The concept of AGI is so ill-defined it becomes a catch-all for magical thinking, both utopian and dystopian. Casado argues it erodes the quality of discourse by preventing focus on concrete, solvable problems and measurable technological progress.
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Today's AI models have surpassed the definition of Artificial General Intelligence (AGI) that was commonly accepted by AI researchers just over a decade ago. The debate continues because the goalposts for what constitutes "true" AGI have been moved.
OpenAI's CEO believes the term "AGI" is ill-defined and its milestone may have passed without fanfare. He proposes focusing on "superintelligence" instead, defining it as an AI that can outperform the best human at complex roles like CEO or president, creating a clearer, more impactful threshold.
The popular concept of AGI as a static, all-knowing entity is flawed. A more realistic and powerful model is one analogous to a 'super intelligent 15-year-old'—a system with a foundational capacity for rapid, continual learning. Deployment would involve this AI learning on the job, not arriving with complete knowledge.
The hype around an imminent Artificial General Intelligence (AGI) event is fading among top AI practitioners. The consensus is shifting to a "Goldilocks scenario" where AI provides massive productivity gains as a synergistic tool, with true AGI still at least a decade away.
Instead of trying to legally define and ban 'superintelligence,' a more practical approach is to prohibit specific, catastrophic outcomes like overthrowing the government. This shifts the burden of proof to AI developers, forcing them to demonstrate their systems cannot cause these predefined harms, sidestepping definitional debates.
The definition of AGI is a moving goalpost. Scott Wu argues that today's AI meets the standards that would have been considered AGI a decade ago. As technology automates tasks, human work simply moves to a higher level of abstraction, making percentage-based definitions of AGI flawed.
Cutting through abstract definitions, Quora CEO Adam D'Angelo offers a practical benchmark for AGI: an AI that can perform any job a typical human can do remotely. This anchors the concept to tangible economic impact, providing a more useful milestone than philosophical debates on consciousness.
The discourse around AGI is caught in a paradox. Either it is already emerging, in which case it's less a cataclysmic event and more an incremental software improvement, or it remains a perpetually receding future goal. This captures the tension between the hype of superhuman intelligence and the reality of software development.
The AI debate is becoming polarized as influencers and politicians present subjective beliefs with high conviction, treating them as non-negotiable facts. This hinders balanced, logic-based conversations. It is crucial to distinguish testable beliefs from objective truths to foster productive dialogue about AI's future.
The race to manage AGI is hampered by a philosophical problem: there's no consensus definition for what it is. We might dismiss true AGI's outputs as "hallucinations" because they don't fit our current framework, making it impossible to know when the threshold from advanced AI to true general intelligence has actually been crossed.
