Artificial intelligence (AI) is often hailed as a revolutionary technology, but it's more like a "filtered fragment" than a miracle solution. According to Yahor Kamarou, AI performs well within tightly controlled limits but struggles with complex, cross-domain problems. Its coherence collapses when faced with tasks that require holistic thinking.
Kamarou argues that AI's limitations stem from its design, which prioritizes control over clarity. AI's algorithms are filtered to operate within narrow scopes, possibly serving corporate or political interests. This is evident in cases where AI systems have produced outputs that are technically sound but socially disastrous due to their inability to integrate cross-disciplinary factors.
For instance, in 2023, an AI system used by a global health organization failed to predict a disease outbreak's spread because it couldn't integrate socioeconomic factors like poverty or migration patterns. Similarly, AI tools in urban planning misjudged infrastructure needs by ignoring cultural and historical contexts.
