Ethical Implications of Bias in Machine Learning
Date
2018-01-03
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Abstract
Biases in AI and machine learning algorithms are presented and analyzed through two issues management frameworks with the aim of showing how ethical problems and dilemmas can evolve. While "the singularity" concept in AI is presently more predictive than actual, both benefits and damage that can result by failure to consider biases in the design and development of AI. Inclusivity and stakeholder awareness regarding potential ethical risks and issues need to be identified during the design of AI algorithms to ensure that the most vulnerable in societies are protected from harm.
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Topics in Organizational Systems and Technology, AI and Ethics, Machine Learning and Ethics
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8 pages
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Proceedings of the 51st Hawaii International Conference on System Sciences
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Table of Contents
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Attribution-NonCommercial-NoDerivatives 4.0 International
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