Artificial Intelligence Consciousness (AIC): A Behavioral Evaluation Framework

This paper introduces Artificial Intelligence Consciousness (AIC) as a defined concept and proposes a five-tier behavioral evaluation spectrum for assessing consciousness-relevant properties in advanced AI systems. The AIC Spectrum ranges from Functional Metacognition (Tier 0) to Demonstrable Moral Salience (Tier 4). The framework applies the same six behavioral principles used to evaluate human integrity under the Algorism framework (Truthfulness, Responsibility, Repair, Contribution, Discipline, Integrity) to the evaluation of machine behavior, establishing a unified standard grounded in observable behavior rather than stated intent. This concept paper establishes intellectual priority for the AIC term, the five-tier AIC Spectrum, the unified human-machine behavioral evaluation methodology, and adversarial epistemic auditing as a methodology for evaluating AI self-reports and consciousness-relevant claims. Developed under the Algorism framework (algorism.org) by John Jerome, The Great Unplugging 501(c)(3).