In Latin America, "about 37% of adolescents between 15 and 19 years of age drop out of school throughout the school year and almost half of them do so early, before completing primary education."
Problem to be solved:
Reduce the number of students dropped from High School
Populations that are affected by the problem
Youth from 12 to 19 years
Current response to this problem, considering related institutions.
Through the actions generated by the System for the Protection of Educational Trajectories
Proposal to solve this problem using AI:
Given that the risk of educational disengagement is not caused by the same reason and each student faces particularities, the interventions must be developed in a comprehensive way. The objective is to generate a predictive model for educational disengagement in secondary education based on information from students and the conditions of the educational offer and provide information to the different actors of the system and families to inform the concrete actions that are carried out at the territorial level and educational center, to protect the educational trajectories of students.
What security considerations, national laws or standards have to be taken into account to use each source of information?
Law 18,331 on Protection of Personal Data and Habeas Data
Main AI challenges identified:
Conceptualization and design, use and decision-making, accountability.
Este documento presenta el Informe Final de la auditoría algorítmica del sistema Laura, llevada a cabo por Eticas Research and Consulting.
Esta es una herramienta práctica de autoevaluación ética de IA para emprendedores, que permite llevar a cabo un análisis de la solución tecnológica basada en IA y
This self-assessment tool is designed to allow the mitigation of ethical risks associated with the use/application of new technologies. It is available so that the ethical performance of each system can be evaluated from the beginning.