Abstract

Artificial intelligence (AI) algorithms are increasingly influencing decision-making processes across various domains. While AI offers undeniable benefits in efficiency and accuracy, its ethical implications necessitate careful consideration. This research paper delves into the ethical landscape of AI algorithms in decision-making. It explores how biases within training data can lead to discriminatory outcomes. The paper further examines the challenge of transparency in AI algorithms, where the rationale behind decisions remains opaque. To ensure responsible AI implementation, the research proposes strategies for mitigating bias and fostering transparency in AI-driven decisionmaking.