Open-endedness and Artificial Superhuman Intelligence

Explore the concept of open-endedness, a key trait for artificial superhuman intelligence. Learn how AI must transcend pattern recognition and develop unbounded creativity, setting its own goals for continual innovation. Discover the challenges in achieving true open-ended AI.

An abstract image of infinity

David Deutsch, the reclusive physicist and philosopher, suggests that the key to human progress lies in our unique ability to create explanatory knowledge—theories that not only describe the world but open new avenues for discovery. In Deutsch's view, intelligence, whether human or artificial, is about participating in an endless frontier of explanation and innovation.

Deutch's book, The Beginning of Infinity, has influenced our understanding of AI, particularly in conceptualizing AGI. His work provides a clear framework for thinking about intelligence, emphasizing that it isn't tied to IQ or mechanistic benchmarks, but to the more elusive qualities we deeply value, such as creativity. As he articulated in 2011 (and is still true today):

The field of artificial (general) intelligence has made no progress because there is an unsolved philosophical problem at its heart: we do not understand how creativity works. Once that has been solved, programming will not be difficult.

For general intelligence, AI has to transcend computation and pattern recognition and develop the capacity for open-ended self-improvement, being unbounded as Deutsch sees in human thought. This means AI systems must be able to generate novel ideas, critically evaluate their own knowledge, identify gaps in their understanding, and autonomously seek out new information to fill those gaps. They should be capable of reformulating problems, making unexpected connections between disparate fields, and even questioning their own fundamental assumptions. They must be able to set their own goals for improvement, driven by an intrinsic curiosity about the world rather than externally imposed objectives.

To match Deutsch's conception of intelligence, AI needs to become not just a problem-solver, but a problem-finder and a creator of new knowledge, where it expands its own horizons in ways that even its creators might not have anticipated—a concept called open-endedness, and it is gaining traction in the AI research community.

Open-endedness is the capacity for continual innovation and learning, a trait that has long defined human intelligence but as yet doesn’t exist in AI. A new paper from Google DeepMind caught my eye because it aims to create a formal definition for open-endedness in AI, why it is required for Artificial Superhuman Intelligence, and outlines how it might be designed.

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