Article Information

Authors DR.HUSNA SULTANA
Article Type Research Article
Language English
Journal North Asian International Research Journal of Sciences, Engineering & I.T.
ISSN 2454-7514
Volume 11
Issue 1
Pages 34-39
Publication Year 2025
Publication Date January 01, 2025
DOI URL https://doiglobal.org/10.2025/NAIRJCSEIT.003

Abstract

Artificial intelligence (AI) has evolved from a largely theoretical effort to reproduce selected forms of human reasoning into a broad technological field that supports perception, language, prediction, planning, creativity, and autonomous action. This paper reviews the conceptual foundations of AI, the historical transition from symbolic systems to data-driven learning, the enabling role of deep neural networks and transformer architectures, and the growing use of AI in health care, education, finance, agriculture, manufacturing, public administration, and scientific research. It also examines persistent limitations, including dependence on data quality, bias, opacity, hallucination, cybersecurity exposure, concentration of computational power, and environmental cost. The paper argues that the future value of AI will depend not only on higher model capability but also on governance, human oversight, transparency, evaluation, and equitable access. Amultidisciplinary approach is therefore required so that AI augments human judgment rather than displacing responsibility

Keywords

artificial intelligence deep learning generative AI responsible AI automation ethics governance

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DOI: 10.2025/NAIRJCSEIT.003

References

1. Autio, C., et al. (2024). Artificial intelligence risk management framework: Generative artificial intelligence profile (NIST AI 600-1). National Institute of Standards and Technology.
2. Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.
3. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521, 436-444. https://doi.org/10.1038/nature145394. McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (1955). A proposal for the Dartmouth summer research project on artificial intelligence.
5. National Institute of Standards and Technology. (2023). Artificial intelligence risk management framework (AI RMF 1.0) (NIST AI 100-1).

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DR.HUSNA SULTANA (2025). ARTIFICIAL INTELLIGENCE: FOUNDATIONS, APPLICATIONS, ETHICAL CHALLENGES, AND FUTURE DIRECTIONS. North Asian International Research Journal of Sciences, Engineering & I.T.. DOI: https://doiglobal.org/10.2025/NAIRJCSEIT.003

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