# AI in the "Real World": Examining the Impact of AI Deployment in Low-Resource Contexts

arXiv: https://arxiv.org/abs/2012.01165 · HTML: https://mlsanity.com/paper/2012.01165/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Nov 2020.

## Built on by (most cited first, 2 of 2)

- [From Development to Deployment of AI-assisted Telehealth and Screening for Vision- and Hearing-threatening diseases in resource-constrained settings: Field Observations, Challenges and Way Forward](https://mlsanity.com/paper/2509.15558/) (2025)
- [Detecting and Mitigating Bias by Treating Fairness as a Symmetry Operation](https://mlsanity.com/paper/2606.06514/) (2026)

## Abstract (arXiv)

As AI becomes integrated throughout the world, its potential for impact within low-resource regions around the Global South have grown. AI research labs from tech giants like Microsoft, Google, and IBM have a significant presence in countries such as India, Ghana, and South Africa. The work done by these labs is often motivated by the potential impact it could have on local populations, but the deployment of these tools has not always gone smoothly. This paper presents a case study examining the deployment of AI by large industry labs situated in low-resource contexts, highlights factors impacting unanticipated deployments, and reflects on the state of AI deployment within the Global South, providing suggestions that embrace inclusive design methodologies within AI development that prioritize the needs of marginalized communities and elevate their status not just as beneficiaries of AI systems but as primary stakeholders.