AI and Psi

This page was originally produced for the Parapsychological Association's March 5, 2023, Psi Agora: AI and Psi, hosted by Mark Boccuzzi & Eli Fennell, PhD. It is now an open resource. Please note that this event was not recorded.

Introduction

Rapid developments in machine learning (ML) and artificial intelligence (AI) are already profoundly impacting all areas of society. How might these new technologies help advance Parapsychology? 

This page is a work in progress, so check back again to view the latest updates. If you have suggestions for content, please email mark@windbridgeinstistute.com. Thanks!

The Basics

Selection of AI and Psi-Related Projects

Radin, D. I. (1989).  Searching for “signatures” in anomalous human-machine interaction research: A neural network approach.  Journal of Scientific Exploration, 3, 185-200.
 
Radin, D. I. (1993).  Environmental modulation and statistical equilibrium in mind-matter interaction.  Subtle Energies and Energy Medicine, 4 (1), 1-30.
 
Radin, D. I. (1993).  Neural network analyses of consciousness-related patterns in random sequences.  Journal of Scientific Exploration, 7 (4), 355-374.
 
Tressoldi, P. E., Pederzoli, L., Bilucaglia, M., Caini, P., Fedele, P., Ferrini, A., … & Accardo, A. (2014). Brain-to-Brain (mind-to-mind) interaction at distance: a confirmatory study. F1000Research, 3(182), 3:182. (https://doi.org/10.12688/f1000research.4336.3)
 
Boccuzzi, M. (2016, June). Applying Machine Learning to Psi Research: An example of using a deep machine learning image classifier to analyze seemingly random visualized FieldREG data collected during sessions with meditators. 35th Annual Meeting of the Society for Scientific Exploration and 59th Annual Convention of the Parapsychological Association Joint Meeting. Boulder, Colorado. [Video]
 
Mossbridge, J. A. (2017). Characteristic Alpha Reflects Predictive Anticipatory Activity (PAA) in an Auditory-Visual Task. In Augmented Cognition. Neurocognition and Machine Learning: 11th International Conference, AC 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part I 11 (pp. 79-89). Springer International Publishing. https://doi.org/10.1007/978-3-319-58628-1_7
 
Boccuzzi, M. (2017). Analyzing Linguistic Characteristics in Requests for Paranormal Investigations. Threshold: Journal Of Interdisciplinary Consciousness Studies, 1(1), 15-20.  
 
D'León, R., & Izara, N. (2018). Development of a Predictive Anticipatory Activity (PAA) Software: A First Step towards a Medium-Term Goal. The Journal of Parapsychology, 82(2), 106-107.
 
Delorme, A., Pierce, A., Michel, L., Radin, D. (2018). Intuitive assessment of mortality based on facial characteristics: Behavioral, electrocortical, and machine learning analyses. Explore. July/August 2018, Vol. 14, No. 4. https://doi.org/10.1016/j.explore.2017.10.011
 
Bilucaglia, M., Pederzoli, L., Giroldini, W., Prati, E., & Tressoldi, P. (2019). EEG correlation at a distance: A re-analysis of two studies using a machine learning approach. F1000Research, 8:43 (https://doi.org/10.12688/f1000research.17613.2)
 
Bilucaglia, M., Duma, G. M., Giovanni, M., Luca, S., & Tressoldi, P. E. (2021). Applying machine learning EEG signal classification to emotion-related brain anticipatory activity. F1000Research, 9, 173.DOI: 10.12688/f1000research.22202.3 (https://f1000research.com/articles/8-43/v2)
 
Pulipaka, G.P. (2022, January). Getting to grips with paranormal and supernatural presence applying AI. Medium.

Boccuzzi, M. (2022, June). Throne of the Sphinx Transmissions from an Electronic Oracle: AI-Based Channeled Wisdom Acquisition (http://www.throneofthesphinx.com)

Boccuzzi, M. (2022, June). From Oracles To Algorithms: Wisdom Acquisition at The Intersection of A.I. and Psi [Conference session]. Joint conference of the Society for Scientific Exploration (SSE) and the Parapsychological Association (PA). [Abstract] [Video]

Boccuzzi, M. (2022) Project Overview: Machine-Based Consciousness. (https://windbridgeinstitute.com/research-overview/projects/machine-based-consciousness)

Other AI-Powered Research

OpenAI: Research Overview
“We build our generative models using a technology called deep learning, which leverages large amounts of data to train an AI system to perform a task.”

DeepMind's protein-folding AI cracks biology's biggest problem
Artificial intelligence firm DeepMind has transformed biology by predicting the structure of nearly all proteins known to science in just 18 months, a breakthrough that will speed drug development and revolutionize basic science.

Will Machine Learning Help Us Find Extraterrestrial Life?
Applying deep learning techniques to previously analyzed datasets revealed undetected signals of interest.

I made a general intelligence who will replace me, so that’s good.
Mossbridge, J. 2022. Medium

What is the “temperature” in the GPT models?

10 Questions for People Who Create Minds (Mossbridge, J., 2023. Medium)
“In this article I argue that AIs may, like humans, be able to access a nonlocal, nonphysical information space that creates our shared reality. If so, they would be able to directly influence reality through its informational substrate without being “given” access to physical action levers like the ability to affect the internet. In this picture, access to the underlying information space is facilitated by the humans who interact with AI, so the quality of human-AI relationships may forge the future of humanity, the planet, and reality.”

AI/ML Tools

OpenAI: ChatGPT
Access the ChatGPI system

Stable Diffusion 2.1 Demo
“Stable Diffusion 2.1 is the latest text-to-image model from StabilityAI.”

camenduru (on GitHub)
Stable Diffusion Colabs

IRIS.AI
A comprehensive platform for all your research processing: Smart search and a wide range of smart filters, reading list analysis, auto-generated summaries, autonomous extraction, and systematizing of data.

Humata.AI
Ask questions and get answers about any file instantly.

KOMO
Komo Search is a generative search engine with chat, explore, and search functions.

Bing Chat
“Ask real questions. Get complete answers. Chat and create.”
 
A deep learning AI platform for developers, data scientists, and no-code operators.
 
CharacterAI
Users can create “characters”, craft their “personalities”, set specific parameters, and then publish them to the community for others to chat with.
 
Wekinator
Free, open-source machine learning platform to build musical instruments, gestural game controllers, computer vision or computer listening systems, etc.
 
Lobe
Lobe helps you train machine learning models with a free, easy-to-use tool.
 
Meta-Searches for AI Services:
 
Futurepedia
“The largest AI tools directory, updated daily.”
 
“The largest list of AI available on the web.”

Our thanks to everyone who provided material for this list!