Medium Article: https://medium.com/@jsmith0475/building-human-facing-agentic-systems-the-psychology-and-sociology-of-super-intelligence-1571cf565d51

Dr. Jerry Smith's January 2025 Medium article explores the psychological, sociological, and ethical implications of "human-facing agentic systems," AI powered by large language models (LLMs). These systems, leveraging multi-headed attention mechanisms, aim to collaborate with humans, not merely serve as tools. The article emphasizes the potential for both empowerment and manipulation inherent in these systems, highlighting the crucial role of self-interest, emotion, and identity in human-AI interaction. Smith concludes with a call for responsible development guided by transparency, inclusivity, and justice, warning against the potential for these systems to become instruments of control.

Building Human-Facing Agentic Systems: The Psychology and Sociology of Super Intelligence

Medium Article: https://medium.com/@jsmith0475/why-current-nil-valuations-fail-and-how-multi-agent-ai-fixes-them-f1652a0e887c
The article, by Dr. Jerry A. Smith, describes VALORE, a novel multi-agent artificial intelligence system designed to accurately value a collegiate athlete's Name, Image, and Likeness (NIL) influence, correcting for the failures of current surface-level metrics. This system employs seven specialized thinking transformer models—such as a Social Media Analysis Agent and a Psychological Profile Agent—that coordinate through goal-oriented consensus mechanisms to integrate diverse factors like behavioral science, economic data, and athletic performance. The research emphasizes that VALORE models crucial human elements like parasocial relationships and authenticity to predict true marketing value, ensuring the system maintains high prediction accuracy, transparent coordination, and ethical oversight through proactive bias detection. Ultimately, VALORE seeks to create more equitable and efficient markets by benefiting athletes, brands, and universities through enhanced decision support and compliance.

Why Current NIL Valuations Fail — and How Multi-Agent AI Fixes Them

In-Depth Explorations of Neuroscience-Inspired Architectures Revolutionizing AI.

Why Current NIL Valuations Fail — and How Multi-Agent AI Fixes Them

Dr. Jerry A. Smith

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