Shahidur Rahoman, Sohag and Syed Muroza Mushrul, Pasha and Muhammad Mahin, Ali (2023) Advanced Approaches to Achieve Adaptive Ethical and AI-Driven Human-Centric Software Engineering. International Journal of Scientific Research and Modern Technology, 2 (11): 321. pp. 19-31. ISSN 2583-4622

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Abstract

Adapting the diversity and modified user requirements, particularly personalization, adaptability and ethics cannot be satisfied by the modern software engineering approaches. This study provides a novel foundation of an adaptive, AI driven, user facing software engineering. It leverages AI to tailor software systems in the moment, factoring in diverse human elements ranging from emotional state to cognitive load to accessibility requirements to dynamically shifting user preferences. At the core of this framework is an active feedback loop from users, where software systems can continuously adapt, evolve, and respond to dynamic user needs throughout their lifecycle. It also involves a complete suite of ethical guidelines that make sure values such as equity, transparency, and inclusion are considered at all stages of the design and development process. In this respect, the ethical emphasis tries to minimize the chances of bias, intrusion into privacy, and exclusionary practices that may arise with the integration of AI into software. This approach offers a robust, responsible solution to software system creation in a manner that is not only technically effective but also socially responsible, merging AI-driven adaptability with a staunch commitment to ethical principles. Designed for various industry verticals, such as healthcare, education, smart cities, and public services, the framework provides scalable solutions to the multivariate challenges associated with human-centered software engineering.

Item Type: Article
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User: Unnamed user with email editor@ijsrmt.com
Date Deposited: 02 Apr 2025 19:13
Last Modified: 02 Apr 2025 19:13
URI: https://eprint.ijsrmtpublication.org/id/eprint/52

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