Isabella Montoya-Bedoya

Isabella Montoya-Bedoya

Mentor

Dr. Amanda Phalin

College

Warrington College of Business

Major

Information Systems

Minor

Portuguese

Organizations

Latin American Women in Business, Heavener International Case Team, Women of Warrington, Florida Leadership Academy Advisory Board, University Minority Mentor Program

Academic Awards

Foreign Language and Area Studies Fellowship 2021-2022

Volunteering

N/A

Research Interests

Artificial Intelligence, Augmented Reality, Machine Learning Models, Cloud Technology, Cybersecurity in Business

Hobbies and Interests

Foreign Language Studies, Classical Music, Fictional Writing

Research Project

Detection and Impact of Bias in Machine Learning Algorithms

This research project will analyze the correlation between machine learning models and algorithmic bias in artificial intelligence systems. I will identify operational factors that lead to discriminatory outcomes in algorithms and propose solutions to detect and mitigate bias. Algorithmic bias is defined as systematic and repeatable errors in computer systems that deliver unfair outcomes and privileges to one arbitrary group of users over another. This bias can arise from a number of factors, including programming errors, data accessibility, and programmer bias. Lack of updated data or training can lead systems to unintentionally discriminate against certain groups of people. Models also have the possibility of operating on data produced from biased intentions and inequities. Due to the relatively new discovery of algorithmic bias, it is imperative that consequences of these bias algorithms are analyzed to ensure that discriminatory practices are eliminated from business operations. 

  • Dr. Amanda Phalin
  • Information Systems
  • Portuguese
  • Artificial Intelligence, Augmented Reality, Machine Learning Models, Cloud Technology, Cybersecurity in Business
  • Foreign Language and Area Studies Fellowship 2021-2022
  • Latin American Women in Business, Heavener International Case Team, Women of Warrington, Florida Leadership Academy Advisory Board, University Minority Mentor Program
  • N/A
  • Foreign Language Studies, Classical Music, Fictional Writing
  • Detection and Impact of Bias in Machine Learning Algorithms
  • This research project will analyze the correlation between machine learning models and algorithmic bias in artificial intelligence systems. I will identify operational factors that lead to discriminatory outcomes in algorithms and propose solutions to detect and mitigate bias. Algorithmic bias is defined as systematic and repeatable errors in computer systems that deliver unfair outcomes and privileges to one arbitrary group of users over another. This bias can arise from a number of factors, including programming errors, data accessibility, and programmer bias. Lack of updated data or training can lead systems to unintentionally discriminate against certain groups of people. Models also have the possibility of operating on data produced from biased intentions and inequities. Due to the relatively new discovery of algorithmic bias, it is imperative that consequences of these bias algorithms are analyzed to ensure that discriminatory practices are eliminated from business operations.