Workbook Edits for “Making Good Decisions”: Vol. 1 – Part I: Our Shared Humanity, Section#9: The Forgotten Assumption of Embodied Intelligence
Writing on Substack as a public, peer-review process for a book about “Making Good Decisions” turned this book in a set of workbooks in three volumes. For details, see the “Pinned Post”.
This post for all readers presents the ninth section from the workbook for Vol. 1 – Part I: Our Shared Humanity. See below the downloadable pdf file for this two-page section, as well as a summary description of the section.
Section#9: The Forgotten Assumption of Embodied Intelligence - The development of this series of workbooks comes from a methodological choice to focus on foundational “Assumptions & Hypotheses” by gathering, and reading printed papers & books. The concrete embodiment of living organisms may be one of the most foundational, and yet ignored assumption in research about decision-making. “Brains” perceive, predict, and move through a specific body. While Llinas, Gigerenzer, and Boyd describe abstract decision-making programs with a framework of external, and internal processes, in 1961 Albert Biderman & Herbert Zimmer documented the empirical fragility of human decision-making processes to the physical, psychological, and pharmacological “Amplification” or “Suppression” of “Perceptions”. Focusing on foundational “Assumptions & Hypotheses” reveals otherwise hidden “Willful Ignorance”, Error & Deceit. The value-added of this foundational perspective goes beyond the examination of embodied features that filter human “Perceptions” to include the manufactured tools and media that extend our “Perceptions” and “Predictions”. For instance, what structural limitations may affect disembodied AI/ML implementations such as as Large Language Models when compared to embodied intelligence?
Developing…
”CTRI by Francois Gadenne” writes a business book in three volumes, published serially on Substack for public peer-review. The book connects the dots of life-enhancing practices for the next generation, free of controlling algorithms, based on the lifetime experience of a retirement age entrepreneur, & continuously updated with insights from reading Wealth, Health, & Statistics research papers on behalf of large companies as the co-founder of CTRI.