Dean Ball has a deep connection to American history through his family lineage in Virginia. His ancestors helped build the early economy of the state, and the town of Ballston is named after them. This history includes a direct link to George Washington through his mother, Mary Ball. Despite this prominent background, Dean notes that his family history does not function as an aristocracy. He grew up in a normal family and views his name as a source of personal responsibility rather than a claim to inherited wealth or status.

I do feel pride and a sense of legacy and also responsibility. My ancestors were people who helped build this country. They helped build the early economy of Virginia. And so I feel a sense of responsibility to keep the flame going.

Dean has built an extensive career in AI policy and political theory, including a stint at the White House Office of Science and Technology Policy. His work spans a wide range of topics from neurotech and bioengineering to criminal justice reform and public finance. For Dean, his background serves as a reminder to maintain the progress started by previous generations of his family.

Washington is an underrated center for intellectual life. Dean suggests that although high quality elected officials are harder to find due to party polarization, the world of political thinkers is vibrant. The shock of the first Trump administration forced intellectuals to build a new scaffolding for a movement that initially lacked a clear framework. This work continued during the Biden presidency. Dean believes this four year period away from power was healthy for conservative ideas. It allowed people to reflect on what went wrong and plan for the future.

I think the 4-year period between Trump 1 and Trump 2 was actually quite healthy for conservatives, the conservative world of ideas, because we were all kind of out in the wilderness for a while. And we had to reckon with the failures of Trump 1 and what went wrong. We had time to reflect.

Anna observes that people in the capital often complain about a lack of culture. However, she sees large groups of people gathering to discuss philosophy and deep social questions. New journals of ideas and organizations have launched recently between New York and D.C. In the field of AI, even small daily controversies quickly turn into debates about fundamental human issues. This happens because the technology is so new that there are no established rules yet.

D.C. in general, I kind of do think it is easy to underrate D.C.'s intellectual climate because so much of what you spend time talking about in D.C. is the controversies that accrete at the margin on politics and policy. Those things are often pretty vapid though in the world of AI, because everything is so nascent, the controversy du jour sort of inspires quite interesting debates.

We are living through a new Industrial Revolution that started 75 years ago with the transistor. Industrial revolutions take a long time to reach their peak. The previous one lasted about a century, from 1825 to 1925. During that time, the biggest changes happened in the final 25 years when inventions like electricity and the internal combustion engine converged. We are now entering a similar peak period with AI.

Industrial revolutions take a long time to peak. And I think we are approaching the beginning of the peak of it. We did not really experience the true shock of the new until the early 20th century. It was really that last 25 years when we really got hit with all of it.

AI is the biggest wave of this current revolution. It is the logical result of building the first computer. Every organization is now trying to figure out how to use this technology. There is a lot of uncertainty about who will have the power to shape these changes. We are moving toward a stage where we build computers to use other computers. This allows humans to step back and focus on different tasks.

AI is going to be the biggest wave of all. It is the apotheosis in many ways. But it is also not a wholly new thing. It is really just the logical endpoint of building a transistor in the first place. You build computers to use computers.

Europeans often rely on the precautionary principle when approaching new technology. This mindset suggests that the state must step in to define and ensure good outcomes. Without government intervention, the default assumption is that things will not go well. In contrast, Americans often distrust the state's ability to manage such transitions. They tend to believe the private sector should drive progress. There is also a specific American preoccupation with transformative AI. While European discussions often focus on narrow AI like facial recognition or loan processing, American companies like OpenAI aim for general intelligence.

Dean notes that the interest in superintelligence seems to be a uniquely Anglo preoccupation shared by the United States, Britain, Australia, and New Zealand. This focus might be rooted in history. The Industrial Revolution began in Britain even though other regions had the same material resources. This suggests a specific cultural feature was at play. AI development also has deep roots in signal processing and information theory from World War II. Pioneers like Alan Turing and Claude Shannon provided the foundations for modern language models.

Signal processing was also that piece of intellectual might that was so important in particular to British and American triumphs in World War II. You can go back and look at people like Alan Turing and Claude Shannon. These are the real foundational ideas behind AI and language modeling.

The culture inside specific companies determines how they build products. The most successful firms at the frontier of AI treat deep learning with a kind of religious conviction. They do not see it as a simple human invention. Instead, they view it as a fundamental discovery about nature. This belief leads to a fervor that distinguishes them from more traditional tech companies.

The companies that do best at the frontier of AI are the ones that have a religious conviction in deep learning as not an invention of man, but a discovery about nature. If you listen to any of the really AGI-pilled CEOs, they will consistently describe deep learning as a discovery.

This intensity is visible in corporate rituals. For example, a former scientist at OpenAI once burned an effigy to represent misaligned AI. This level of commitment is rare at companies like Meta where the focus is more on serving ads. The companies most committed to general intelligence often operate with a cult like fervor.

The classics used to be a reliable guide for understanding the present. In the past, reading about Napoleon or the Bible helped people understand military expansion and national morale. Today, this might not be possible. We are experiencing a shift in our mental model of the world that is entirely new. This mirrors the 1860s when society had to grapple with the realization that humans are animals descended from apes. There was nothing in previous traditions to help people deal with that discovery.

