Designing AI-Enabled Products for Emerging Markets: Analytics-Driven Strategies Amid Data Scarcity

Abstract

Although there is much opportunity for AI-driven products in emerging markets, common machine learning techniques struggle with shortages of data, poor infrastructure and diversity in behavior. In this paper, we discuss using strategies based on analytics, like few-shot learning, producing synthetic data and federated learning to deal with these constraints. Using observations and case studies, we present practical guides for building local and ethical AI systems that are also resilient. We use fairness-aware federated systems and context expertise to provide both AI professionals and product managers with useful techniques for ethical progress in areas where resources are limited and the impact is high.