What does it mean for an AI to be curious?
Not curious in the romantic sense of wondering at the stars. Not the child’s persistent “why” that drives parents to exhaustion. I mean something more specific: the computational pressure to seek information that isn’t currently possessed but might matter.
Persuasion is ancient. Aristotle catalogued its forms: ethos (credibility), pathos (emotion), logos (logic). Cicero refined the art. Every culture has developed sophisticated traditions for moving minds: rhetoric, preaching, advertising, therapy, teaching.
The oracle at Delphi spoke in riddles. Cassandra knew the future but no one believed her. Tiresias paid for foresight with blindness. Every culture has stories about the burden of knowing what comes next.
What would it mean to study AI the way anthropologists study humans?
The question contains a trap. It assumes AI should be measured against human categories, as if the goal were replication, as if “artificial general intelligence” meant artificial human intelligence, as if the destination were minds like ours running on different hardware.
We’re building millions of AI agents.
Not just chatbots responding to human queries, but autonomous systems that act in the world: booking appointments, executing trades, managing infrastructure, coordinating logistics, negotiating on behalf of users. Each with some degree of autonomy. Each interacting not just with humans but with other AI agents.
You’re buying a car. Not you personally, your AI agent is buying a car on your behalf. It knows your budget, your preferences, your constraints. It’s been authorized to negotiate, to commit, to close the deal.