Category: Uncategorized
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From Models to Meaning: Interpreting, Trusting, and Governing AI Systems
As AI systems grow more capable, a paradox emerges: performance improves while human understanding often declines. Large models achieve remarkable accuracy, yet their internal reasoning remains opaque. This gap between capability and interpretability is one of the defining challenges of contemporary AI. Interpretability is frequently misunderstood as a technical add-on—an afterthought applied once a model…
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Machine Learning Across Disciplines: How Domain Knowledge Shapes Intelligent Systems
Machine learning is often presented as domain-agnostic: a set of universal algorithms applicable wherever data exists. In practice, however, domain knowledge is a decisive factor in determining whether a machine learning system is merely functional or genuinely useful. At a conceptual level, machine learning algorithms optimize mathematical objectives defined over data. Yet the formulation of…
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Artificial Intelligence as a General-Purpose Technology: Foundations, Trajectories, and Societal Integration
Artificial intelligence should be understood not merely as a collection of algorithms, but as a general-purpose technology—comparable in scope and impact to electricity, the internet, or the internal combustion engine. Its defining characteristic is not task specificity, but its capacity to reshape multiple sectors simultaneously through learning, adaptation, and decision-making under uncertainty. At its core,…