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AI for Good

What is AI for Good?

Growth in the effectiveness and relevancy of machine learning (ML) algorithms and artificial intelligence (AI) systems has presented us with a unique opportunity to tackle some of the world’s most critical issues, ranging from poverty to climate change to social inclusion. The AI for Good initiative at the Smith School of Business aims to bring together researchers, practitioners and policymakers from diverse fields to form an interdisciplinary and collaborative partnership focused on utilizing the transformative capacity of Artificial Intelligence (AI) for social good.

AI provides us with an unprecedented opportunity to tackle large scale data and make inferences from it, enabling us to solve societal problems at a global level. This opportunity comes with its own set of risks – owing to its widespread and pervasive impact, we believe, that considerable focus should be given to the research investigating the ethics behind AI usage and the role of deliberate design in the utilization of AI for social impact. The AI for Good initiative at Smith envisions the implementation of ethically backed AI which can yield social and community impact.

Current Research Projects

The Dark Side of AI

This paper explores the issues of bias, fairness, transparency, and privacy issues related to artificial intelligence (AI) systems. The implications of the “black box phenomenon” and the non-explainability of AI outcomes are investigated. A set of guidelines is recommended for AI scholars and implementers to reduce the impact of its deleterious effects.

AI Trust

This paper investigates the factors which impact humans’ trust in Artificial Intelligent systems. Through focus group interviews of end-users of AI systems, this work uncovers the situational and behavioural factors which impact the trustworthiness of Artificial Intelligent systems. The paper’s findings are significant for designing and implementing more trustworthy AI systems.

AI and Social Enterprise

Artificial Intelligence’s unique scaling capacity makes it highly relevant to the aims of social enterprises addressing societal concerns. This research project uses qualitative interviews to analyze the major challenges faced by social entrepreneurs in using Artificial Intelligence to scale up their offerings. This work makes important contributions towards increasing the accessibility of AI to social enterprises.

MMA and MMAI Projects

Each year students of Master of Management in Analytics (MMA) and Master of Management in Artificial Intelligence (MMAI) work in a team-based format to develop projects intended to solve a social challenge using data analytics and artificial intelligence. The goal of this initiative is to assist students in developing a viable solution and prototype centred around AI for Good. Past projects have addressed traffic solutions in urban and rural communities, enhancing crop yields in developing countries, enhancing local food security as well as reduction of food waste, enhancing the processing needs of immigration pipelines, and scaling affordable housing for people experiencing homelessness.

Student Projects

Green Guide

In a world where our primary food sources are not sustainable, such as meat, our MMA Student Team designed a recommender system to provide sustainable ingredients and recipes to consumers that maintain an optimal nutritional profile and save users money. Green Guide can help improve the consumer's overall health and positively impact our planet.

Addressing Bias In Recruitment

Team Avenue has developed an in-depth evaluation process to monitor, measure, and address bias in the interview process for BIPOC individuals. Utilizing NLP modelling, Diversity Equity and Inclusion consultant, and sentiment/bias analysis, they train and empower hiring managers to reduce their bias during interviews and create a more vital, more inclusive organization.

Contributions & Impacts with the Kingston Tennis Club

Over the 2021 summer term, BCom’22 Rachel De Sousa held an Undergraduate Student Research Award (USRA) where, alongside Centre Director Ceren Kolsarici, she applied business methods and analytics to various challenges faced by the Kingston Tennis Club (KTC). Rachel left a lasting impact on KTC’s operations — read about her experience.

Early & Middle Stage Dementia Assistive Device

Early & Middle stage Dementia Assistive Device (EM-DAD) is a non-diagnostic assistive device that helps the patients locate and identify everyday objects and refresh knowledge of their use and meaning. The product targets no specific age group; instead targeting is assessed on the qualitative state of dementia, as directed by medical professionals. It is assumed that the users have some experience using smart devices.


The objective of AidBrain is to drive scalable assessment and management of cognitive health. The team’s solution uses sensory and motor fluctuations as biomarkers for Alzheimer’s disease. Their application uses AI to track eye movement, dexterity, and audio and engages users with gamification for early detection.