A Multilayered Study of Trends, Ethical Agendas for Machine Learning, and Worldwide Impact

Authors

  • Rishwinder Singh Baidwan Department of Computer Science and Engineering, CGC-COE Landran, Mohali, Punjab, India
  • Tusharika Singh Department of Computer Science and Engineering, CGC-COE Landran, Mohali, Punjab, India
  • Rakesh Kumar Department of Regulatory Affairs, Auxein Medical Private Limited, Sonipat, Haryana, India

DOI:

https://doi.org/10.70112/ajcst-2024.13.1.4254

Keywords:

Machine Learning, Multilayered Study, Ethical Agendas, Worldwide Impact

Abstract

Many businesses have been significantly influenced by the rapid emergence of Artificial Intelligence (AI), a branch of Computer Science focused on developing intelligent machines. This study examines the current state of machine learning (ML), a core aspect of AI, as well as its global impact and ethical considerations. It explores how the availability of data and advancements in computational models have expanded the capacity of AI systems to handle complex tasks. It also investigates the ethical issues surrounding AI technology and the proposed solutions. This discussion addresses the various ways AI is evolving and how it affects industries such as manufacturing, healthcare, transportation, and finance, highlighting both potential benefits and drawbacks. The study aims to illuminate the intricate relationship between machine learning and society by examining existing literature, including both well-established and newly released studies. It outlines the key insights drawn from the literature review, covering machine learning's trends, advancements, ethical considerations, and societal impact. Finally, the study emphasizes the connection between machine learning and society, summarizes the key findings, and suggests areas for further research.

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S. Kumar and R. Kumar, “Influence of processing conditions on the properties of thermal sprayed coating: a review,” Surface Engineering, vol. 37, no. 11, pp. 1339-1372, Aug. 2021, doi: 10.1080/02670844.2021.1967024.

S. Kumar, A. Handa, V. Chawla, N. K. Grover, and R. Kumar, “Performance of thermal-sprayed coatings to combat hot corrosion of coal-fired boiler tube and effect of process parameters and post-coating heat treatment on coating performance: a review,” Surface Engineering, vol. 37, no. 7, pp. 833-860, May 2021, doi: 10.1080/02670844.2021.1924506.

S. Kumar, M. Kumar, and A. Handa, “Erosion corrosion behaviour and mechanical properties of wire arc sprayed Ni-Cr and Ni-Al coating on boiler steels in a real boiler environment,” Materials at High Temperatures, vol. 37, no. 6, pp. 370-384, Aug. 2020, doi: 10.1080/09603409.2020.1810922.

S. Kumar, M. Kumar, and A. Handa, “Comparative study of high temperature oxidation behavior and mechanical properties of wire arc sprayed Ni Cr and Ni Al coatings,” Engineering Failure Analysis, vol. 106, p. 104173, Dec. 2019, doi: 10.1016/j.engfailanal.2019.104173.

S. Kumar, M. Kumar, and A. Handa, “High temperature oxidation and erosion-corrosion behaviour of wire arc sprayed Ni-Cr coating on boiler steel,” Materials Research Express, vol. 6, no. 12, p. 125533, Jan. 2020, doi: 10.1088/2053-1591/ab5fae.

M. Kumar, S. Kant, and S. Kumar, “Corrosion behavior of wire arc sprayed Ni-based coatings in extreme environment,” Materials Research Express, vol. 6, no. 10, p. 106427, Aug. 2019, doi: 10.1088/ 2053-1591/ab3bd8.

T. S. Bedi, S. Kumar, and R. Kumar, “Corrosion performance of hydroxyapaite and hydroxyapaite/titania bond coating for biomedical applications,” Materials Research Express, vol. 7, no. 1, p. 015402, Dec. 2019, doi: 10.1088/2053-1591/ab5cc5.

S. Kumar, M. Kumar, and A. Handa, “Combating hot corrosion of boiler tubes - A study,” Engineering Failure Analysis, vol. 94, pp. 379-395, Dec. 2018, doi: 10.1016/j.engfailanal.2018.08.004.

S. Kumar, M. Kumar, and N. Jindal, “Overview of cold spray coatings applications and comparisons: a critical review,” World Journal of Engineering, vol. 17, no. 1, pp. 27-51, Jan. 2020, doi: 10.1108/wje-01-2019-0021.

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Published

22-03-2024

How to Cite

Baidwan, R. S., Singh, T., & Kumar, R. (2024). A Multilayered Study of Trends, Ethical Agendas for Machine Learning, and Worldwide Impact. Asian Journal of Computer Science and Technology, 13(1), 18–26. https://doi.org/10.70112/ajcst-2024.13.1.4254

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