Demis Hassabis on the link between AI for art and AI for science

2026-06-24 · Source: Semafor · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation · Depth: Intermediate, quick

Summary

Google DeepMind CEO Demis Hassabis challenges the common distinction between AI for scientific discovery and AI for artistic creation, arguing that the underlying technological capabilities are inseparable. He posits that for AI to truly revolutionize science, it must achieve "true creativity" – the ability to formulate genuinely new concepts beyond human extrapolation, a benchmark he calls the "Einstein test." This requires AI to understand the physical world, not just text or logic, suggesting that training on human-made visual and auditory creations is crucial. Hassabis connects imagination to simulation, drawing parallels from his neuroscience research on memory and his game design experience. He notes that DeepMind's early work on games paved the way for advancements in protein folding, implying that capabilities developed for creative applications, like generating advertisements, could similarly advance scientific understanding, robotics, or molecular analysis. This perspective is underscored by Google's \$75 million investment in A24, an independent film studio, to integrate AI tools into its creative processes.

Key takeaway

For Directors of AI/ML evaluating investment strategies, recognize that core AI capabilities driving scientific breakthroughs are intrinsically linked to artistic creation. Your teams should avoid segmenting AI development into "good" science and "bad" art. Progress in one domain often fuels the other. Instead, consider holistic investments in AI research. Foster imagination and simulation across diverse data types, including visual and auditory creations. This approach accelerates broad technological advancement and innovation.

Key insights

AI's "true creativity" for both scientific discovery and artistic creation relies on shared simulation capabilities.

Principles

• True creativity formulates genuinely new concepts.
• Imagination operates as a type of internal simulation.
• AI capabilities for art and science are inseparable.

In practice

• Train AI on human-made visual and auditory creations.
• Apply game-based research ladders to new domains.
• Integrate AI tools into creative production workflows.

Topics

• AI Creativity
• Scientific Discovery
• Artistic AI
• DeepMind Research
• AI Simulation
• Google Investments

Best for: Research Scientist, AI Scientist, Director of AI/ML, AI Ethicist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Semafor.