AI for Social Good papers

Nigerian English adaptation, Pidgin, has evolved over the years through multi-language code switch- ing, code mixing and linguistic adaptation. While Pidgin preserves many of the words in the normal English language corpus, both in spelling and...

Artificial intelligence (AI) is already part of our daily lives and is playing a key role in defining the economic and social shape of the future. In 2018, the European Commission introduced its AI strategy able to compete in the next years with world...

Rotating savings and credit associations (roscas) are informal financial organizations common in settings where communities have reduced access to formal financial institutions. In a rosca, a fixed group of participants regularly contribute small sums of...

We present a large-scale case study using agent plat- form that facilitated and gathered public opinions on internet-based town discussion. The hypothesis set to test how agent-mediated argumentative messages leads the discussion structure in a “Issue...

In this paper we consider the problem of building Boolean rule sets in disjunctive normal form (DNF), an interpretable model for binary classification, subject to fairness constraints. We formulate the problem as an integer program that maximizes...

Disease dynamics, human mobility, and public policies co-evolve during a pandemic such as COVID-19. Understanding dynamic human mobility changes and spatial interaction patterns are crucial for understanding and forecasting COVID- 19 dynamics. We...

Online search engines are an extremely popular tool for seeking information. However, the results returned sometimes exhibit undesirable or even wrongful forms of bias, such as with respect to gender or race. In this paper, we consider the problem of fair...

Fair representation learning is an important task in many real-world domains, with the goal of finding a performant model that obeys fairness requirements. We present an adversarial representation learning algorithm that learns an informative...

This paper focuses on learning index-based policies in rest- less multi-armed bandits (RMAB) with applications to public health concerns such as maternal health. Maternal health is a very important public health concern. It refers to the health of women...

In this work, we look at cases where we want a classifier to be both fair and interpretable, and find that it is necessary to make trade-offs between these two properties. We have theoretical results to demonstrate this tension between the two...