Why Curiosity Matters More Than Credentials [Newsletter #84]

Hello, AI enthusiasts from around the world.

Welcome to this week’s newsletter for the AI and the Future of Work podcast.

For centuries, universities sat at the center of education and professional growth. Entire learning systems formed around them. That structure is now under pressure.

AI is driving this shift. Memorizing answers matters less. Asking better questions matters more.

This change reaches beyond academia. It shapes how we learn, how we work, and how we make decisions about our lives.

Let’s dive into this week’s highlights! 🚀

🎙️ New podcast episode with Lynn Thoman, Professor at Columbia University and 3 Takeaways Podcast host

Academia is facing a period of disruption. For many people, that creates discomfort.

AI is reshaping how learning happens, and education looks very different now than it did even a few years ago. Longstanding systems are under pressure to change, and not every institution will adapt at the same pace.

For decades, people built entire careers around the degree they earned. That path once felt essential. Today, it holds less weight.

Lynn Thoman sees this shift as an opportunity. It’s a chance to elevate one of the most human skills education can help develop: curiosity.

Lynn is a professor at Columbia University School of International and Public Affairs and host of 3 Takeaways, a Top 1% global podcast known for distilling big ideas into practical insight.

At Columbia, she teaches leaders how to scale social impact and build effective public-private partnerships. On her podcast, she hosts conversations with global decision-makers about how ideas shape leadership, work, and society.

Her work keeps her close to the changing role of academia. In her conversation with Dan Turchin, Lynn explains how AI creates space for humans to lean into curiosity. AI already handles tasks like summarizing research, analyzing data, and drafting reports.

As those capabilities expand, skills rooted in memorization and static knowledge matter less. What matters more is how we think, question, and explore what comes next.

In this conversation, we explore these ideas and more:

• Why the most useful way to understand AI is as an amplifier of human capability. This becomes clear in leadership, where judgment and decision-making matter more than any tool.

• What preparing students for an AI-shaped job market looks like when education emphasizes learning paths, adaptability, and relationships over fixed career tracks.

• The hidden risks inside AI systems. Small shifts in data or models can create downstream harm that is difficult to detect or undo.

• How AI is pulling education, work, and leadership back toward core human skills such as judgment, curiosity, and imagination.

• Why AI’s greatest upside lies in expanding access to knowledge, health, and opportunity—not in replacing human intelligence.

🎧 This week’s episode of AI and the Future of Work features Lynn Thoman, Professor at Columbia University and host of the 3 Takeaways podcast.

Listen to the full episode to hear why Lynn views AI’s growing role in academia as a constructive shift for the future of thinking and shared learning.

📖 AI Fun Fact Article

Republicans and Democrats often hold opposing views on many topics. According to Pew Research Center researchers Monica Anderson and William Bishop, both sides now share similar concerns about AI in daily life.

Members of both parties report feeling both concerned and excited about increased AI use. Around 10% of each group say they feel more excitement than concern.

The data shows a clear shift. In 2021, Republicans were more likely than Democrats to say they felt concerned about AI’s growing role in daily life. Since 2023, the share of Republicans who express concern has dropped by nine percentage points.

Democrats show the opposite trend. In 2021, 31% expressed concern about AI’s role in daily life. That figure rose to 46% in 2023 and reached 51% in 2025.

The result is a political impasse. Some advocates push for stricter AI regulation. Others warn that aggressive rules could slow innovation.

California recently became the first state to regulate chatbots, adding momentum to the broader debate around AI governance.

Public trust remains divided. About 44% of Americans say they trust the U.S. government at least somewhat to regulate AI effectively. By contrast, 47% say they have little to no trust in its ability to do so.

Most Americans also report higher trust in the European Union to regulate AI than in China.

PeopleReign CEO Dan Turchin reminds us that governments have a responsibility to protect the welfare of citizens. Unfortunately, as with many aspects of modern society, AI safety has become politicized.

Political parties are an artifact of a different moment in history, when ideological debates were more civil and grounded in principles rather than personal interests. Today, political polarization and a zero-sum approach to nearly every issue make it difficult for citizens to entrust AI regulation to governments.

In the U.S., there is no agreement on who should regulate AI, whether states or the federal government, nor on what should be regulated. What is clear is that bureaucrats often lack the technical understanding, and at times the motivation, to regulate AI for the right reasons.

Similar challenges have slowed progress in the EU and beyond. Still, a small but growing group of researchers and executives is working to create frameworks that allow AI labs and vendors to self-report their progress using balanced scorecards of risk factors.

Let’s celebrate and support those efforts. Responsible AI requires collective action, and this is an important moment.

📽️ Worth a Watch

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Special Podcast Episode

Until Next Time: Stay Curious 🤔

👋 That's a Wrap for This Week!

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