Academic papers and scientific foundations supporting GettingStoned's AI-powered spiritual practice technology
GettingStoned is built on a foundation of rigorous academic research spanning neuroscience, Buddhist philosophy, machine learning, and behavioral modeling. Below are the key scientific papers that inform our approach to quantifying and supporting spiritual practice.
These papers explore how past actions can be mathematically modeled to predict future behavior and assess trustworthiness—a direct parallel to a karmic ledger or reputation system.
This paper provides a formal mathematical model for trust and reputation, which are secular equivalents of karma. It discusses how an "agent's" reputation is updated based on past interactions, much like our system updates a user's karma score based on white and black stones.
This chapter explores how game theory—a mathematical study of strategic decision-making—can explain the emergence of moral behavior (virtue). It models how cooperation and altruism can be rational choices.
These articles discuss using technology and computational models to classify and understand mental states associated with meditation, similar to our Muse EEG integration and enlightenment probability calculations.
This classic study uses EEG to find quantifiable evidence of meditative states. The research found that meditation produced statistically significant increases in theta and alpha brainwave activity—the exact kind of data our Muse EEG integration captures.
This paper delves into the "Bayesian Brain" hypothesis, which posits that the brain is a prediction machine that constantly updates its model of the world. Altered states of consciousness, like those in deep meditation, can be understood as changes in the brain's "priors" or core beliefs.
These sources focus on the rigorous, logical methods of the Prasangika school, providing academic validation for the philosophical structure behind our "Emptiness Analysis" feature.
This paper directly analyzes the prasaṅga (reductio ad absurdum) method central to the Prasangika school. It compares this ancient Buddhist logical framework to modern Western philosophical deconstruction.
This chapter details the specific logical arguments used in Madhyamaka philosophy to demonstrate emptiness, including "the reasoning from dependent arising".
These papers show how methods from finance and risk analysis are used to predict human behavior over time, analogous to our goal of predicting future stone counts and spiritual progress.
This paper uses survival analysis—a core actuarial method—to model the "time until a customer makes their next purchase". This exact methodology can model the "time until a user logs their next white stone" or the "time until the next black stone risk event."
This foundational text explains how Monte Carlo simulations can be used to explore the range of outcomes in any system governed by probabilities. By treating a user's daily practice as a probabilistic event, we can simulate thousands of possible "future spiritual paths."
GettingStoned represents the intersection of ancient wisdom and modern science. By grounding our approach in peer-reviewed research, we ensure that our technology is both spiritually authentic and scientifically rigorous.
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