Abstract
Artificial Intelligence (AI) is penetrating all the domains worldwide and healthcare is no exception. Due to the huge amount of returns on investment in the AI systems developed for healthcare, a huge amount of investments are underway. Though big leaps in the application of healthcare cannot be ignored, the application of AI specifically in mission-critical domains like healthcare must be handled with care. This paper provides insights into the possible inherent biases, unfairness and inequality of the AI algorithms. The concerns related to data quality and training datasets. The inherent bias could be due to numerous reasons that are hidden preferences or unrepresented/incomplete datasets.
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Verma, P., Kushwaha, H., Singh, H. (2023). Artificial Intelligence in Healthcare: Inherent Biases and Concerns. In: Yadav, D.K., Gulati, A. (eds) Artificial Intelligence and Machine Learning in Healthcare. Springer, Singapore. https://doi.org/10.1007/978-981-99-6472-7_12
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DOI: https://doi.org/10.1007/978-981-99-6472-7_12
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