[Spanish only] How we address risks, bias and accountability in Responsible AI

Artificial Intelligence is rapidly transforming society, but its adoption also introduces new challenges for organizations. In this episode, we explore what Responsible AI really means, focusing on key aspects such as risks, bias and the implications of delegating decisions to automated systems.

Through expert insights, we examine the main challenges associated with AI, including hidden errors, algorithmic bias, and the role of regulation, ethics and corporate responsibility. We also explain how AI systems work and why they do not truly “understand” the world, but instead detect patterns from data, which can sometimes lead to unexpected outcomes.

In this context, we discuss how organizations can address these challenges through governance, control and oversight frameworks that ensure a more secure, transparent and human-centric use of AI. We also reflect on a critical aspect: accountability when AI fails and the importance of defining clear responsibility models in increasingly automated environments.

A podcast episode to better understand the role of Responsible AI today and how to move towards more trustworthy, ethical and sustainable technology.