Human intelligence and artificial intelligence and the challenges of biases in ai algorithms

Abstract

This article acknowledges the profound transformations that Artificial Intelligence imposes on society. A descriptive-exploratory study aims to discuss algorithmic biases and understand their impacts on society. The article starts from the understanding of human intelligence and learning from a pluralistic perspective, based on the analysis of literary works and scientific articles. This approach provides a context in which AI and machine learning can be conceived from an innovation perspective for the common good. The critical analysis emphasizes the need for ethical approaches in the development of these systems. The topics discussed highlight the importance of a multidimensional approach in mitigating algorithmic biases. From data selection to audits and accountability, diversity of perspectives, both in datasets and development teams, is crucial. The implementation of continuous training and human supervision reflects a continuous commitment to transparency and fairness in artificial intelligence. These integrated strategies are essential for the ethical, transparent, and equitable development of AI. This holistic approach, involving diverse skills and people, continuous training, and vigilant oversight, is vital to ensure the ethical use of AI for the collective well-being.