Multiscalar brain adaptability in AI systems
Year: 2024
Type: editorial
Abstract: The advent of Generative AI has transformed creative and analytical landscapes, leveraging vast datasets to produce sophisticated outputs with remarkable efficiency. Despite these advancements, human judgment and adaptability remain indispensable for navigating complex, dynamic, and context-sensitive environments. This editorial explores the interplay between human cognition, AI, and quantum biological consciousness, emphasizing how the brain’s multiscalar adaptability can inform the development of conscious AI systems. At the core of this exploration is Artificial General Intelligence (AGI), which seeks to emulate human cognitive flexibility, reasoning, and learning within computational paradigms. While AGI excels in predefined tasks, it falters in managing uncertainty and unpredictability. Strong Artificial Intelligence (SAI), by contrast, envisions systems capable of mind-like processes—managing uncertainty and anticipating unexpected events. Achieving SAI requires a deeper understanding of the brain’s adaptability, spanning multiple scales from synaptic plasticity to precognitive consciousness. Consciousness, defined as the phenomenal experience or the subjective "feeling" of awareness, remains a formidable challenge in AI development. Current neural architectures, such as those in deep learning, can mimic patterns of intentionality but lack the intrinsic depth of consciousness. Multiscale adaptability offers a novel perspective, highlighting the brain’s dynamic, non-linear interactions across various scales. Consciousness, in this view, is not a static state but a fluid process, driven by self-referential pathways and diachronic adaptability.
DOI: 10.56280/1663524979
Authors: Senior AI Scientist at Silo AI, 00180 Helsinki,, Shantipriya Parida
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4405912883