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5. Ng, A. (2017). Machine Learning Yearning. Draft in progress. Retrieved from https://www.deeplearning.ai/machine-learning-yearning/
6. Russell, S. J., & Norvig, P. (2010). Artificial intelligence: A modern approach. Prentice Hall.
7. Shetty, P., & Adjeroh, D. (2018). Intelligent data analysis: A survey of the state-of-the-art. Journal of Big Data, 5(1), 42.
8. Thrun, S., & Mitchell, T. M. (2019). Machine learning and the future of education. Science, 363(6423), 1279-1282.
9. World Economic Forum. (2018). Future of Jobs Report 2018. Retrieved from https://www.weforum.org/reports/the-future-of-jobs-report-2018
10. Liang, Z., Li, F., Zhang, Y., Huang, C., & Chen, C. (2017). A deep learning framework for financial time series using stacked autoencoders and long-short term memory. PloS one, 12(7), e0180944.
11. Tapscott, D., & Tapscott, A. (2016). Blockchain revolution: How the technology behind bitcoin is changing money, business, and the world. Penguin.
12. Malik, A. (2019). Ethical and Social Challenges of AI: A survey of the current state-of-the-art. arxiv preprint arXiv:1906.04358.
13. Brynjolfsson, E., & Mitchell, T. (2017). What can machine learning do? Workforce implications. Science, 358(6370), 1530-1534.
14. Yiu, C. S., & Law, R. (2018). Artificial intelligence in tourism and hospitality: a review of the literature. In Information and Communication Technologies in Tourism 2018.
1. Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton & Company.
2. Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116.
3. Kshetri, N. (2018). Will blockchain emerge as a tool to break the poverty chain in the Global South?. Third World Quarterly, 39(11), 2189-2211.
4. Li, Y., Liang, X., Li, J., & Zheng, X. (2018). Artificial intelligence in healthcare: past, present and future. Seminars in cancer biology, 52, 10-16.