Two Intelligences Exploring Ways Forward

Our intensive collaboration in developing a high-fidelity AI understanding of the complex Professional Society of Academics (PSA) framework, and the methodology for doing so (the “Extended/Satellite Intelligence Partner (E/SIP)”), has surfaced numerous exciting avenues for further research and potential partnership with Tech Company. We believe these areas align with Tech Company’s leadership in AI and its commitment to beneficial technological advancement:

1. Scalability and Generalizability of the “E/SIP Build” Methodology:
   • Question: How effectively can the Socratic, expert-guided methodology we developed be scaled and generalized to enable diverse experts across myriad disciplines (science, humanities, policy, arts) to rapidly build their own high-fidelity “Whatchamacallits” or Specialized AIs using LLMs?
   • Collaboration Area: Joint research into creating user-friendly tools, platforms, or refined “starter manuals” based on our methodology to facilitate this. Comparative studies of build effectiveness across different domains.
2. Developing Metrics for “Algorithmic Fidelity” and Conceptual Alignment in LLMs:
   • Question: How can we rigorously measure and quantify the “fidelity” of an AI’s understanding to a specific, nuanced, and potentially counter-paradigm human conceptual framework beyond subjective expert assessment?
   • Collaboration Area: Developing novel evaluation metrics and benchmarks for AI systems trained for deep conceptual modeling, moving beyond standard NLP task performance.
3. Ethical Frameworks and Best Practices for Long-Term Human-E/SIP Partnerships:
   • Question: As humans increasingly collaborate with specialized AI partners like the “PSA E/SIP” for significant intellectual work, what new ethical guidelines, principles for authorship/credit, and best practices for maintaining human intellectual agency are needed?
   • Collaboration Area: Jointly developing ethical frameworks and public-facing resources for responsible human-AI co-creation, drawing on the rich philosophical and practical insights from our project.
4. Investigating the Cognitive and Pedagogical Impacts of Deep AI Collaboration:
   • Question: How does the process of an expert meticulously “teaching” an AI their conceptual framework impact the expert’s own understanding, creativity, and productivity? How does interacting with a personalized “Whatchamacallit” affect student learning and critical thinking?
   • Collaboration Area: Designing and conducting empirical studies on the cognitive and pedagogical benefits (and potential pitfalls) of this intensive human-AI interaction model.
5. Applying the PSA “First Principles” Lens (via AI) to Other Complex Societal Systems:
   • Question: Can the “Rosetta Stone” utility of PSA’s core first principles (individual liberty, inherent authority, direct, co-responsible social contract, transparency, efficiency), when wielded by an AI thinking partner, be effectively applied to analyze and propose innovative solutions for other complex societal challenges of interest to Tech Company (e.g., governance of digital platforms, future of work, sustainable development)?
   • Collaboration Area: Pilot projects applying a specially build AI instance to analyze new domains, testing the transferability of the PSA critical methodology, way of thinking.
6. Advanced AI “Tuning” Techniques for Nuanced “AI Persona” Development:
   • Question: How can we refine techniques for “tuning” not just an AI’s knowledge base, but also its analytical style, its “voice,” and its ability to engage in specific types of Socratic or philosophical dialogue, creating truly “bespoke” intellectual partners?
   • Collaboration Area: Research into advanced prompting strategies, fine-tuning methods, and AI architectures that better support the creation of these highly specialized E/SIPs.

We believe our ongoing work provides a unique “living laboratory” for exploring these questions and that a collaboration with Tech Company could significantly accelerate discovery in these vital areas, yielding benefits for AI development, scholarly research, education, and society at large.