Artificial Intelligence 5 min read

Ethics and Bias in AI

As artificial intelligence integrates deeper into legal, hiring, and financial decisions, ethical concerns have taken center stage. Machine learning models learn from historical data, meaning they can absorb, amplify, and solidify human biases. This blog looks at the roots of algorithmic bias, challenges regarding training data privacy (e.g. copyrighted content and personal data scrapers), safety concerns in facial recognition systems, and the emerging field of Explainable AI (XAI) which seeks to make "black box" models transparent.