technological (AKA PEST) impacts that AI has on engineering. This does not mean it is imposing a new model for engineering but just showing how AI can benefit engineering and any industrial/ manufacturing field of work. This article will be used in part 2 of my Social and Ethical Analysis (SEA), because of its in-depth evaluation of how AI is impacting the industrial side of engineering. In the case of civil engineering buildings, bridges, water management systems, or even highway roads are built. This comes into play by helping show a crucial point on my causal loop diagram (CLD) talking about the new ways AI is being used in the field of civil engineering. Thus, this helps the reader see emphasis on my balancing loop on my CLD on how AI is changing the field of civil engineering not just by computing complex solutions/ designs but by helping the building or manufacturing of raw materials or roads and highways etc. Hamitouche, M., & Molina, J. (2022). A review of (AI)methods for the prediction of high flow extremal hydrology. Water Resources Management , 36(10), 3859-3876. https://doi.org/10.1007/s11269-022-03240-y . Hamitouche, M., & Molina, J. (2022) discusses the way AI is being used for predicting high level extremes in the sub field of civil engineering known as hydrology. The author notes various techniques that AI is used for and shows examples of these techniques that I will mention later in

the summary. Hamitouche, M., & Molina, J. (2022) go into detail about these techniques talking about how some AI implements are better than others. To see which AI method’s impacts are better than others, a strengths, weaknesses, opportunities, and threats (SWOT) is used to test which methods of AI are ethically correct based on a criterion. For example, predictable methods have been studied and shown to perform the best are artificial neural network (ANN), support vector machine (SVM), wavelets transform (WT) and Bayesian methods (BT). These AI methods produce the best high level flow extreme predictions. This article will be used in part 3 of my Social and Ethical Analysis (SEA), because of the ways in which Hamitouche, M., & Molina, J. (2022) mention how AI was producing predictions on how the technology would control high flow extremes in hydrology. Thus, this shows how AI technology has had a beneficial impact on the field of civil engineering. With Al doing this job this allows engineers to be able to focus on other jobs. Another key piece of this article is it talks about how they test different methods of AI technology to see what predictions/ outputs they give to see which AI methods are the best to perform these predictions for hydrology. Lagaros, N., & Plevris, V. (2022). Artificial intelligence (AI) applied in civil engineering. Applied Sciences , 12(15), 7595. https://doi.org/10.3390/app12157595 . Lagaros, N., & Plevris, V. (2022) discusses ways that AI has been able to gain main attention in recent years due to the impact that it has not only on civil engineering but also various scientific fields. AI benefits civil engineering by increasing the processes of construction and pioneering a new working space for builders and engineers. Furthermore, the authors cover why AI has benefited civil engineering, which is that AI makes the decision-making process faster, easier, and far more efficient. The article goes into depth on how Ai will not only change the computing side of civil engineering but also in the construction sector, allowing them to overcome challenges they face in the field and improve overall worksite efficiency. This article will be used in part 3 of my Social and Ethical Analysis (SEA), because of how the authors Lagaros, N., & Plevris, V. (2022) evaluate how AI positively benefits the field of civil engineering and they cover the most recent ways AI is going to further change the industry. For example, AI will aid the construction process of building the projects that civil engineers are tasked with thus making these construction projects more efficient. Another way AI can aid the construction process of projects is with drones mapping out where the foundation of the building

should be placed. Thus, this would be able to help support my idea as to why AI is important for the future of civil engineering. (My critical ethical analysis & Ethical Analysis sources are the following and are in blue texts.) Carew, P., Stapleton, L., & Byrne, G. (2008). Implications of an ethic of privacy for human-0 centered systems engineering. AI & Society , 22(3), 385-403. https://doi.org/10.1007/s00146-007-0149-7 . Carew, et al, (2008) discusses the issue with ethical privacy in factors dealing with systems engineering. The authors note their concerns with addressing that there are moral standards to cover privacy issues within systems engineering. Therefore, meaning that within systems engineering AI must be used in the most ethical way possible. Carew, et al, (2008) goes on to further explain that they look at the role of privacy in systems engineering through the human centered design perspective. They examined two human-centered design standards using what they call a multi-dimensional privacy model, what they uncovered was that these human- centered standards are inefficient in dealing with privacy issues. These authors draw attention to future ways we can implicate and make changes to the use of privacy in system engineering. This article will be used in part 3 of my Social and Ethical Analysis (SEA), because of the in- depth information that it gives about the issues with the privacy of using AI. Meaning that for civil engineers this can cause a major problem with their privacy because, by using AI to design buildings or any projects they must entrust AI with highly private files and if the AI fails to provide an adequate amount of privacy. The engineer could lose the design blueprints, thus meaning the contract fails and millions of projects dollars are lost. Who is ethically in the wrong the engineer for using AI or AI for not having adequate amount of privacy. Blake, R., Mathew, R., George, A., & Papakostas, N. (2021). Impact of artificial intelligence on engineering: Past, Present and Future. Procedia CIRP, 104, 1728-1733. https://doi.org/10.1016/j.procir.2021.11.291 . Blake,et al, (2021) evaluates how AI has impacted and evolved the field of engineering. It shows how AI has become a substantial influence in our society and today's business models. But however, with all the benefits of AI it also comes with its drawbacks which the authors go into context by mentioning the recent scandals that have been plaquing AI technology. Which are

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auto pilots crashing or even to AI facial recognition that do not perform well with dark skin toned people which has caused major back lash of this recent technology in all fields not only just in engineering. The article evaluates the future of AI in micro/ macro perspectives to show what are all negative impacts of the use of AI in the future. This article will be used in part 3 of my Social and Ethical Analysis (SEA), because the author mentions various recent instances where AI has been criticized for not performing the way it should which is causing the users of AI to react with this recent technology in a negative way. Furthermore, I would like to use this article to help back my opinion as to why I think we should slow down incorporating AI in every field of engineering because the chance of AI causing a problem in the designs of a civil engineer is high due to how new the technology is. This is also a problem for every recent technology. It comes with its fair number of ups and downs but the benefits of using AI ethically outweigh all the negatives of using AI in such fields. I support AI but I believe that we should be careful how we use AI in the field of civil engineering.

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