AI Governance: Challenges of Bias, Censorship, and Alignment
Artificial Intelligence (AI) has profoundly transformed from a largely experimental technology into an essential infrastructure that underpins economic, political, and social life. The pervasive integration of large language models (LLMs) across diverse domains—including healthcare, education, cybersecurity, and entertainment—underscores their increasing criticality. However, this proliferation is accompanied by growing concerns surrounding fairness, accountability, and the alignment of these powerful models with fundamental human values. Current debates in AI governance are predominantly shaped by three interconnected challenges. The first is algorithmic bias , which manifests when AI systems reproduce and amplify existing societal prejudices. This bias can originate from skewed or unrepresentative training data, as well as from the architectural design of the models themselves. The consequences are significant, as biased algorithms can undermine equity, perpetuate discrimination, and...