# Global AI Ethics: A Review of the Social Impacts and Ethical Implications of Artificial Intelligence

arXiv: https://arxiv.org/abs/1907.07892 · HTML: https://mlsanity.com/paper/1907.07892/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jul 2019.

## Built on by (most cited first, 21 of 21)

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- [Towards Trustworthy AI: A Review of Ethical and Robust Large Language Models](https://mlsanity.com/paper/2407.13934/) (2024)
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- [Simulating Policy Impacts: Developing a Generative Scenario Writing Method to Evaluate the Perceived Effects of Regulation](https://mlsanity.com/paper/2405.09679/) (2024)
- [How Platform-User Power Relations Shape Algorithmic Accountability: A Case Study of Instant Loan Platforms and Financially Stressed Users in India](https://mlsanity.com/paper/2205.05661/) (2022)
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- [AI and Identity](https://mlsanity.com/paper/2403.07924/) (2024)
- [Limits to AI Growth: The Ecological and Social Consequences of Scaling](https://mlsanity.com/paper/2501.17980/) (2025)
- [Are You Worthy of My Trust?: A Socioethical Perspective on the Impacts of Trustworthy AI Systems on the Environment and Human Society](https://mlsanity.com/paper/2309.09450/) (2023)
- [(Unfair) Norms in Fairness Research: A Meta-Analysis](https://mlsanity.com/paper/2407.16895/) (2024)
- ["My Kind of Woman": Analysing Gender Stereotypes in AI through The Averageness Theory and EU Law](https://mlsanity.com/paper/2407.17474/) (2024)
- [Ethical Concerns of Generative AI and Mitigation Strategies: A Systematic Mapping Study](https://mlsanity.com/paper/2502.00015/) (2025)
- [Understanding Critical Thinking in Generative Artificial Intelligence Use: Development, Validation, and Correlates of the Critical Thinking in AI Use Scale](https://mlsanity.com/paper/2512.12413/) (2025)
- [Evaluating the Capabilities of LLMs for Supporting Anticipatory Impact Assessment](https://mlsanity.com/paper/2401.18028/) (2024)
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- [Bridging the AI Trustworthiness Gap between Functions and Norms](https://mlsanity.com/paper/2512.20671/) (2025)

## Abstract (arXiv)

The ethical implications and social impacts of artificial intelligence have become topics of compelling interest to industry, researchers in academia, and the public. However, current analyses of AI in a global context are biased toward perspectives held in the U.S., and limited by a lack of research, especially outside the U.S. and Western Europe. This article summarizes the key findings of a literature review of recent social science scholarship on the social impacts of AI and related technologies in five global regions. Our team of social science researchers reviewed more than 800 academic journal articles and monographs in over a dozen languages. Our review of the literature suggests that AI is likely to have markedly different social impacts depending on geographical setting. Likewise, perceptions and understandings of AI are likely to be profoundly shaped by local cultural and social context. Recent research in U.S. settings demonstrates that AI-driven technologies have a pattern of entrenching social divides and exacerbating social inequality, particularly among historically-marginalized groups. Our literature review indicates that this pattern exists on a global scale, and suggests that low- and middle-income countries may be more vulnerable to the negative social impacts of AI and less likely to benefit from the attendant gains. We call for rigorous ethnographic research to better understand the social impacts of AI around the world. Global, on-the-ground research is particularly critical to identify AI systems that may amplify social inequality in order to mitigate potential harms. Deeper understanding of the social impacts of AI in diverse social settings is a necessary precursor to the development, implementation, and monitoring of responsible and beneficial AI technologies, and forms the basis for meaningful regulation of these technologies.