La privacidad en el uso de los datos en la Ciencia de Datos

Aravena Nina, Dilcia Kelly and Tapia Quispe, Higuey Edson La privacidad en el uso de los datos en la Ciencia de Datos., 2022 Bachelor's Degree thesis, Universidad Peruana de Ciencias Aplicadas. [Thesis]

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English abstract

The purpose of the research is to contrast the authors' positions on who is responsible for data privacy in data science, given that it is not clear, since it allows identifying the responsible actors who must manage the use of data, valuing the right to privacy that people have. The study has a qualitative approach that seeks to analyze the arguments of the authors, whose academic scope of consulted references correspond to scientific articles indexed in journals of quartiles 1 and 2. As a result, it is identified that algorithms are increasingly used to analyze large complex data sets in order to generate knowledge from the data, such as: discovering behavior patterns, knowing if someone is hired or promoted, if someone accesses a loan or is provided with housing, etc. (Martin, 2019; Someh et al., 2019). The findings show that data science can affect the stakeholders, these are: the owners who contribute their data, the companies that use Big Data, the builders that develop the algorithms, the State institutions that regulate the use of data and the societies that have the responsibility to govern, control and shape this changing socio-technical phenomenon, among other actors. Likewise, the research establishes a shared responsibility between the aforementioned interest group and all those who may be affected by the analysis of their data in data science.

Spanish abstract

La investigación tiene como propósito contrastar las posturas de los autores sobre quién es el responsable de la privacidad de los datos en la ciencia de datos, dado que no está clara, ya que permite identificar a los actores responsables que deben gestionar el uso de los datos, valorando el derecho a la privacidad que tienen las personas. El estudio es de enfoque cualitativo que busca analizar los argumentos de los autores, cuyo alcance académico de referencias consultadas corresponden a artículos científicos indexados a revistas de cuartiles 1 y 2. Como resultado, se identifica que, cada vez más se usan los algoritmos para analizar grandes conjuntos de datos complejos con el fin de generar conocimientos a partir de los datos, como es: descubrir patrones de comportamientos, saber si alguien es contratado o promovido, si alguien accede a un préstamo o es provisto de vivienda, etc. (martín, 2019; Someh et al., 2019). Los hallazgos demuestran que la ciencia de datos puede afectar a las partes interesadas, estos son: los propietarios que contribuyen con sus datos, las empresas que usan Big Data, los constructores que desarrollan los algoritmos, las instituciones del Estado que regulan el uso de los datos y las sociedades que tienen la responsabilidad de gobernar, controlar y dar forma a este fenómeno sociotécnico cambiante, entre otros actores. Asimismo, la investigación establece una responsabilidad compartida entre el grupo de interés antes mencionado y todos aquellos que pueden verse afectado por el análisis de sus datos en la ciencia de datos.

Item type: Thesis (UNSPECIFIED)
Keywords: Data Analysis; Privacy; Big Data; Data Science
Subjects: B. Information use and sociology of information > BC. Information in society.
G. Industry, profession and education. > GB. Software industry.
H. Information sources, supports, channels. > HL. Databases and database Networking.
I. Information treatment for information services > IE. Data and metadata structures.
I. Information treatment for information services > IM. Open data
K. Housing technologies. > KG. Safety.
L. Information technology and library technology > LC. Internet, including WWW.
L. Information technology and library technology > LN. Data base management systems.
L. Information technology and library technology > LP. Intelligent agents.
Depositing user: Lic. Adriana Mora Natera
Date deposited: 12 Aug 2023 09:17
Last modified: 12 Aug 2023 09:17
URI: http://hdl.handle.net/10760/44268

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