Affiliation:
1. Central University of Kerala, India
Abstract
The history of artificial intelligence (AI) and data science has their origins in the 1940s and 1950s respectively. However, it has been through many changes throughout its history. AI is a vast and fascinating subject. There are many more elements to discover and understand. This chapter aims to outline the history of AI and data science, from its origin to its current developments. It will also explore the ethical considerations within AI and data science, such as bias and fairness, transparency, data privacy, etc. In the end, the chapter sheds light on the ethical concerns regarding the implementation of AI and the security concerns that data science poses. The chapter also provides insights into the role of individuals, government, and society in mitigating these issues. This chapter aims to furnish the reader with the scientific foundation and essential understanding required for embarking on the journey to comprehend the realm of artificial intelligence and data science.
Reference45 articles.
1. Abbasi-Sureshjani, S., Raumanns, R., Michels, B., Schouten, G., & Cheplygina, V. (2020). Risk of Training Diagnostic Algorithms on Data with Demographic Bias. Interpretable and Annotation-Efficient Learning for Medical Image Computing: Third International Workshop, iMIMIC 2020. Springer International Publishing.
2. A survey on data‐efficient algorithms in big data era
3. Agarwal, A., Gans, J., & Goldfarb, A. (2016, December 21). The Obama Administration’s Roadmap for AI Policy. Harvard Business Review. https://hbr.org/2016/12/the-obama-administrations-roadmap-for-ai-policy
4. Algorithmic Bias in Education.;R.Baker;International Journal of Artificial Intelligence in Education,2021
5. Cao, L. (2017). Data Science: A Comprehensive Overview. ACM Computing Surveys (CSUR), 50(3), 1-42.