Can We Trust AI?
AI is evolving rapidly — from LLMs and multimodal models to breakthroughs in healthcare, robotics, and traffic systems. Yet ethical hurdles persist: bias, transparency, privacy, accountability, and misuse. While tools like XAI, federated learning, and fairness metrics offer promise, implementing them at scale remains complex. Moving forward, global cooperation, regulation, and inclusive design are key to building trustworthy, responsible AI that aligns with human values and ensures equitable impact across societies. AI — The Fastest Moving Frontier in Tech Large language models (LLMs) like GPT-4 and multimodal models handling text, images, and audio have significantly improved, enabling more natural human-AI interactions and content creation. Additionally, efforts to address the “black box” problem have grown, with Explainable AI (XAI) enhancing transparency in AI decision-making to reduce bias and build trust, particularly in healthcare and justice. AI is transforming diagnostics,...
