AI-driven solutions for personalized knowledge dissemination and inclusive library user experiences
1 Texas A&M University -Commerce, Texas, USA.
2 Independent Researcher, United Kingdom.
Review
International Journal of Engineering Research Updates, 2023, 04(02), 052-062.
Article DOI: 10.53430/ijeru.2023.4.2.0023
Publication history:
Received on 01 March 2023; revised on 18 April 2023; accepted on 21 April 2023
Abstract:
Artificial Intelligence (AI) is revolutionizing the way libraries deliver knowledge, enabling personalized dissemination and fostering inclusive user experiences. This review explores AI-driven solutions designed to address the diverse needs of library users, ensuring equitable access to information and resources. By leveraging AI technologies such as machine learning (ML), natural language processing (NLP), and recommender systems, libraries can transform user engagement and knowledge delivery. Machine learning models analyze user behavior and preferences, enabling libraries to provide tailored resource recommendations that enhance discovery and satisfaction. NLP facilitates semantic search capabilities, automated summarization, and real-time translation, ensuring that language barriers and information overload are minimized. Recommender systems further personalize user interactions by suggesting relevant resources based on collaborative and content-based filtering techniques. AI-powered chatbots and virtual assistants play a pivotal role in providing real-time support, streamlining inquiries, and ensuring accessibility for users with disabilities. These tools, coupled with assistive technologies like speech-to-text and screen readers, enhance inclusivity for visually and hearing-impaired individuals. Furthermore, AI-driven solutions extend the reach of library services to underserved communities by overcoming geographical, linguistic, and cultural barriers. This highlights successful implementations of AI in academic and public libraries, emphasizing their impact on creating adaptive, user-centric services. Challenges, including data privacy, algorithmic bias, and ethical considerations, are discussed to ensure responsible AI deployment. Recommendations for future research include advancing open-source AI tools and fostering cross-institutional collaborations to democratize knowledge dissemination. AI-driven personalization and inclusivity have the potential to redefine library services, promoting equity, accessibility, and engagement. This research underscores the transformative role of AI in empowering libraries to meet evolving user needs and support lifelong learning.
Keywords:
AI-driven; Dissemination; Inclusive library; User experiences
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Copyright information:
Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0