The AGI Debate: Are We Five Years Away or Fifty?

At a dinner in San Francisco in early 2026, four of the most prominent AI researchers in the world sat around a table and were asked the same question: "When will we achieve artificial general intelligence?" Their answers spanned five decades: from "we're basically there" to "not in my lifetime." They all had PhDs. They all had access to the same research. They fundamentally disagreed about the most important question in their field.

The AGI timeline debate isn't just academic. It drives billions in investment, shapes government policy, and determines whether the public treats AI with appropriate urgency or premature panic. Getting the timeline wrong in either direction has consequences.

The first problem is definitional. AGI: artificial general intelligence: is loosely defined as AI that can perform any intellectual task a human can. But what counts?

The narrow definition: AGI can autonomously perform any job a human does, including learning new skills it wasn't trained for. By this standard, we're nowhere close.

The broad definition: AGI can match or exceed human performance on a wide range of cognitive tasks, even if it can't do everything. By this standard, GPT-4 is already closer than many expected.

The economic definition (used by OpenAI): AGI is "AI that can do the work of a senior engineer." This conveniently makes AGI a goalpost that OpenAI can plausibly claim to approach.

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