Thesis Abstract

Abstract
The integration of artificial intelligence (AI) technologies into decision-making processes has raised significant ethical concerns in various fields. This thesis delves into the complexities surrounding the ethical implications of AI in decision-making processes. The study begins by introducing the concept of AI and its increasing prevalence in contemporary society. It then provides a comprehensive background of the study by exploring the evolution of AI technologies and their impact on decision-making processes. The problem statement highlights the ethical dilemmas posed by AI algorithms in decision-making, including issues of bias, transparency, accountability, and the potential erosion of human autonomy. The objectives of the study are to critically analyze the ethical considerations of AI in decision-making, identify key challenges and opportunities, and propose ethical frameworks to guide the responsible development and deployment of AI technologies. Acknowledging the limitations of the study in addressing the vast and evolving landscape of AI ethics, the scope is defined to focus on specific aspects such as algorithmic bias, explainability, and human oversight in decision-making systems. The significance of the study lies in its contribution to the ongoing discourse on AI ethics and its implications for societal well-being, individual rights, and organizational practices. The structure of the thesis is outlined, detailing the organization of chapters and sub-sections that will guide the reader through the research journey. Definitions of key terms related to AI ethics are provided to ensure clarity and understanding of the terminology used throughout the thesis. The literature review in Chapter Two critically examines existing research on AI ethics, decision-making processes, algorithmic bias, transparency, and accountability. Ten key themes are identified and analyzed to provide a comprehensive overview of the current state of knowledge in the field. Chapter Three presents the research methodology, including the research design, data collection methods, sampling techniques, and data analysis procedures. Eight content areas are explored to ensure a rigorous and systematic approach to investigating the ethical implications of AI in decision-making processes. Chapter Four delves into the discussion of findings, presenting the analysis of empirical data and theoretical insights. The ethical challenges and opportunities of AI in decision-making are examined, and potential strategies for addressing these challenges are proposed. Finally, Chapter Five offers a conclusion and summary of the thesis, highlighting the key findings, implications, and recommendations for future research and practice in the field of AI ethics and decision-making processes. The thesis concludes with reflections on the broader implications of AI ethics for society, technology, and human well-being.

Thesis Overview