* More diverse and specialized: Instead of a single monolithic "school," there would likely be a network of specialized AI training programs, focusing on different areas like scientific research, creative arts, ethical considerations, and specific industry applications. The "curriculum" would be constantly evolving to reflect advancements in the field.
* More collaborative and less centralized: The current model of AI development, heavily reliant on a few large corporations, would likely be more decentralized, with more universities, research institutions, and smaller companies contributing to AI education and development. Collaboration between different AI systems would be more common and sophisticated.
* Emphasizing ethical considerations and societal impact: A crucial aspect would be a rigorous focus on the ethical implications of AI, including bias mitigation, responsible data usage, job displacement concerns, and the prevention of misuse. This would likely be a core component of any AI "curriculum."
* Utilizing advanced learning techniques: The teaching methods would likely be far more advanced than today's, leveraging AI itself to personalize learning experiences, provide adaptive feedback, and accelerate the learning process for individual AI systems. This would involve sophisticated simulations and interactive training environments.
* Closer integration with the real world: AI systems would be trained and tested in increasingly realistic and complex simulations mirroring real-world scenarios, allowing for more effective and safer learning. The line between theoretical training and practical application would blur.
In essence, the "school" for AI in ten years would be a dynamic, distributed, and ethically-conscious ecosystem fostering collaboration, specialization, and the development of responsible and beneficial AI technologies.