Role of artificial intelligence (AI) in poverty alleviation: a bibliometric analysis

Abstract

Purpose

This study aims to examine the current state of academic research pertaining to the role played by artificial intelligence (AI) in the achievement of a critical sustainable development goal (SDG) – poverty alleviation and describe the field’s development by identifying themes, trends, roadblocks and promising areas for the future.

Design/methodology/approach

The authors analysed a corpus of 253 studies collected from the Scopus database to examine the current state of the academic literature using bibliometric methods.

Findings

This paper identifies and analyses key trends in the evolution of this domain. Further, the paper distils the extant literature to unpack the intermediary mechanisms through which AI and related technologies help tackle the critical global issue of poverty.

Research limitations/implications

The corpus of literature used for the analysis is limited to English language studies from the Scopus database. The paper contributes to the extant research on AI for social good, and more broadly to the research on the value of emerging technologies such as AI.

Practical implications

Policymakers and government agencies will get an understanding of how technological interventions such as AI can help achieve critical SDGs such as poverty alleviation (SDG-1).

Social implications

The primary focus of this paper is on the role of AI-related technological interventions to achieve a significant social objective – poverty alleviation.

Originality/value

To the best of the authors’ knowledge, this is the first study to conduct a comprehensive bibliometric analysis of a critical research domain such as AI and poverty alleviation.

Citation

Raghavendra, A.H., Majhi, S.G., Mukherjee, A. and Bala, P.K. (2023), "Role of artificial intelligence (AI) in poverty alleviation: a bibliometric analysis", VINE Journal of Information and Knowledge Management Systems, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/VJIKMS-05-2023-0104