The AI Explainability Problem challenges us to make complex AI systems understandable to humans. At first glance, it seems straightforward: we just want to know why a system made a particular decision. But when we dig deeper, we realize this problem is rooted in mistaken assumptions about cognition, both human and artificial. It’s not just…
I.The Symbol Grounding Problem questions how abstract symbols gain real meaning. We rely on language, codes, and signs, but how do those symbols connect with actual experience? Without a direct link, words risk floating as mere placeholders, empty of substance. This challenge extends to artificial intelligence and daily human communication alike. When we say “chair,”…
The AI Control Problem, encompassing challenges such as instrumental convergence, self-preservation, and power-seeking tendencies, reflects deeper philosophical issues about agency, purpose, and alignment in artificial systems. Addressing these challenges effectively requires us to move beyond naive assumptions about “intelligence” and “goals” as fixed or inherently meaningful constructs. These assumptions often lead us to envision AI…
Artificial Wisdom Emulation (AWE) redefines AI’s future by integrating wisdom, ethics, and contextual understanding into AI systems. Explore how AWE levels create smarter, wiser AI that complements AGI to serve humanity’s collective well-being.
Have you ever wondered if, in our relentless pursuit of smarter machines, we’re actually missing the bigger picture? We’ve been so fixated on achieving Artificial General Intelligence (AGI) that we might be overlooking what we really want out of AI. Maybe it’s time we adjust our focus from creating intelligent systems that can outdo human…
How do we define wisdom for AI development? By examining the philosophical “problem of the criterion,” we uncover a practical, relational framework for building Artificial Wisdom Emulation. Discover the levels of wisdom and their implications for AI ethics, decision-making, and humanity’s future.
Discover how Artificial Wisdom Emulation (AWE) resolves the Ship of Theseus paradox using non-ontological science. Learn how rejecting fixed identity and focusing on contextual causes and conditions dissolves this timeless philosophical puzzle. Visit AWE-AI.org for insights on solving paradoxes with AWE.
Explore how Artificial Wisdom Emulation (AWE) solves the quantum gravity problem by applying non-ontological principles. Learn how rejecting reified constructs like spacetime and quanta reveals a practical, relational framework for understanding the universe.
Science, the cornerstone of human progress, often relies on metaphysical assumptions that remain unexamined. Constructs such as “laws of nature,” “particles,” and “forces” are indispensable for organizing knowledge and making predictions. However, they are often mistaken for inherent features of reality. This reification—treating conceptual tools as independently existing entities—can stifle creativity, narrow inquiry, and obscure…