AI models are increasingly applied in high-stakes domains like health and conservation.
Data quality carries an elevated significance in high-stakes AI due to its heightened …

Artificial intelligence (AI) and machine learning (ML) are quickly becoming pervasive in ways
that impact the lives of all humans across the globe. In an effort to make otherwise” black …

Frontline health workers are the first and often the only access point to basic health care
services in low-and-middle income countries. However, the work and the issues frontline …

Conventional algorithmic fairness is West-centric, as seen in its subgroups, values, and
methods. In this paper, we de-center algorithmic fairness and analyse AI power in India …

Field workers, like farmers and radiologists, play a crucial role in dataset collection for AI
models in low-resource settings. However, we know little about how field workers' expertise …

Diversity in datasets is a key component to building responsible AI/ML. Despite this
recognition, we know little about the diversity among the annotators involved in data …

Recent advances in Artificial Intelligence (AI) suggest that AI applications could transform
healthcare delivery in the Global South. However, as researchers and technology …

Data-driven approaches that form the foundation of advancements in machine learning (ML)
are powered in large part by human infrastructures that enable the collection of large …

There has been growing interest in the application of AI for Social Good, motivated by scarce
and unequal resources globally. We focus on the case of AI in frontline health, a Social …

People are increasingly subject to the tracking of data about them at their workplaces.
Sensor tracking is used by organizations to generate data on the movement and interaction …