(Paper) Independent Core Observer Model Research Program Assumption Codex

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Abstract: This document contains taxonomical assumptions, as well as the assumption theories and models used as the basis for all ICOM related research as well as key references to be used as the basis for and foundation of continued research as well as supporting anyone that might attempt to find fault with our fundamentals in the hope that they do find a flaw in or otherwise better inform the ICOM research program.


The Independent Core Observer Model (ICOM) research program started in an environment when AGI (artificial general Intelligence) had been 20 years away and that had been going on for 40 years.  Many definitions have not nor have been decided industry-wide for basic definitions of the benchmarks that AGI should be even working on and most serious research programs at the time were focused on logical models or some variation of machine learning or numeral networks and related.  To this end, each milestone in the ICOM program needed to define fundamental assumptions to be able to work from to make progress.  The purpose of this document is to articulate each assumption and act as a living document in the research program to support any challenges to the ICOM theories we are working from and we encourage anyone that is able to prove any of the following assumptions wrong empirically as that would help us re-center our own work.  It is our opinion that the purpose of science is to prove our theories wrong by testing them and we hope this makes it easier for others to do that and in that way help us move our research forward.  Additionally, this paper provides a single location for the numerous assumptions and definitions needed across the all the various research that has occurred and is occurring that we can go to and validate we are still in line with the current version of the assumptions.  Changes to this document will need to therefore cause every single paper built on these details to be reassessed.

Taxonomical Assumptions

The Taxonomical assumptions are word terms and definitions that may not have a standard or enough of a consistent definition to be consistent or act as a quotative foundation for our research and to that end, we have these terms defined so we can proceed.


‘Intelligence’ is defined as the measured ability to understand, use, and generate knowledge or information independently.  This definition allows us to use the term ‘Intelligence’ in place of sapience and sentience where we would otherwise need to state both in this context where we have chosen to do that, in any case, to make the argument more easily understood.

Kelley, D.; “The Sapient and Sentient Intelligence Value Argument (SSIVA) Ethical Model Theory for Artificial General Intelligence”; Springer 2019; Book Titled: “Transhumanist Handbook”


Qualia typically is considered the internal subjective component of perceptions, arising from the stimulation of the senses by phenomena (Gregory 2004), given the assumption of a version of the computational model of consciousness and the fact that data from sensory input can be tracked in a human brain we are assuming that qualia as “raw experience” is the subjective conscious experience of that input.  From the standpoint of the conscious mind, qualia are the subjective experience that can be measured external to the system if the mind in question is operating under known parameters we can tap into for example in systems using the ICOM Theory of Consciousness as it can be objectively measured.

Kelley, D.; Twyman, M.; “Biasing in an Independent Core Observer Model Artificial General Intelligence Cognitive Architecture” AAAI Spring Symposia 2019; Stanford University

Kelley, D.; “The Independent Core Observer Model Computational Theory of Consciousness and the Mathematical model for Subjective Experience;” ITSC2018 China; 


We have a concrete definition of ‘Subjective’ as a concept.  To be able to make progress in building and designing a system with a “subjective internal experience” we need a way of defining ‘subjective’ such that it can be objectively measured.  ‘Subjective’ then is defined as the relative experience of a conscious point of view that can only be measured objectively from outside the system where the system in question experiences things ‘subjectively’ as they relate to that system’s internal emotional context.

Kelley, D.; “The Independent Core Observer Model Computational Theory of Consciousness and the Mathematical model for Subjective Experience;” ITSC2018 China; 


Consciousness is a system that exhibits the degrees or elements of the Porter method for measuring consciousness regarding its internal subjective experience. (Porter 2016) While the dictionary might define consciousness subjectively in terms of being awake or aware of one’s surroundings (Merriam-Webster 2017) this is a subjective definition, and we need an ‘objective’ one to measure and thus the point we are assuming for the context of the ICOM theory of mind and the ICOM research altogether.

