Tech Needs Humanists More

The piece argues that as AI takes over fact retrieval and formulaic writing, the competitive advantage for technologists and tech writers will come from humanistic training: deep thinking, clear stances, and the ability to convey and defend ideas. Rather than prioritizing another technical trade or language of code, the recommendation is to study philosophy, literature, linguistics, history, anthropology, mathematics or classics, and to learn spoken languages. These disciplines supply conceptual tools - philosophy of mind and science, computational linguistics, logic and ontology - that underlie current AI systems and software design, and they cultivate rapid learning, system-level thinking, and attention to human factors that boilerplate skills do not.

Concrete outcomes and practices follow: read proposals closely to detect poor reasoning, separate evidence from inference, build arguments that survive disagreement, spot reinvented wheels, question AI outputs, design human-centered information architectures, and explain idea-driven product problems. Examples include UX borrowing from the arts and anthropology, clinical-psychology-informed projects like NOPE for safer AI, and logic informing database and information models. Learning other languages is presented as a method to absorb different worldviews and broaden problem‑solving. The overall call is to become a flexible, culture-translating humanist in tech able to navigate conceptual roots as effectively as technical stacks.