SMART Workshop: April 30-May 2, 2024
Hunter Kallay
Categorical Programming: How Kant might solve ethical bias and prevent AI-driven atrocities
This research explores the potential application of Kantian ethics in addressing the challenges of AI decision-making. The author, Hunter Kallay, argues that implementing two formulations of Kant’s categorical imperative as safeguards for foundational AI models could help solve issues of ethical bias and prevent AI-driven atrocities.
Sangmi Kim
Predicting Adolescent Suicidal Ideation: The Role of Physical Activity Evaluated Through Machine Learning Models
In this research, Sangmi Kim explores the factors influencing adolescent suicidal ideation, with a specific focus on the role of physical activity. The study aims to understand how cyberbullying, screen time, and physical activity impact suicidal thoughts among high school students in the United States.
M. Harshvardhan
End-to-End Inventory Prediction and Contract Allocation for Guaranteed Delivery Advertising
In the ever-evolving world of online advertising, Guaranteed Delivery (GD) Advertising has emerged as a strategic approach that allows advertisers to secure their desired inventory of advertising impressions in advance by signing contracts with publishers. This research, conducted by researchers at the University of Tennessee and the Alibaba Group, explores an innovative end-to-end solution for inventory prediction and contract allocation in GD Advertising.
Tyler Morris
Using a Social Robot and AI to Train Novice Dementia Caregivers
As the number of individuals diagnosed with Alzheimer’s Disease continues to rise, there is a growing need to support and train the increasing number of novice caregivers who are often unpaid family members or friends. Researchers from the University of Tennessee have developed an innovative approach to address this challenge by using a social robot and artificial intelligence (AI) to train novice dementia caregivers.