Author: Shahriar Akter, Grace McCarthy, Shahriar Sajib, Katina Michael, Yogesh Dwivedi, John D’Ambra; Publisher: International Journal of Information Management; Publication Year: 2021. The following paper provided a thorough framework for algorithmic biases in data driven…
Author: Sean Michael Kerner; Publisher: VentureBeat; Publication Year: 2022. The following article discusses how when labeling data for modeling and machine learning, the person labeling the data can accidently introduce bias to the models. This…
Author: Sarah E. Bon, Nyasha Junior; Publisher: Hyperallergic; Publication Year: 2020. The following article explores the use of artificial intelligence (AI) and machine learning in artistic research and reconstructions. Specifically, the authors explore the hidden…
Author: Rik Chomko; Publisher: Forbes; Publication Year: 2022. The following article describes how, from an equity standpoint, artificial intelligence (AI) transparency is vital for preventing bias that has the potential to penalize protected classes or…
Author: Prabhakar Krishnamurthy; Publisher: Medium; Publication Year: 2019. The following article discusses how most datasets suffer from bias which can affect conclusions drawn from the data in a way that is discriminatory. This paper describes…