AI in Bangladeshi libraries: opportunities and challenges

Abstract

Purpose

This paper aims to explore the opportunities and challenges associated with adopting artificial intelligence (AI) in libraries in Bangladesh and provide recommendations to guide the responsible integration of AI to enhance library services and accessibility.

Design/methodology/approach

The paper reviews relevant literature on the applications of AI in libraries, the current state of technology adoption in Bangladeshi libraries and the ethical considerations surrounding AI implementation. It analyzes the potential benefits of AI tools such as chatbots, intelligent search engines, text-to-speech and language translation for improving user services and inclusion. The challenges of infrastructure constraints, lack of resources and skills, data privacy issues and bias are also examined through the lens of the Bangladeshi context.

Findings

AI offers transformative opportunities to automate operations, strengthen user services through 24/7 virtual assistants and personalized recommendations and promote accessibility for diverse users in Bangladeshi libraries. However, significant challenges such as inadequate technology infrastructure, funding limitations, shortage of AI-skilled staff, data privacy risks and potential biases must be addressed. Strategically planning for sustainable implementation, building AI capacity, prioritizing ethical AI development and fostering collaborations are critical factors for successful AI adoption.

Originality/value

This paper provides an in-depth analysis of the prospects and obstacles in leveraging AI specifically for libraries in Bangladesh. It offers original insights and context-specific recommendations tailored to the needs and constraints of a developing nation working to harness AI’s potential to create dynamic, inclusive knowledge centers serving all communities.

Citation

Mahmud, M.R. (2024), "AI in Bangladeshi libraries: opportunities and challenges", Library Hi Tech News, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/LHTN-04-2024-0053