Abstract
Recent innovations performed on data analytics technologies within the last two decades have steered towards a new level of data-driven decision-making in different industries. This chapter elucidates the significant aspects of data privacy with ethics under the dominion of data analytics. Firstly, the chapter details how imperative is protecting an individual's personal information. Secondly, discusses the legal frameworks, namely, GDPR (General Data Protection Regulation) and different data protection laws around the world, which have greatly influenced for bringing awareness on data privacy. Thirdly, how ethical considerations do compliment the outcome when these regulations are complied with. Finally, this chapter also offers information on how the organizations and its professionals must meticulously put efforts towards building a world on how to handle data ethically. In this regard, the chapter provides various instances from projects, case studies and real-world scenarios to support and discuss how data analytics do create positive and negative impacts amongst an individual and the society. To conclude, this chapter focuses on the vital aspects of mixing data privacy and ethics when working with data analytics. Furthermore, how organizations can follow holistic approaches wherein a blend of technology safety, legal frameworks and ethical awareness can be infused into their work culture when their employees are dealing with data in various projects in the future.
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References
Bhageshpur K: Data Is the New Oil—And That’s A Good Thing. Forbes Technology Council
Bibri, S.E., Alexandre, A., Sharifi, A., Krogstie, J.: Environmentally sustainable smart cities and their converging AI, IoT, and big data technologies and solutions: an integrated approach to an extensive literature review. Energy Infor. 6(9), 32 (2023)
Christen, M., Gordijn, B., Loi, M.: The ethics of cybersecurity. In: International Library of Ethics, Law and Technology, pp. 1–8. Springer Science and Business Media B.V (2020)
Gellert, R.: Data protection law and responsible data science. In: Data Science for Entrepreneurship. pp. 413–439. Springer, Cham (2023)
Gomathi, L., Mishra, A.K., Tyagi, A.K.: Industry 5.0 for healthcare 5.0: Opportunities, challenges and future research possibilities. In: 7th International Conference on Trends in Electronics and Informatics, ICOEI 2023—Proceedings, pp. 204–213. Institute of Electrical and Electronics Engineers Inc. (2023)
Grace, J.: Exploring algorithmic justice for policing data analytics in the United Kingdom. In: Privacy, Technology, and the Criminal Process, pp. 18–38. Taylor and Francis (2023)
Hassani, H., Silva, E.S.: The role of chatgpt in data science: How AI-assisted conversational interfaces are revolutionizing the field. Big Data and Cognitive Comput. 7, (2023) https://doi.org/10.3390/bdcc7020062
Jain, P., Gyanchandani, M., Khare, N.: Enhanced secured map reduce layer for big data privacy and security. J Big Data. 6, (2019). https://doi.org/10.1186/s40537-019-0193-4
Jiang, R., Bouridane, A., Li, C.T., Crookes, D., Boussakta, S., Hao, F., Edirisinghe, E.A.: Big Data Privacy and Security in Smart Cities. Springer, Cham (2022)
Kaufmann, U.H., Tan, A.B.C.: Why data analytics is important? In: Data Analytics for Organisational Development. pp. 1–20. John Wiley & Sons (2021)
Ma, Z., Clausen, A., Lin, Y., Jørgensen, B.N.: An overview of digitalization for the building-to-grid ecosystem. An Overview of Digitalization for the Building-to-Grid Ecosystem. Energy Inform. 4 (Suppl. 2), Article 36 (2021). https://doi.org/10.1186/s42162-021-00156-6
Mühlhoff, R., Willem, T.: Social media advertising for clinical studies: Ethical and data protection implications of online targeting. Big Data Soc. 10 (2023). https://doi.org/10.1177/20539517231156127
Mühlhoff, R.: Predictive privacy: Towards an applied ethics of data analytics. Ethics Inf. Technol. 23, 675–690 (2021). https://doi.org/10.1007/s10676-021-09606-x
Myers, N.E., Kogan, G.: Emerging AI and data analytics tooling and disciplines. In: Self-service data analytics and governance for managers, pp. 25–49. John Wiley & Sons, Inc (2021)
Nevaranta, M., Lempinen, K., Erkki, K.: Students’ perceptions about data safety and ethics in learning analytics (2020).
O’Regan, G.: Ethics and privacy. In: Concise Guide to Software Engineering. Springer, Cham (2022)
O’Regan, G.: Introduction to data science. In: Mathematical Foundations of Software Engineering, pp. 385–398. Springer, Cham (2023)
Papadogiannakis, E., Papadopoulos, P., Kourtellis, N., Markatos, E.P.: User tracking in the post-cookie era: How websites bypass gdpr consent to track users. In: WWW ’21: Proceedings of the Web Conference 2021, pp. 2130–2141. Creative Commons Attribution 4.0 International (2021)
Shah, S.I.H., Peristeras, V., Magnisalis, I.: DaLiF: A data lifecycle framework for data-driven governments. J Big Data. 8 (2021). https://doi.org/10.1186/s40537-021-00481-3
Shukla, S., George, J.P., Tiwari, K., Varghese Kureethara, J.: Data privacy. In: Data Ethics and Challenges, pp. 17–39. Springer, Singapore (2022)
Subramanian, R.: Have the cake and eat it too: Differential privacy enables privacy and precise analytics. https://doi.org/10.21203/rs.3.rs-1847248/v1 (2022)
The world’s most valuable resource is no longer oil, but data, https://www.economist.com/leaders/2017/05/06/the-worlds-most-valuable-resource-is-no-longer-oil-but-data
Trunk, A., Birkel, H., Hartmann, E919: On the current state of combining human and artificial intelligence for strategic organizational decision making. Bus. Res. 13, 875 (2020). https://doi.org/10.1007/s40685-020-00133-x
Wylde, V., Rawindaran, N., Lawrence, J., Balasubramanian, R., Prakash, E., Jayal, A., Khan, I., Hewage, C., Platts, J.: Cybersecurity, data privacy and blockchain: A review. SN Computer Sci. 3 (2022). https://doi.org/10.1007/s42979-022-01020-4
Zambas, M., Illarionova, A., Christou, N., Dionysiou, I.: Exploring user attitude towards personal data privacy and data privacy economy. In: Proceedings of the Second International Conference on Innovations in Computing Research (ICR’23), pp. 237–244. Springer, Cham (2023)
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Rajasegar R. S., Gouthaman P., Vijayakumar Ponnusamy, Arivazhagan N., Nallarasan V. (2024). Data Privacy and Ethics in Data Analytics. In: Singh, P., Mishra, A.R., Garg, P. (eds) Data Analytics and Machine Learning. Studies in Big Data, vol 145. Springer, Singapore. https://doi.org/10.1007/978-981-97-0448-4_10
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