Ethical Considerations in AI and Ml: Bias Detection and Mitigation Strategies

Authors

  • Vineet Dhanawat

Keywords:

Mitigation Strategies

Abstract

The bias of AI is used when the application of machine learning can expand out of its ethical use in the machine learning platform. The evaluation of these biases is important to discuss for the proper use of AI in different platforms. In this paper, the data that are provided to the AI is properly enhanced so that the bias is used for the detection of proper data, and it is also noticed if the data that is provided in the system is properly trained to get better results out of the system. There are some proper strategies that are used to mitigate AI in machine learning platforms and deliver proper algorithms to the system. There are teams associated with multi-disciplinary streams that help provide proper algorithms to the machine using AI and machine learning systems. The policies of ethical practices should be considered when applying the proper use of AI and machine learning to develop proper algorithms that could be provided to the system.

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Published

2023-08-17

How to Cite

Vineet Dhanawat. (2023). Ethical Considerations in AI and Ml: Bias Detection and Mitigation Strategies. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 2(3), 61–65. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/67