Why does AI-written language feel meaningful—even when no meaning was intended? In this episode of AnthroIntelligence: Culture, Cognition, and Code, I draw a sharp line between human language as a symbolic, cultural system and AI language as an algorithmic process of prediction.

Humans use words to mean—to refer, intend, and share understanding within a lived social world. Large language models, by contrast, generate fluent text by detecting patterns in data, not by participating in meaning. When we confuse algorithmic fluency with symbolic thought, we misunderstand both AI and ourselves.

This episode explores why machines can sound thoughtful without thinking—and why the real marvel is not artificial intelligence, but the depth and structure of human symbolic culture that makes such imitation possible.

#AnthroIntelligence #HumanLanguage #ArtificialIntelligence #SymbolsAndAlgorithms #Anthropology #SymbolicAnthropology #CultureAndTechnology #Semiotics

Why does AI feel authoritative—even when we know it’s just a machine? In this episode of AnthroIntelligence: Culture, Cognition, and Code, I turn to anthropology to explain a quiet but dangerous confusion at the heart of our AI moment. Artificial intelligence works on tokens—units of prediction without belief—but humans increasingly treat its outputs as totems: sources of meaning, trust, and authority.

From students seeking life advice at 2 a.m. to institutions deferring judgment to algorithms, this episode explores how fluency becomes mistaken for wisdom, and prediction for truth. The real risk of AI is not intelligence run amok—but our willingness to surrender interpretation, responsibility, and belief.

#AnthroIntelligence #AIandCulture #HumanInterpretation #AIEthics #Anthropology #CultureAndTechnology #PsychologicalAnthropology #SymbolicAnthropology

Is AI really “end-to-end”—or is that just a comforting illusion? In this episode of AnthroIntelligence: Culture, Cognition, and Code, I unpack a simple but overlooked truth: every AI workflow still begins and ends with a human being. From defining the task and setting boundaries to interpreting consequences and carrying accountability, humans remain the anchors of every so-called automated system.

AI may accelerate the middle—the pattern-finding, the drafting, the prediction—but meaning, purpose, and judgment never leave human hands. The real risk isn’t that machines will turn into Skynet. It’s that we forget how deeply these systems still depend on us.

#AnthroIntelligence #AIPhilippines #AIethics #CultureAndTechnology #HumanCenteredAI