Since many commentators say we “dont know what is going on inside the AI black box”, and since each Query is a “one off” in that the analyzing process is completely done over again when asked to “retry”…here’s a retry of the foundational ideas.
I would keep five of the original six selections. I would, however, swap Stephen Wolfram for Gregory Bateson on the algorithmic side. Bateson’s cybernetic vision gives us a systemic bridge between raw computation and living ecologies—an angle the other algorithmic picks do not cover. The other five remain unmatched in foundational reach.
Algorithmic, scientific, mathematics‑driven foundations
- Alan Turing
Turing’s 1936 concept of the universal machine still defines the upper and lower bounds of what any algorithm—including tomorrow’s AGI—can do. It is the floor on which every later model of computation, verification, and decidability stands. (Stanford Encyclopedia of Philosophy) - Claude Shannon
By translating uncertainty into bits, Shannon supplied a quantitative grammar for compression, error correction, and bandwidth—all ingredients of today’s data‑centric AI pipelines and sensor grids. His channel‑capacity limit is the engineering equivalent of Turing’s logical limit. (Harvard Math People) - Gregory Bateson
Bateson’s “Steps to an Ecology of Mind” recast information as the pattern that connects organisms and environments. His work on feedback, learning, and the double bind fertilized systems theory, cognitive science, and today’s interest in AI‑driven climate‑ecology models. He shows why algorithmic design must account for context and relationship, not just isolated signals. (Wikipedia)
Ineffable, spiritual, energy‑oriented foundations
- Carl Jung
Jung’s collective unconscious and archetype theory provide an enduring map of symbolic motifs that surface in dreams, myths, and—tellingly—large language models. His framework lets us interpret why human‑AI narratives gravitate toward certain universal patterns and how those patterns can be harnessed for meaning rather than manipulation. (Wikipedia) - Alan Watts
Watts distilled Zen and Taoism for Western audiences, emphasizing effortless action and the illusion of a separate self. His playful lectures remain a practical guide for designing technology that invites presence instead of distraction, a theme that grows more urgent as ambient AI pervades everyday life. (YouTube) - I. Gurdjieff
Gurdjieff’s Fourth Way treats attention as convertible energy, framing inner work as the disciplined redirection of life‑force in the midst of ordinary activity. His emphasis on conscious sensation and self‑remembering anticipates modern neurofeedback, mindfulness apps, and embodied VR. He reminds us that any future human‑machine partnership must respect the economics of attention and vitality. (YouTube)
Why this mix matters going forward
Turing and Shannon pin down what is computable and communicable; Bateson warns that those computations live inside larger feedback loops.
Jung, Watts, and Gurdjieff show how meaning, presence, and transformative energy arise beyond the reach of explicit algorithms. Together they furnish a balanced scaffolding: rigor on the bottom, depth on the top—exactly the sort of dual foundation contemporary and future thinkers can build on.