All Outputs (2)

Measuring AI Fairness in a Continuum Maintaining Nuances: A Robustness Case Study (2024)
Journal Article
Paxton, K., Aslansefat, K., Thakker, D., & Papadopoulos, Y. (2024). Measuring AI Fairness in a Continuum Maintaining Nuances: A Robustness Case Study. IEEE Internet Computing, 28(5), 11-19. https://doi.org/10.1109/MIC.2024.3450815

As machine learning is increasingly making decisions about hiring or healthcare, we want AI to treat ethnic and socioeconomic groups fairly. Fairness is currently measured by comparing the average accuracy of reasoning across groups. We argue that im... Read More about Measuring AI Fairness in a Continuum Maintaining Nuances: A Robustness Case Study.

Creating a Classification Module to Analysis the Usage of Mobile Health Apps (2022)
Journal Article
Azuma, K., Al Jaber, T., & Gordon, N. (2022). Creating a Classification Module to Analysis the Usage of Mobile Health Apps. Acta Scientific Computer Sciences, 4(12), 34-42

With an ageing society becoming a major issue for many countries, health-related concerns are growing and mobile health applications (MHAs) are rapidly gaining users. The applications available range from those that promote exercise to maintain healt... Read More about Creating a Classification Module to Analysis the Usage of Mobile Health Apps.