The answer is hinted at, and often buried under the dire prognostications of AGI doomers, but findings have shown that human-AI augmentation, not replacement, not human job preservation, but humans using AI as cognitive scaffolding outperforms all human, and all AI teams. While it wasn’t on every task, a significant meta-study of AI augmentation found that AI augmentation was a significant enhancement in the efficacy of creation tasks, just not decision tasks.[21] Early market signals are absolutely both definitive, and daunting.[22][23] The market has identified and is pivoting towards AI native skills. Yet, this recognition has caused an intriguing downstream effect: the market is now struggling to identify, recruit, onboard, and retain AI talent in particular, but not AI talent alone.[24]
The dire prognostication of AGI doomers meant the AGIs which have yet to be created. When you wrote this, the humans did excel at tasks like long-term planning, few-shot learning of new information and deeply integrating it into world models, which lets the humans augment current-state AIs. A hypothetical AGI is a system which would excel even at these tasks. How does a human-AGI centaur outperform the AGI-AGI “centaur” which can be created artificially and cloned in an infinite amount?
The dire prognostication of AGI doomers meant the AGIs which have yet to be created. When you wrote this, the humans did excel at tasks like long-term planning, few-shot learning of new information and deeply integrating it into world models, which lets the humans augment current-state AIs. A hypothetical AGI is a system which would excel even at these tasks. How does a human-AGI centaur outperform the AGI-AGI “centaur” which can be created artificially and cloned in an infinite amount?