Abstract
Data science is reshaping our world in ways we never experienced before. This transformation carries an enormous potential to improve mental health care and patient assessment. However, it is not only data gathering that is increasing at a high velocity, but also relevant ethical issues derived from its ownership, analysis, and impact in our lives. In this chapter, we review potential applications of big data analytics and associated dilemmas that may arise from it. We start by discussing issues linked to data itself, involving ownership, privacy, transparency, and reliability. Then, we proceed to discuss what may happen following data processing, and the implementation of predictive models = in real scenarios, focusing on the implications for clinicians, scientists, and patients. We highlight that while it is necessary to develop more strict regulations for handling sensitive data, we must also pay attention to the problem of overregulation, which could create unnecessary obstacles for data science and slow down the potential benefits it may have in our society.
To appear in Ives Passos, Benson Mwangi, and Flávio Kapczinski (Eds.) Personalized and Predictive Psychiatry - Big Data Analytics in Mental Health. NY: Springer Nature.
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Librenza-Garcia, D. (2019). Ethics in the Era of Big Data. In: Passos, I., Mwangi, B., Kapczinski, F. (eds) Personalized Psychiatry. Springer, Cham. https://doi.org/10.1007/978-3-030-03553-2_9
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