Leveraging Artificial Intelligence to increase STEM Graduates Among Underrepresented Populations

Leveraging Artificial Intelligence to increase STEM Graduates Among Underrepresented Populations

Bibliographic Details
Main Author: Riep, Josette R.
Language:English
Published: University of Cincinnati / OhioLINK 2021
Subjects:
Artificial Intelligence
Machine Learning
African American
Bias
Classification and regression trees
STEM
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627663323829372
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spelling ndltd-OhioLink-oai-etd.ohiolink.edu-ucin16276633238293722021-10-16T05:25:21Z Leveraging Artificial Intelligence to increase STEM Graduates Among Underrepresented Populations Riep, Josette R. Artificial Intelligence Artificial Intelligence Machine Learning African American Bias Classification and regression trees STEM STEM remains one of the fastest-growing and most segregated professions in the United States. Predominately white and male, opportunities in STEM continue to grow exponentially. For example, areas such as the Internet of Things (IoT) and Artificial Intelligence (AI) are expected to become $11 trillion industries by 2025.As companies struggle to find enough skilled candidates, we face the reality that African Americans are too often left behind. If we, for example, examine technology as a subset of STEM, we see that African Americans make up less than 5% of the IT workforce and a small percentage of IT graduates. Although there is a general acknowledgment and some investment by both industry and educational institutions, there has been minimal success in changing the demographic landscape. This study focuses on the advent of bias-conscious AI and how it can be used to better understand barriers to success, personalize student experiences, and provide pathways of attainment for an increasingly diverse student body. 2021-10-05 English text University of Cincinnati / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627663323829372 http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627663323829372 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection NDLTD
language English
sources NDLTD
topic Artificial Intelligence
Artificial Intelligence
Machine Learning
African American
Bias
Classification and regression trees
STEM
spellingShingle Artificial Intelligence
Artificial Intelligence
Machine Learning
African American
Bias
Classification and regression trees
STEM
Riep, Josette R.
Leveraging Artificial Intelligence to increase STEM Graduates Among Underrepresented Populations
author Riep, Josette R.
author_facet Riep, Josette R.
author_sort Riep, Josette R.
title Leveraging Artificial Intelligence to increase STEM Graduates Among Underrepresented Populations
title_short Leveraging Artificial Intelligence to increase STEM Graduates Among Underrepresented Populations
title_full Leveraging Artificial Intelligence to increase STEM Graduates Among Underrepresented Populations
title_fullStr Leveraging Artificial Intelligence to increase STEM Graduates Among Underrepresented Populations
title_full_unstemmed Leveraging Artificial Intelligence to increase STEM Graduates Among Underrepresented Populations
title_sort leveraging artificial intelligence to increase stem graduates among underrepresented populations
publisher University of Cincinnati / OhioLINK
publishDate 2021
url http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627663323829372
work_keys_str_mv AT riepjosetter leveragingartificialintelligencetoincreasestemgraduatesamongunderrepresentedpopulations
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