Responsible Artificial Intelligence on Large Scale Data to Prevent Misuse, Unethical Challenges and Security Breaches

Authors

  • Chandra Sekhar Veluru Tracy, United States.  Author

DOI:

https://doi.org/10.47363/JAICC/2024(3)331

Keywords:

Artificial Intelligence (AI), Ethical Frameworks, Accountability, Transparency, Fairness, Privacy, Security, Bias Mitigation, Explainable AI (XAI), Responsible AI Practices, Ethical AI Deployment, AI Governance

Abstract

Artificial Intelligence, AI, has recently grown exponentially and has transformed tremendously and some of the sectors that primarily benefitted are education, public administration, environmental management, and workforce management. The element of AI enhances data analysis, decision-making, and automation, and it is, according to its promises, set to do this with more efficiency and accuracy. As AI technology rapidly proliferates, it raises ethical concerns about its potential misuse, bias, and security. However, stringent ethical practices have emerged, and the emphasis remains squarely on accountability, transparency, fairness, privacy, and security. And that is what this research paper delves deeper into, to assess how it remains effective in addressing the associated risks
of AI technologies. It is therefore important to explore the key principles for responsible practices of AI, including how it is implemented and their effects across industry sectors. Along with these fundamental principles, the paper presents various case studies, which cover a series of fields to give an ample view of practical applications and success of these ethical standards. For instance, AI in education offers personalization in learning while keeping fairness and transparency, AI in public administration ensures accountability in making decisions, and the environmental management department gets to have AI application, offering sustainability to the environment. In the workforce management sector, AI enhances workforce management with ethical guidelines to ensure fairness and no bias during recruitment and evaluation processes. This establishes that some important themes entail continuous monitoring, data practices that are diverse and inclusive, and techniques for AI that can help in explaining, hence promoting transparency and trust.

Author Biography

  • Chandra Sekhar Veluru , Tracy, United States. 

    Chandra Sekhar Veluru, Tracy, United States. 

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Published

2024-01-23

How to Cite

Responsible Artificial Intelligence on Large Scale Data to Prevent Misuse, Unethical Challenges and Security Breaches. (2024). Journal of Artificial Intelligence & Cloud Computing, 3(1), 1-6. https://doi.org/10.47363/JAICC/2024(3)331

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