Abstract
Artificial Intelligence is a popular concept amongst academics and business professionals these days. It is increasingly omnipresent in every aspect of our life, such as voice assistance, automated customer service and semi-automated driving experiences. Even with such advancements, it is important to recognize that AI is not capable of predicting our future exactly. Rather, we should view AI as a complementary tool which enables us to replace dated existing processes and improve our ways of living via automated learning. To start with, a comparison between Narrow & General AI and the interpretability of existing AI will be discussed. Additionally, the complex and non-trivial discussion between model generalization and overfitting will also be covered. We will also cover the importance of good data quality and provide a list of recommended but non-exhaustive best practices in data preparation. Finally, we end off by summarizing current developments in the issue of data privacy.
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Yang, Y.(., Akbarzadeh Khorshidi, H., Aickelin, U. (2022). Limitations. In: Raz, M., Nguyen, T.C., Loh, E. (eds) Artificial Intelligence in Medicine. Springer, Singapore. https://doi.org/10.1007/978-981-19-1223-8_9
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DOI: https://doi.org/10.1007/978-981-19-1223-8_9
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