Former OpenAI scientist Andrej Karpathy posits that once AGI handles most cognitive tasks, education will shift from a professional necessity to a personal pursuit. Similar to how people visit gyms for health and enjoyment despite machines handling heavy labor, learning will become an optional activity for fulfillment.
OpenAI co-founder Ilya Sutskever suggests the path to AGI is not creating a pre-trained, all-knowing model, but an AI that can learn any task as effectively as a human. This reframes the challenge from knowledge transfer to creating a universal learning algorithm, impacting how such systems would be deployed.
Like chess players who still compete despite AI's dominance, humans will continue practicing skills like writing or design even when AI is better. The fear that AI will make human skill obsolete misses the point. The intrinsic motivation comes from the journey of improvement and the act of creation itself.
The popular conception of AGI as a pre-trained system that knows everything is flawed. A more realistic and powerful goal is an AI with a human-like ability for continual learning. This system wouldn't be deployed as a finished product, but as a 'super-intelligent 15-year-old' that learns and adapts to specific roles.
Adopting the philosophy of 'building for dying' (向死而生), the founder views his AI product not just for current productivity, but as a future 'playground.' In a world where AI automates most jobs, the product's purpose will shift to providing fulfillment and the pleasure of 'pretend work.'
As the traditional employer-employee social contract breaks and AI automates cognitive tasks, individuals can no longer rely on physical or mental effort for their value. This shift compels a deeper search for purpose and what makes us uniquely human: our soul and self-awareness.
Companies like OpenAI and Anthropic are spending billions creating simulated enterprise apps (RL gyms) where human experts train AI models on complex tasks. This has created a new, rapidly growing "AI trainer" job category, but its ultimate purpose is to automate those same expert roles.
ASU's president argues that if an AI can answer an assignment, the assignment has failed. The educator's role must evolve to use AI to 'up the game,' forcing students to ask more sophisticated questions, making the quality of the query—not the synthesized answer—the hallmark of learning.
In an age where AI can produce passable work, an educator's primary role shifts. Instead of focusing solely on the mechanics of a skill like writing, the more crucial and AI-proof job is to inspire students and convince them of the intrinsic value of learning that skill for themselves.
Rather than causing mass unemployment, AI's productivity gains will lead to shorter work weeks and more leisure time. This shift creates new economic opportunities and jobs in sectors that cater to this expanded free time, like live events and hospitality, thus rebalancing the labor market.
Contrary to fears of a forced, automated future, AI's greatest impact will be providing 'unparalleled optionality.' It allows individuals to automate tasks they dislike (like reordering groceries) while preserving the ability to manually perform tasks they enjoy (like strolling through a supermarket). It's a tool for personalization, not homogenization.