News — Bias in AI RSS

The Unseen Hand: How Biases in Technology Reinforcement Learning Shape Our World Reinforcement learning (RL) is the driving force behind many cutting-edge technologies, from self-driving cars to personalized recommendations. It's a powerful tool that allows machines to learn through trial and error, optimizing their actions to achieve specific goals. But there's a dark side to this seemingly objective learning process: bias. Just like humans, RL algorithms are susceptible to biases, often reflecting the prejudices present in the data they are trained on. These biases can have profound consequences, shaping our interactions with technology and perpetuating existing societal inequalities. Where do these biases come from? Data reflects reality: RL algorithms learn from massive datasets, which inevitably contain human-created biases stemming from...

The Unseen Bias: How Technology Can Perpetuate Discrimination We live in an age where technology promises to solve our problems, automate our lives, and even predict our futures. But behind the sleek interfaces and complex algorithms lie hidden dangers: discriminatory outcomes. While technology itself is neutral, it's built by humans, trained on data reflecting existing societal biases, and used in ways that can amplify inequalities. The Data Dilemma: AI algorithms learn from the data they are fed. If this data reflects historical prejudices, the algorithm will inevitably perpetuate them. For example, facial recognition software has been shown to be less accurate at identifying people of color, leading to potential misidentification and discrimination in law enforcement. Similarly, hiring algorithms trained on...