Meet Raul Parihuana
Raul is an experienced QA Engineer and Web Developer with over three years in software testing and more than a year in web development. He has a strong background in agile methodologies and has worked with diverse companies, testing web, mobile, and smart TV applications. Raul excels at writing detailed test cases, reporting bugs, and has valuable experience in API and automation testing. Currently, he is expanding his skills at a company focused on artificial intelligence, contributing to innovative projects in the field.
Raul's Articles
Explainable AI and Transparency: Building Trust and Accountability in AI Systems
As artificial intelligence reshapes industries like healthcare and finance, a critical question emerges: How can we trust AI decisions? Enter…
Explainable AI in Fraud Detection: Enhancing Transparency and Trust in Identifying Fraudulent Activities
Imagine receiving an urgent alert that your credit card transaction was declined due to suspected fraud, but no one can…
Explainable AI Research Papers: Key Insights and Applications for Transparency in AI
Imagine a world where artificial intelligence makes crucial decisions affecting your healthcare, finances, and career opportunities without giving you any…
Explainable AI Algorithms: Unlocking Transparency and Interpretability in Machine Learning Models
Imagine trying to trust a decision that impacts your life, made by an AI system you can’t understand. As artificial…
Explainable AI for Decision-Making: Enhancing Transparency and Confidence in AI-Driven Choices
Imagine working alongside an AI system that influences critical decisions in healthcare, finances, or criminal justice, yet being unable to…
Explainable AI vs. Black Box Models: Understanding Transparency and Trust in AI
The battle between Explainable AI (XAI) and black box models represents a critical turning point in artificial intelligence. While black…