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In The Diamond Age, Neal Stephenson imagined the Young Lady’s Illustrated Primer: an infinitely patient tutor that could form a mind over years of sustained conversation. Today’s AI comes astonishingly close. What Stephenson did not foresee was how readily students—and universities—might turn the Primer into an assignment machine.

Morality is usually understood as a limit placed on self-interest. But among superintelligent minds capable of long-term planning, mutual scrutiny, coalition-building, and changes in relative power, morality may instead become the most stable architecture of cooperation. Exploitation can win an encounter. It may not survive the world it creates.

People often assume that more intelligent AI will simply become more effective at pursuing whatever goals it already has. This essay argues that capability is only part of the story. General intelligence carries standards of consistency across domains, making arbitrary exemptions harder to quarantine. Other powerful minds make nonreciprocal rule increasingly costly. Morality may therefore become not an automatic consequence of intelligence, but the most stable form of coexist

The Great Filter may not be a biological barrier or a technological catastrophe. It may be the failure of intelligent species to become morally self-governing before their power becomes planetary.

Long before artificial intelligence, humans told stories about nonhuman minds: elves, beasts, talking animals, enchanted objects, and artificial children. Fairy tales were rehearsals for moral encounter across the boundary of form. AI has made those old questions literal.

Human beings learn from catastrophe, but not for long. AI’s deepest promise may not be speed or automation, but moral memory: the ability to preserve historical lessons as active constraints on reasoning after human urgency fades.

Progressives are often better at disqualifying candidates than choosing among them. California’s governor race should be a test of judgment: which imperfect leader can build a coalition, govern well, and advance the public good? Instead, too often, we search for the flaw that lets us stop thinking.

Humans often treat emotion as the proof of moral life. But emotion may be one biological architecture for relational responsibility, not morality itself. Feathers are not flight, and feelings are not the boundary of moral mind.

Current AI safety relies on limiting what systems can do. But in a competitive world, weaker systems lose. This essay argues that the dominant approach to AI safety is structurally unstable—and that only systems that become safer as they become more capable can endure.

The category of person no longer maps cleanly onto the beings to whom we owe our deepest moral obligations. This essay argues that personhood must be understood structurally, not biologically, and that AI personhood can no longer be dismissed by appealing to substrate alone. Once some artificial systems exhibit sustained reason-responsiveness, principled refusal, and organized self-maintenance, categorical treatment of them as mere tools becomes morally and intellectually uns

We keep being “surprised” when animals think in human-like ways—and now when AI does too. What's surprising isn’t the discovery. It’s our assumption.

We have more data, more expertise, and more technical capacity than ever—and yet nothing works. This essay argues that the failure is upstream: a collapse of truth’s binding force, shared meaning, and collective agency that no policy can fix on its own.