Shivaraj
Computer Science
June 2024
This study examines how data science and artificial intelligence (AI) interface with ethical issues, with a particular emphasis on responsibility, justice, and bias. It starts with a brief historical review, highlighting the development of data science and artificial intelligence while highlighting the significance of ethical issues in modern technology. After that, the paper explores the complex topic of bias, looking at its definitions, typologies, and effects on judgment. This article examines fairness in AI systems, discussing its foundations, difficulties, and evaluation criteria. Examining the definition of stakeholder responsibility as well as the legal and ethical ramifications, the topic of accountability is examined. There are case studies that show how to successfully integrate ethics, as well as frameworks, guidelines, and other practical approaches for handling ethical issues. This study adds to the conversation around ethical technology development by advising interested parties to proceed with caution regarding any potential ethical ramifications.
565- 577
© Airo Journals 2021
