Bias in the Machine: AI’s Stereotype Problem

AI Mirrors Society’s Flaws

A new MIT Technology Review report reveals that large AI models continue to replicate and even reinforce harmful gender and racial stereotypes. Researchers found that state-of-the-art systems like OpenAI’s GPT and Meta’s LLaMA favor biased representations in their output, particularly when asked to generate images or descriptions. These learned biases reflect the data on which the models were trained—hugely influenced by societal norms, internet content, and developer decisions. Despite efforts to filter out problematic content, baked-in prejudice continues to surface in AI-generated results.

A New Era of Accessible Coding

Meanwhile, AI is sparking a quiet revolution in how software is built. With new tools like GitHub Copilot and ChatGPT, non-programmers and casual developers alike are writing code faster and more efficiently than ever. This democratization of software development is drastically reducing entry barriers, enabling more people to automate tasks, build digital tools, and even launch startups. As AI takes on more of the coding workload, human roles in software creation could shift toward design, strategy, and problem framing.