An Investigation of Algorithmic Bias in AI-Based University Admissions Systems: A Case Study of Federal Polytechnic, Bauchi (Bauchi LGA, Bauchi State)
- Project Research
- 1-5 Chapters
- Abstract : Available
- Table of Content: Available
- Reference Style:
- Recommended for :
- NGN 5000
Background of the Study
Artificial intelligence (AI) is increasingly being used in university admissions to automate the process of selecting applicants based on predefined criteria. AI-based systems are designed to streamline admissions, increase efficiency, and reduce human bias. However, there is growing concern about the presence of algorithmic bias in these systems, which could lead to unfair outcomes. Algorithmic bias refers to the systematic favoritism or discrimination built into AI models, often due to biased data or flawed algorithms. This issue can perpetuate inequalities in admissions, affecting underrepresented groups and disadvantaging certain applicants.
Federal Polytechnic, Bauchi, located in Bauchi LGA, Bauchi State, has implemented an AI-based admissions system, but concerns about the fairness and impartiality of the selection process remain. This study aims to investigate the potential for algorithmic bias in the university's AI-based admissions system, analyzing whether certain groups of applicants are unfairly favored or disadvantaged. By addressing this issue, the study seeks to provide recommendations for improving the fairness and transparency of AI-driven admissions processes.
Statement of the Problem
The use of AI in admissions at Federal Polytechnic, Bauchi, has raised concerns about algorithmic bias in the selection process. There is limited research on whether the AI-based system used at the institution is inadvertently favoring certain demographic groups over others, potentially leading to discriminatory practices. This study seeks to investigate the presence of algorithmic bias in the admissions system and its implications for fairness and equity in university admissions.
Objectives of the Study
1. To identify and analyze potential algorithmic biases in the AI-based admissions system at Federal Polytechnic, Bauchi.
2. To assess the impact of algorithmic bias on the fairness and transparency of the admissions process.
3. To propose strategies for mitigating algorithmic bias in the AI-based admissions system.
Research Questions
1. Does the AI-based admissions system at Federal Polytechnic, Bauchi exhibit any form of algorithmic bias?
2. How does algorithmic bias, if present, impact the fairness of the admissions process?
3. What measures can be taken to reduce or eliminate algorithmic bias in the university's AI-based admissions system?
Research Hypotheses
1. The AI-based admissions system at Federal Polytechnic, Bauchi exhibits algorithmic bias, favoring certain demographic groups over others.
2. Algorithmic bias in the admissions system negatively affects the fairness and transparency of the selection process.
3. Implementing fairness-enhancing strategies will reduce algorithmic bias and improve the impartiality of the AI-based admissions system.
Significance of the Study
This study will contribute to the understanding of algorithmic bias in AI-based systems used for university admissions. The findings will help Federal Polytechnic, Bauchi, identify and address potential biases in its admissions process, promoting fairness and equity. The research will also provide insights into best practices for designing unbiased AI systems in educational settings, which could be applied to other institutions across Nigeria and beyond.
Scope and Limitations of the Study
This study will focus on investigating algorithmic bias in the AI-based admissions system at Federal Polytechnic, Bauchi, located in Bauchi LGA, Bauchi State. The research will analyze the system's fairness but will not examine other AI-based systems used in different areas of university administration. The study will be limited to identifying biases in the admissions algorithm and will not involve redesigning the system.
Definitions of Terms
• Algorithmic Bias: The presence of systematic errors or discrimination in an algorithm that leads to unfair or unequal outcomes.
• AI-Based Admissions System: A system that uses artificial intelligence to automate the university admissions process by selecting candidates based on predefined criteria.
• Fairness: The principle of treating all applicants equally, without discrimination or favoritism, based on factors such as gender, ethnicity, or socioeconomic status.
• Transparency: The extent to which the decision-making process of an algorithm can be understood and audited.
Related Project Materials
The Impact of Radio Programming on Promoting Child Education: A Study of Mubi North Local Government Area, Adamawa State
Background of the Study
Radio is one of the most accessible forms of media in many rural Nigerian communities, providing...
An Examination of the Relationship Between Energy Consumption and Economic Output in Nigeria
Background of the Study
Energy consumption is widely regarded as a fundamental driver of economic output....
ESTIMATION OF PATIENT RADIATION DOSES FOR SELECTED X-RAY EXAMINATIONS AND CENTRES IN NORTH-CENTRAL, NIGERIA
ABSTRACT
The risk of occurrence of cancer in developed and developing nations has become a major concern in the scientific and medical ci...
IMPACT OF CORPORATE SOCIAL RESPONSIBILITY ON COMMUNITY DEVELOPMENT
BACKGROUND OF THE STUDY
Academics and practitioners have been striving to establish and agreed upon definitions of the c...
DESIGN AND IMPLEMENTATION OF A COMPUTER BASED INFORMATION SYSTEM FOR THE PROJECTION OF STUDENT’S ENROLMENT IN UNIVERSITIES
INTRODUCTION
The project work deals on computer based planning information system for the projection of...
The influence of early childhood exposure to science activities on later STEM achievement in Katsina LGA, Katsina State
Background of the Study
Early childhood exposure to science activities is believed to have a lasting impact on childr...
An appraisal of fraud prevention measures on bank security: a case study of First City Monument Bank
Background of the Study
Fraud prevention is a cornerstone of bank security, critical for protecting assets, maintaining cu...
DESIGN AND IMPLEMENTATION OF MOBILE APPLICATION RESULT CHECKER
ABSTRACT
In this project work, we present a way to bring information to students by leveraging the availability of p...
An Assessment of How HRM Contributes to Organizational Change Management: A Study of Dangote Sugar Refinery in Gombe State
Background of the Study
Human Resource Management (HRM) plays a vital role in managing organizational change, as employe...
The Effectiveness of Road Safety Campaign Advertisements in Misau LGA, Bauchi State
Chapter One: Introduction
1.1 Background of the Study
Road safety is a critical issue in Nigeria, with high rates of traffic ac...
