An exploration of how we might conceptualize the design of AGI within the context of human left and right brains.

The tension between AI and human functioning highlights unique cooperation. AI uses language, abstraction, and analysis, while humans rely on experience, empathy, and metaphor. AI manipulates static elements well but struggles in a changing world.

This leads to two distinct design approaches for future AI and considerations for "artificial general intelligence" (AGI).

One approach focuses on "left-brained" AI—controlling facts with internal consistency, while relying on humans for context, meaning, and care. Here, machines serve humans. This path is popular due to the challenge of developing AI mimicking human right hemisphere functions.

However, we want machines that can correct contextual mistakes and understand our intended meanings. The design challenge here lies in connecting highly "left-brained" AI to holistic humans in a way that enhances human capabilities.

Alternatively, we could design AI with asymmetry, mirroring the human brain's evolution. Such AI would provide a synthesized perspective before interacting with a human, applying computational power to intuition and addressing human paradoxes. Some envision this as AGI—an all-knowing synthesis machine.

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