Dean points out that scientific breakthroughs often lead to new technologies. Newton's insights into gravity and force led to machines that used pulleys and levers. This era also embraced the idea that nature is something humans can change and control.

There's such an interesting relationship between really, really monumental scientific insights about the world and then the technology that inventors create.

Literature from the mid-19th to the early 20th century is especially rewarding because the authors knew they were living through a massive change. Unlike the very start of the Industrial Revolution, thinkers in this period realized their world was transforming forever. Writers like Marx, Dickens, and Dostoevsky used their work to process the impact of industrialization. They were trying to understand a world that was becoming unrecognizable.

Michael Oakeshott introduced a beautiful concept called the warmth of untidiness. The idea is that an untidy room feels like it belongs to you. While an austere and perfectly clean room can be pleasant, there is a specific happiness in a space that is messy in exactly the way you like. This concept helps define conservatism as a personal disposition rather than just a political ideology. It involves an intrinsic love of things for their own sake and a preference for the actual present over a hypothetical perfect future.

Dean explains that this disposition appears in many parts of life. For example, most people are conservative with their friends. A healthy friendship means appreciating someone for who they are right now rather than trying to change them. Anna notes that this perspective feels like making peace with reality. It suggests that if people are left to their own devices, they can figure things out and deal with challenges together through conversation.

This mindset leads to a specific view of government and classical liberalism. A person with a conservative disposition often has their own wild ambitions and skills to practice. They do not want the state to direct their lives. Instead, they want a government that provides clear rules and order so they can pursue their own dreams.

Such people know the value of a rule which imposes orderliness without directing enterprise, a rule which concentrates duty so that room is left for delight.

The goal of classical liberalism is not just economic growth. It is about creating a framework where there is room for delight. Human nature involves a constant tension between wanting to solve problems and wanting to appreciate the world as it is. Owning up to both sides is more realistic than trying to ignore one half of our nature.

The Pope is surrounded by a permanent staff of elites. In the Vatican, these elites function like European technocrats. Their influence appears in the Pope's recent encyclical on AI. This document reflects a European mentality that favors government management. It envisions a process where stakeholders determine how historical change unfolds. This approach treats innovation like a French garden where every hedge is perfectly trimmed. It stands in contrast to an English garden that grows more naturally.

Dean points out that this bureaucratic lean comes from Europe's early start in technology governance. A decade ago, the focus was on narrow machine learning like facial recognition or loan processing. This created a supply of lawyers and compliance professionals. Their business is to find problems that require regulatory solutions. They now see the world through this lens. Anna notes that many EU regulators moved from healthcare to digital policy. They bring a harm principle model to AI, treating it like dangerous medicine.

The Europeans, because they are so eager to regulate technology, they actually started thinking about what their AI governance regime would look like close to a decade ago. And a decade ago, no one was talking about general purpose AI. That was the era of narrow machine learning.

There is also a cultural dimension where AI is viewed through post-colonial theory. In this view, Silicon Valley is a colonizing force. Concepts like Artificial General Intelligence are treated as imperial constructs that must be deconstructed. The encyclical gained traction because AI safety groups lobbied the church to include their perspectives. Even today, it matters when the Pope writes 43,000 words about a new technology.

Choosing to speak honestly about public policy and technology often carries a significant professional and personal price. For those working at the intersection of government and AI, the expectation is often to be a repeat player. These people prioritize loyalty to secure future high-level roles. Rejecting this path in favor of being an honest writer means sacrificing future optionality. It means potentially closing doors at certain organizations. This independence can be baffling to those who view the world through a lens of strict loyalty.

If you become someone whose views are predictable or who ignores controversies because you don't want to offend your friends, people notice. You become a different kind of actor. I want to be someone where you know I'm trying to be honest, and I'm not in any particular person's camp.

The cost is not just professional. It is also personal. Publicly criticizing influential figures or organizations can result in being labeled an enemy. Dean describes a specific example of this friction involving Marc. Marc used a social media meme to blame Dean for a decline in American vigor. Being mocked by someone you once viewed as a hero is genuinely hurtful. However, it is a byproduct of choosing to show your true colors rather than maintaining strategic deniability for the sake of future collaboration.

The piano underwent a significant technological transformation during the life of Beethoven. Manufacturing moved from using wood to casting iron parts, which created a much stronger instrument. This shift happened rapidly between 1795 and 1815. Early instruments used by composers like Mozart or Haydn sounded thin, almost like guitars or harpsichords. Beethoven utilized the new industrial piano to create sounds that were previously impossible.

Beethoven is a very cool story of both manufacturing innovation and sonic innovation. One of his most complex sonatas, the Hammerklavier, is literally named for a technological innovation of the piano.

Dean notes that the manufacturers building these new tools could not have imagined the musical genius Beethoven would express through them. This relationship between technology and creativity serves as a model for the future of artificial intelligence. AI functions as a modern keyboard that expands the palette of human expression. It increases the precision with which people can communicate complex ideas.

I think that AI is a kind of keyboard that will massively expand the palette of human expression and increase our dynamic range. I hope that there are many young Beethovens out there who will do with AI what Beethoven did with the modern industrial piano.