Navigating the Ethical Landscape: A Pythonic Approach to AI Ethics and Fairness

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Kamel Alikhan Siddiqui, Mateen Ahmed ,Khutaija Abid, Syed Juber


As the use of Artificial Intelligence (AI) becomes increasingly prevalent in coding practices, there is a pressing need for developers to align their work with ethical considerations and fairness principles. This abstract explores the critical aspects of AI Ethics and Fairness in the context of Python coding, emphasizing the importance of responsible AI development. The discussion begins with an overview of transparency and accountability, highlighting how Python developers can incorporate clear documentation and responsible coding practices to enhance the transparency of their AI algorithms. Emphasis is placed on the role of comments, documentation, and version control in fostering a transparent development process. The abstract then delves into the concept of fairness, illustrating how Python coding can inadvertently introduce biases and discrimination. Strategies to identify and mitigate biases in Python-based AI models are presented, with an emphasis on diverse and representative datasets, fairness metrics, and algorithmic adjustments.

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