The Role of Artificial Intelligence Techniques in Analyzing the Sustainable Development Goals, Practice, Indicators, Values and Environment

This study introduces a framework aimed at enhancing the role of Artificial Intelligence (AI) in achieving the Sustainable Development Goals (SDGs). The primary objective is to address key challenges in AI applications, such as data scarcity, ethical concerns, and cultural diversity, by integrating explainable AI (XAI), simulation environments, and modular customization. The study emphasizes on region-specific datasets, synthetic data generation, and iterative refinement to improve AI solutions in sectors like poverty, healthcare, and climate action. The findings emphasizes on AI’s potential to transform theoretical solutions into practical, scalable implementations, driving sustainable development. While addressing challenges like data quality, algorithmic bias, and regulatory issues, the study also highlights the importance of ethical principles and contextual adaptability to achieve long-term, inclusive progress toward the SDGs.

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Publication Details

Journal
Recent Research Reviews Journal
Published
2025-01-27
DOI
https://doi.org/10.36548/rrrj.2024.2.011
Primary Topic
Innovation, Sustainability, Human-Machine Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

The Role of Artificial Intelligence Techniques in Analyzing the Sustainable Development Goals, Practice, Indicators, Values and Environment

Suma Sira Jacob, K. Saranya, R S Samrrutha, A Akalya et al.
Recent Research Reviews Journal
Innovation, Sustainability, Human-Machine Systems
article

The Role of Artificial Intelligence Techniques in Analyzing the Sustainable Development Goals, Practice, Indicators, Values and Environment

Suma Sira Jacob, K. Saranya, R S Samrrutha, A Akalya, L Karthika
article en

Abstract

This study introduces a framework aimed at enhancing the role of Artificial Intelligence (AI) in achieving the Sustainable Development Goals (SDGs). The primary objective is to address key challenges in AI applications, such as data scarcity, ethical concerns, and cultural diversity, by integrating explainable AI (XAI), simulation environments, and modular customization. The study emphasizes on region-specific datasets, synthetic data generation, and iterative refinement to improve AI solutions in sectors like poverty, healthcare, and climate action. The findings emphasizes on AI’s potential to transform theoretical solutions into practical, scalable implementations, driving sustainable development. While addressing challenges like data quality, algorithmic bias, and regulatory issues, the study also highlights the importance of ethical principles and contextual adaptability to achieve long-term, inclusive progress toward the SDGs.

Recent Research Reviews JournalVol. 3(2)
PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH (IN)
Openalex Percentile: Top 98%
Innovation, Sustainability, Human-Machine Systems
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