🔗 https://shre.ink/Learning-how-to-learn
By Derek Gatopoulos
Demis Hassabis, CEO of DeepMind and 2024 Nobel laureate, delivered a speech in Athens in which he emphasized that the most essential skill for the next generation will be “learning how to learn.” He argued that as AI transforms education, workplaces, and societies, the ability to adapt, acquire new knowledge, and continually re‑skill will matter more than any specific technical or subject expertise.
Speaking from an ancient Roman theatre at the foot of the Acropolis, Hassabis pointed out just how unpredictable the near future has become, due to rapid AI developments happening week by week. He said that while it's nearly impossible to forecast precisely what the world will look like in 10 years, one thing is certain: huge change is coming.
He also introduced the idea of meta‑skills — capabilities that go beyond traditional domain skills like math, science, and humanities. Among these are figuring out how to learn effectively, optimizing one’s approach to mastering new subjects, and being comfortable with learning in unknown or rapidly evolving environments.
Hassabis noted that artificial general intelligence (AGI) could potentially arrive within a decade. With such powerful models on the horizon, the pace of innovation could accelerate dramatically, bringing both "radical abundance" and serious risk. This amplifies the stakes: those who cannot adapt may be left behind in a world where continuous learning is not optional.
Greek Prime Minister Kyriakos Mitsotakis was present and contributed remarks. He warned that the benefits of AI need to be widely shared. If only a few companies or people profit, social inequality may worsen, and public skepticism could grow. He emphasized that personal, tangible benefits need to be visible to prevent unrest.
Hassabis also reflected on his own background: a neuroscientist, former chess prodigy, and co‑founder of DeepMind (founded in 2010, acquired by Google in 2014). His past scientific work includes breakthroughs like AI‑based protein folding prediction—something with real stakes in medicine and drug discovery. He used that as an example of how AI can solve complex problems when paired with the right mindset.
In a fast‑moving AI world, continuous learning, agility, curiosity, and proactive growth will define success. Traditional credentials will still have value, but what matters more is the ability to master new skills, unlearn outdated ones, and use AI as a tool—but not to depend on static knowledge alone.