Responsible AI for AI Sustainable Future: Governance, Ethics, and The Reality Behind the Promise
DOI:
https://doi.org/10.70715/jitcai.2025.v2.i2.012Keywords:
Ethics, Governance, Responsible AI, SustainabilityAbstract
Artificial intelligence has emerged as a powerful force shaping global development, offering promising solutions across health, education, climate change, and governance. However, its rapid integration into critical sectors raises urgent questions about ethics, governance, and sustainability. This systematic review explores the promise and practice of responsible AI through the lens of three core objectives: the governance mechanisms guiding AI implementation, the ethical frameworks shaping its design, and the practical realities influencing its deployment across contexts. Drawing from sixty peer-reviewed articles published between 2017 and 2024, the review identifies strong global consensus on foundational principles such as fairness, accountability, and transparency. Nonetheless, a significant implementation gap persists, particularly in low-resource settings, where enforcement mechanisms and institutional readiness are often lacking. The findings also reveal that ethical commitments are frequently undermined by organizational constraints and commercial interests, leading to surface-level adherence without substantive change. Environmental sustainability, a critical dimension of responsible AI, remains underrepresented in current governance discussions despite mounting evidence of AI’s carbon footprint. This review contributes to the growing body of scholarship advocating for inclusive, enforceable, and context-sensitive approaches to responsible AI. It underscores the need for deeper engagement with the political, social, and environmental realities that shape AI’s impact on sustainable development. Ultimately, bridging the gap between AI’s ethical aspirations and real-world outcomes requires not only technical innovation but also strong institutional leadership, interdisciplinary collaboration, and meaningful stakeholder participation.
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Data Availability Statement
This study is based on a systematic review of peer-reviewed literature, and no primary data were collected. All sources analyzed are publicly available through academic databases such as Scopus, IEEE Xplore, and Web of Science. A complete list of reviewed articles is included in the references. No additional datasets were generated or analyzed during the study.
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Copyright (c) 2025 Miracle Atianashie, Mark K. Kuffour, Bernard Kyiewu , Philipa Serwaa (Author)
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