Artificial Intelligence and Biases

Predicting Adolescent Pregnancy in Salta

Authors

DOI:

https://doi.org/10.52712/issn.1850-0013-359

Keywords:

artificial intelligence, machine learning algorithm, biases, value neutrality, public policies

Abstract

Faced with the rhetoric of an efficient and free of prejudice artificial intelligence (AI), this article discusses why this popular vision is inadequate and examines some of its shifts in the design of public policies. Firstly, we argue that it is impossible –in principle– to propose a value-neutral AI, based on what has been indicated by some canonical and contemporary philosophical contributions. In the second section we analyze a case that clearly illustrates the value burden that gravitates on AI. This will lead us to investigate, in the third section, the different levels at which biases can have an influence on AI. Our main objective is to unveil the paradox related to how the application of AI in public policies and private spheres, far from being a tool to combat structural inequalities, ends up consolidating harmful scenarios for vulnerable populations.

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Author Biographies

Karina Pedace, Universidad Nacional de La Matanza

Associate professor at the National University of La Matanza (UNLAM), head of practical works at the University of Buenos Aires (UBA) and researcher at IIF-SADAF-CONICET, Argentina.

Tobías Schleider, Universidad Nacional del Sur

Professor and researcher at the National Southern University (UNS) and head of practical works at the National University of Mar del Plata (UNMDP), Argentina. Researcher at UNMDP, UNS and the Latin American Institute for Security and Democracy (ILSED).

Tomás Balmaceda, Universidad de Buenos Aires

Head of practical works at the University of Buenos Aires (UBA), Argentina. Associate professor at the University of Business and Social Sciences (UCES), Argentina. Researcher at IIF-SADAF-CONICET, Argentina.

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Published

2022-12-26

How to Cite

Pedace, K., Schleider, T., & Balmaceda, T. (2022). Artificial Intelligence and Biases: Predicting Adolescent Pregnancy in Salta. Revista Iberoamericana De Ciencia, Tecnología Y Sociedad - CTS (Ibero-American Science, Technology and Society Journal), 18(53), 9–26. https://doi.org/10.52712/issn.1850-0013-359

Issue

Vol. 18 No. 53 (2023)

Section

Articles

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