AI, Copyright and the Next Generation - Part 2:

Learning, Limits and the Myth of Falling Behind

As the world dashes into an AI-driven future, Google DeepMind CEO Demis Hassabis recently warned young people:

“Learn now or be left behind.”

It’s a provocative message, but it deserves closer scrutiny.

At Aralia, we believe that learning about AI is essential, but not in the way it’s often presented. Understanding the limitations and implications of the technology is just as important as knowing how to use it. In this blog, we examine why creativity, critical thinking, and foundational knowledge in science and the humanities still matter far more than chasing every new AI tool.

A Broader View than the Machine Can See

Isaac Newton once said he had seen further by “standing on the shoulders of giants.” We don’t believe AI will create the next generation of giants. Its function is to predict using what’s already known, not to create new paradigms.

AI can surface patterns, generate summaries, and provide clarity. But it cannot see beyond its training data. Its horizon is inherently limited.

Young people need a working knowledge of AI to the extent that it helps them reach their goals. But becoming “AI Ninjas,” as Hassabis suggests, isn’t essential, and may even constrain their creative potential.

1. Copyright

Hassabis asserts that Artificial General Intelligence (AGI), sentient AI capable of true innovation, is only a few years away. However, this view is not shared by the majority of AI researchers. We are still far from creating AGI, and its speculative promise should not shape educational priorities.

Read: “4 Shortcomings of Large Language Models” – Synthedia

At Aralia, we’ve developed and deployed “world models” that solve reasoning tasks efficiently, but even these sophisticated systems fall short of human cognition. As we noted in our previous blog on the limits of machine learning, current AI lacks the philosophical foundation to truly create or innovate. It excels at interpolation, not invention.

2. Innovation

The idea that young people must become AI specialists to remain relevant assumes AI will rapidly transform every field. Yet over the past 18 months, progress in generative AI has plateaued. The narrative of constant exponential growth has not materialised.

Current AI has proven to be a powerful numerical tool, revealing hidden patterns in large datasets. But it rarely uncovers why those patterns exist. True scientific discovery still requires creative thought and rigorous reasoning.

Rather than replacing disciplines, AI should complement them. If we want meaningful breakthroughs, we need renewed focus on STEM excellence, not just AI literacy. Creativity is still the sole domain of humans, AI is currently, and for the foreseeable future, incapable of forming the framework of natural philosophy.

And when it comes to the humanities, the story is the same. Generative tools may save time, but the results are formulaic, generic, and uninspired. AI can replicate the mediocre. But young people shouldn’t aspire to be mediocre.

Looking Ahead

We welcome the idea that young people engage with AI, but not because they’re at risk of being left behind. Instead, we should encourage them to develop critical, ethical, and creative capacities that AI cannot replicate.

In short, don’t teach them to chase the machine, teach them to lead it.

📖 Missed Part 1? Read our take on AI, copyright, and commercial realities here.