The Lost Humanistic Foundation of Computing

The article "Humanities in the Machine" by Blain Smith presents a compelling historical argument that the most profound contributions to computing emerged not from pure technical expertise, but from minds deeply informed by the humanities. This observation challenges the contemporary separation between technical and humanistic disciplines, suggesting that the very essence of computing was born from their intersection.

The historical pattern revealed through the lives of computing pioneers is striking. Tony Hoare, creator of Quicksort and Hoare logic, studied Classics and Philosophy at Oxford before encountering computing. His approach to programming as a formal system with correctness as an intellectual virtue rather than merely an engineering goal reflects this philosophical training. Similarly, Ada Lovelace's "poetical science"—her refusal to separate analytical from imaginative thinking—allowed her to envision machines that could manipulate symbolic systems beyond mere calculation, a conceptual leap that founded modern computing.

Edsger Dijkstra's classical education in Greek and Latin, combined with his early ambition to study law, shaped his view of programming as a mental activity demanding clarity of thought. His famous EWD manuscripts were not technical reports but essays, demonstrating how his classical training influenced his communication style and his belief that programming required precision of expression as a moral obligation. Grace Hopper's broad Vassar education exposed her to diverse disciplines beyond mathematics and physics, leading to her humanistic insight that programming languages should speak to people in English rather than mathematical symbols—a perspective that gave us FLOW-MATIC and COBOL.

Even figures with primarily technical educations like Dennis Ritchie and Brian Kernighan benefited from environments that valued cross-disciplinary thinking. Ritchie, though his education was purely technical, was shaped by Bell Labs' extraordinary intellectual culture where physicists, mathematicians, linguists, and engineers collaborated. Kernighan, in the latter part of his career, actively sought connections between computing and the humanities, teaching courses for literature students and exploring data in the humanities.

The article traces a worrying trajectory: as computing matured, the influence of the humanities diminished. While early pioneers were steeped in philosophical thinking and classical education, later generations had less exposure to these traditions. By the time we reach contemporary technology leaders, the humanities influence has "thinned to almost nothing" in their formal education.

This separation has had tangible consequences. Modern technology systems demonstrate "technical sophistication and humanistic bankruptcy." Social media platforms optimized for engagement without understanding their psychological impact. Algorithms that shape billions of people's information diets are designed by teams lacking training in ethics, epistemology, or the philosophy of information. The result is technology that functions efficiently but often fails to serve human needs or consider human consequences.

The article provocatively suggests that this humanities deficit explains why modern technology can predict what you want to buy but cannot determine whether showing teenagers endless curated suffering is appropriate. AI models trained on the breadth of human knowledge are deployed by people who have never seriously considered the responsibilities that come with such power.

What makes this argument particularly compelling is its demonstration that humanities thinking was not merely decorative for early computing pioneers but fundamental to their breakthroughs. Lovelace's insight that machines could manipulate symbolic systems came from her "poetical" perspective. Hopper's human-centered approach to programming languages emerged from her understanding of how people actually think and communicate. Dijkstra's belief in clarity as a moral obligation reflected classical values of expression.

The article wisely avoids suggesting that every programmer needs a philosophy degree or that studying Latin will improve coding skills. Instead, it emphasizes the importance of disposition—the concern for clarity that extends beyond code, the awareness that systems exist within larger human contexts, and the willingness to ask not just "does it work" but "is it good."

This humanistic disposition requires more than casual weekend reading of philosophy. It demands "serious, sustained time with literature, with history, with ethics, with the long conversation that humanity has been having with itself for thousands of years." Such engagement fundamentally changes how problems are perceived, what questions are asked, and what solutions are considered acceptable.

The article concludes with a call to action for technical professionals to re-engage with the humanities, not as an academic requirement but as a personal choice that can reshape approach to work. It suggests that the tradition that produced Lovelace's poetical science and Hoare's classical mind is "not dead. But it is diminishing, generation by generation." The challenge is to reverse this trend by recognizing that "building machines worthy of human trust requires understanding what it means to be human."

This analysis reminds us that technology is never neutral—it embodies the values, assumptions, and blind spots of its creators. As computing continues to permeate every aspect of human life, the need for creators who understand both the technical and human dimensions of their work becomes increasingly urgent. The article's historical perspective suggests that this integration is not only possible but has been the foundation upon which computing was originally built.