Anemia, Algorithms, and the Lost Art of Connection

Why liberal arts may win in an AI-driven world

When Algorithms Miss Something Important

Imagine an AI looking at lab results and identifying iron-deficiency anemia. It seems like a simple example of technology solving a real world problem. But what if the patient follows a specific cultural diet that doesn’t fit neatly with standard treatments? A human doctor who knows about these cultural nuances can suggest adjustments that the AI might miss.

These moments show why thinking broadly (while using insights from culture, history, and ethics) could become immensely valuable as AI takes over more tasks.

LLMs: Great Remixers, but Can They Create Insights?

Large language models (LLMs) are amazing at pulling together existing information. They can quickly mix and match ideas, but they often struggle to come up with truly new insights. Think of them like an advanced search engine: great at finding what’s already there, but not always aware when something important is missing.

People, especially those with broad backgrounds in the liberal arts, might be better at noticing these gaps and understanding why certain connections are important.

When Exploring Broadly Might Matter More

Connecting What Might Seem Unrelated

A historian who understands economics might notice how August tariffs on toys could impact holiday shopping months later. Making these connections takes intuition and broad knowledge.

Thinking About Ethics

Moral philosophers think about unexpected outcomes. When AI suggests policies based only on efficiency, it might accidentally overlook important human values or ethical considerations. This is why “AI alignment,” the process of ensuring AI matches human values, is so important.

Creativity in Art

Artists and writers often find inspiration in uncertain situations. They naturally explore contradictions and come up with fresh ideas that statistical models might not catch. For example, Studio Ghibli created a unique visual style, but when AI began remixing it, the style became repetitive. Human artists keep experimenting and pushing boundaries, so we don’t get bored.

When AI Might Miss Connections

Economics

🤖 AI sees: Higher toy prices in August due to tariffs

🧠 Human insight: Connects them to the Christmas manufacturing rush, affecting holiday inflation.

Urban Planning

🤖 AI sees: New bike lanes reducing traffic.

🧠 Human insight: Spots that the lanes overlap with annual festivals, temporarily increasing congestion.

Climate Policy

🤖 AI sees: Efficient carbon credit allocation.

🧠 Human insight: Considers local cooking habits that influence adoption of new technologies.

Product Design

🤖 AI sees: Negative reactions to UI changes.

🧠 Human insight: Reflects on how neurodiverse users experience the interface differently.

These examples show how data alone might miss important context.

Neurosymbolic AI: Could It Help?

Neurosymbolic AI combines deep learning with logic, potentially helping AI understand connections like how tariffs affect holiday prices. But even these systems need humans to help define what’s important. People skilled in seeing across different fields will remain essential.

What Does This Mean for Education and Jobs?

Students

📜 Past approach: Focus on a single specialty.

⚡️ Future with AI: Develop T‑shaped skills — deep expertise plus broad, interdisciplinary knowledge.

Employers

📜 Past approach: Hire narrow specialists.

⚡️ Future with AI: Build teams that mix specialists with connectors who understand wider contexts.

Universities

📜 Past approach: Operate in siloed departments.

⚡️ Future with AI: Encourage collaboration across disciplines.

Policy‑makers

📜 Past approach: Emphasize STEM funding almost exclusively.

⚡️ Future with AI: Integrate STEM with philosophy, ethics, and history to guide responsible innovation.

Becoming Someone Who Makes Connections

Stay Curious

Regularly explore subjects outside your main interests.

Use Analogies

When you learn something new, ask yourself: “What else does this remind me of?”

Question AI

Notice what the AI doesn’t mention and think about why.

Draw Connections

Sketch diagrams to visualize relationships that data alone might miss.

Practice Working With AI

Collaborate with AI tools, adding the context and connections they might overlook.

Final Thought

As AI continues to grow, the ability to think broadly and connect ideas might become more important than ever. Liberal arts education helps build exactly these skills: finding connections, filling gaps, and providing important context.

Data tells us what’s already happened, but stories and contexts help us imagine what could happen next.

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Originally published on 2025-07-19 on Medium.