IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Generative Artificial Intelligence: Evolution, Applications, and Ethical Considerations

Generative Artificial Intelligence: Evolution, Applications, and Ethical Considerations
View Sample PDF
Author(s): Aditya Shrivastav (Ajeenkya D.Y. Patil University, India), Sunil Sankathala (Ajeenkya D.Y. Patil University, India), Kashvi Chaturvedi (Ajeenkya D.Y. Patil University, India), Krutika Patre (Ajeenkya D.Y. Patil University, India), Susanta Das (Ajeenkya D.Y. Patil University, India)and Rizwan Shaikh (Dr. D.Y. Patil Institute of Management and Entrepreneur Development, India)
Copyright: 2026
Pages: 30
Source title: Generative AI-Powered Data Architectures: From Governance to Autonomous Analytics
Source Author(s)/Editor(s): Bahaa Eddine Elbaghazaoui (Sultan Moulay Slimane University, Morocco), Mohamed Amnai (Ibn Tofail University, Morocco)and Noreddine Gherabi (Sultan Moulay Slimane University, Morocco)
DOI: 10.4018/979-8-3373-5616-7.ch002

Purchase

View Generative Artificial Intelligence: Evolution, Applications, and Ethical Considerations on the publisher's website for pricing and purchasing information.

Abstract

Generative Artificial Intelligence (GAI) is a technical term used to designate elaborate machine learning algorithms that allow the creation of human-like output text, images, audio, and biomedical data. Such methods as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and diffusion models led to making GAI an initiative that promotes innovation in other fields such as healthcare, education, and creative fields. Yet with its fast development, one must wonder about algorithm bias as well as data privacy issues, misinformation, and control over AI-based content. The chapter delves into the history of the development of GAI, its theoretical background, and its fundamental implementation. It presents a bibliometric analysis to point out the interdisciplinary dynamics of GAI study. It looks at ethics implications, legal implications as well as social implications and necessity of responsible innovation. The chapter winds up with highlighting the challenges that persist and proposing future steps toward transparent and responsible use of generative technologies.

Related Content

Usharani Bhimavarapu. © 2026. 30 pages.
Jasvir Kaur. © 2026. 24 pages.
Nida Fatimah, K. Jayashree. © 2026. 30 pages.
Kirti Rani, Simranjit Kaur. © 2026. 24 pages.
Usharani Bhimavarapu. © 2026. 26 pages.
Piali Haldar, Dev Kumar Mandal, Utkarsh Gupta. © 2026. 32 pages.
Rachit Agarwal, Tanya Kumar, Shraddha Rawat, Harpreet Kaur. © 2026. 28 pages.
Body Bottom