Artificial Intelligence To Curtail Poverty And Attain SDG-1: Lecturers’ Perceptions
Year: 2025
Type: article
Abstract: Poverty eradication, an essential component of SDG-1, utilizes AI in education as a transformative means to alleviate poverty through enhanced teaching efficiency, innovative learning methods and diminished inequalities. This study examines lecturers’ perceptions of AI’s role in combating poverty, employing a thematic analysis of interviews conducted with 50 participants. Five research questions guided the investigation, structured around an interview titled Lecturers’ Perceptions of Using Artificial Intelligence to Curtail Poverty and Attain SDG-1 Interview (LPUAICPSI, IRR=.79) for data collection purposes. The findings reveal varying levels of awareness regarding AI in education. Whereas thirty respondents averted to the transformative potential of AI to curtail poverty, twenty admitted to having limited knowledge yet expressed a desire to learn more, highlighting the necessity for training, retraining, skilling and reskilling in AI utilization for SDG-1 attainment. Systemic issues like too much workload, insufficient resources, and trouble with new technologies were mentioned by forty-five lecturers as things that block resilience, equal education and AI utilization to curtail poverty and attain SDG-1. Lecturers pointed out that AI could help curtail poverty, but these problems must be fixed first. It was therefore recommended, among others, that institutional management arrange seminars, workshops, conferences and symposia on AI utilization to curtail poverty and enhance SDG-1 attainment. Curriculum developers and educational policymakers should also revamp educational curricula to include AI utilization for poverty alleviation and SDG-1 attainment.
DOI: 10.59231/sari7819
Author: Abiodun Ezekiel Adesina
Institution: Emmanuel Alayande University of Education, Oyo
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4411731450
