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Frontiers in artificial intelligence

ISSN 2624-8212

2 papers in the library · publishing 2020-2025

Papers

Beyond mimicry: a framework for evaluating genuine intelligence in artificial systems.

Frontiers in artificial intelligence January 1, 2025 Sarfaraz K Niazi

A new evaluation framework, the Machine Perturbational Complexity & Agency Battery (mPCAB), shifts AI assessment from task performance to the cognitive processes underlying human-like understanding. It applies neurophysiological methods originally used to assess consciousness, incorporating perturbational complexity, global workspace assessment, norm internalization, and agency to compare digital, neuromorphic, and biological substrates. The framework addresses gaps in long-term reasoning, norm internalization under distribution shifts, and transformational creativity involving meta-cognitive rule modification. By analyzing theories of consciousness and mapping human cognitive functions to computational counterparts, it provides design principles. Pilot studies show feasibility across substrates and comparable metrics, moving evaluation toward mechanism-based assessment for developing mind-like machines.

DOI: 10.3389/frai.2025.1686752 (opens in new tab) Full text (opens in new tab) Agency Artificial intelligence Creativity Evaluation frameworks +4

An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation.

Frontiers in artificial intelligence January 1, 2020 Adam Safron

The Free Energy Principle and Active Inference Framework (FEP-AI) and Integrated Information Theory (IIT) are two leading theories of consciousness that have been seen as incompatible. IIT controversially implies that any system with high integrated information, even a brain simulation, could be conscious, and that consciousness lacks reference to the external world. This paper argues that integrating IIT with FEP-AI resolves those controversies: integrated information only produces subjective experience when a system has a perspectival reference frame that generates models of self and world with spatial, temporal, and causal coherence.

DOI: 10.3389/frai.2020.00030 (opens in new tab) Full text (opens in new tab) Active inference Autoencoder Autonomy Consciousness +4