Authors : Bhawya Prajapati

Volume/Issue : Volume 10 - 2025, Issue 2 - February

Google Scholar : https://tinyurl.com/npxvenfj

Scribd : https://tinyurl.com/4ssyrnbx

DOI : https://doi.org/10.5281/zenodo.14964550

Abstract : In the current era, artificial intelligence (AI) has become a disruptive force that is affecting many industries. AIis propelling innovation at a never-before- seen rate, from automating sectors and transforming economies to transforming healthcare and education. This article examines the various facets of artificial intelligence's position in the modern world, emphasising its uses, difficulties, and moral ramifications. It explores how AI-powered systems improve productivity, make better decisions, and solve challenging issues while addressing privacy, bias, and job displacement issues. This paper highlights the necessity of responsible development and governance frameworks to harness AI's potential for social benefit by analysing both the benefits and challenges it poses. The results highlight that although AI is an effective tool for progress, its integration needs to be properly controlled to guarantee fair and moral results in a world that is changing quickly

Keywords : Artificial Intelligence, Ethical Challenges in AI, AI in Healthcare.

References :

1. Brynjolfsson, E., & McAfee, A. (2017). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W.
2. W. Norton & Company.
3. Binns, R. (2018). Fairness in Machine Learning: Lessons from Political Philosophy. Proceedings of the 2018 Conference on Fairness, Accountability, and Transparency.
4. Chen, M., et al. (2020). Applications of Artificial Intelligence in Healthcare: Strategies and Challenges. Current Research in Translational Medicine, 68(2), 59-66.
5. Davenport, T. H., & Ronanki, R. (2018). Artificial Intelligence for the Real World. Harvard Business Review, 96(1), 108-116.
6. Topol, E. J. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books.
7. Luckin, R., et al. (2016). Intelligence Unleashed: An Argument for AI in Education. Pearson Education White Paper.
8. Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial Intelligence and the Public Sector: Applications and Challenges. International Journal of Public Administration, 42(7), 596-615.
9. Cath, C., et al. (2018). Artificial Intelligence and the ‘Good Society’: The US, EU, and UK Approach. Science and Engineering Ethics, 24, 505-528.
10. Dwivedi, Y. K., et al. (2021). Artificial Intelligence (AI): Multidisciplinary Perspectives on Emerging Challenges, Opportunities, and Agenda for Research, Practice, and Policy. International Journal of Information Management, 57, 101994.
11. Floridi, L., et al. (2018). AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations. Minds and Machines, 28(4), 689-707.
12. Angwin, J., et al. (2016). Machine Bias. ProPublica.
13. Bresnick, J. (2018). IBM Watson’s Role in Oncology Care. Health IT Analytics.
14. CropIn. (2020). AI in Agriculture: Enhancing Crop Yields. CropIn White Paper.
15. howed Bias Against Women. Reuters.
16. De Fauw, J., et al. (2018). Clinically Applicable Deep Learning for Diagnosis in Retinal Disease. Nature Medicine, 24(9), 1342-1350.
17. Floridi, L., et al. (2018). AI4People—An Ethical Framework for a Good AI Society. Minds and Machines, 28(4), 689-707.
18. McKinsey Global Institute. (2021). AI and the Future of Work. McKinsey Reports.
19. Midorikawa, S. (2021). AI in Earthquake Prediction: Advancements and Challenges. Journal of Disaster Research, 16(3), 290-298.
20. NITI Aayog. (2021). AI for All: India’s National Strategy. Government of India Reports.
21. VanLehn, K. (2011). The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems. Educational Psychologist, 46(4), 197-221.
22. Dastin, J. (2018). Amazon Scraps Secret AI Recruiting Tool that S