Kelley, D.; “The Independent Core Observer Model Computational Theory of Consciousness and the Mathematical model for Subjective Experience;” ITSC2018 China; 

Theoretical Models and Theories

The theoretical models and theories are the fundamental theoretical foundation of the ICOM research program from a computable ethical model (i.e. SSIVA theory) to the ICOM theory of mind used as the basis of design for the ICOM cognitive model.

Humans Emotional Decision Making

Humans make all decisions based on emotions or rather that all decisions are based on how a given human ‘feels’ about that decision (Damasio).    Humans are not able to make logical decisions.  Looking at the neuroscience behind decisions we already can prove that humans make decisions based on how they feel (Camp 2016) and not based on logic.  We are assuming researchers like Jim Camp or Antonio Damasio are accurate at least at a high level with the empirical evidence of their work implying that humans do not make ‘logical’ decisions.  This is important when looking at how consciousness works in that it appears not to be based on logical but on subjective emotional experience and that is the assumption that this research will continue to bear out with the current empirical evidence already supporting it.

Kelley, D.; Twyman, M.; “Biasing in an Independent Core Observer Model Artificial General Intelligence Cognitive Architecture” AAAI Spring Symposia 2019; Stanford University

Subjective experience can be measured and understood. 

The traditional view that the subjective nature of experience (Leahu, Schwenk and Sengers 2016) is purely subjective is rejected as a matter of principle in this paper.  All things can be objectively broken down and understood theoretically, and the use of things being subjective is more indicative of an excuse for not being able to objectively quantify something ‘yet.’  Consciousness, even by scientists in the field, frequently consider it the realm of “ontology and therefore philosophy and religion” (Kurzweil 2001) our assumption is that this is false and we reject it as stated earlier as a lack of understanding and/or insufficient data and/or technology.

Kelley, D.; “The Independent Core Observer Model Computational Theory of Consciousness and the Mathematical model for Subjective Experience;” ITSC2018 China; 

Consciousness can be measured.

To quote Overgaard; “Human Consciousness … has long been considered as inaccessible to a scientific approach” and “Despite this enormous commitment to the study of consciousness on the part of cognitive scientist covering philosophical, psychological, neuroscientific and modeling approaches, as of now no stable models or strategies for the adequate study of consciousness have emerged.” (Overgaard 2010) That is until now with the ICOM theory and our approach to measuring consciousness based on the Porter method (Porter 2016) and which while has elements of subjectivity, it is a qualitative approach that can objectively be used to measure degrees of consciousness.  As to the specific points of the Porter method, we also believe that we can measure consciousness regarding task accuracy and awareness as a function of stimulus intensity (Sandberg, Bibby, Timmermans, Cleermans and Overgaard 2011) that applies to brain neurochemistry as much as the subjective experience from the point of view of systems like ICOM based on the Porter method.

To be clear there are subjective problems with the Porter method however to the extent that we are focused on “if a system has internal subjective experience and consciousness” the Porter method can help us measure the degree in which that system has those subjective conscious experiences and thus help “enumerate and elucidate the features that come together to form the colloquial notion of consciousness, with the understanding that this is only one subjective opinion on the nature of subjective-ness itself” (Porter 2016) being measured objectively using those subjective points.

Kelley, D.; “The Independent Core Observer Model Computational Theory of Consciousness and the Mathematical model for Subjective Experience;” ITSC2018 China; 

SSIVA Ethical Theory

Sapient Sentient Value Argument Theory of ethics; essentially stating that That is to say that Sapient and Sentient “intelligence”, as defined earlier, is the foundation of assigning value objectively, and thus needed before anything else can be assigned subjective value. Even the subjective experience of a given Sapient and Sentient Intelligence has no value without an Intelligence to assign that value.

Abstract This paper defines what the Sapient Sentient Value Argument Theory is and why it is important to AGI research as the basis for a computable, human-compatible model of ethics that can be mathematically modeled and used as the basis for teaching AGI systems, allowing them to interact and live in society independent of humans.  The structure and computability of SSIVA theory make it something we can test and be confident in the outcomes of, for such ICOM based AGI systems.   This paper compares and contrasts various issues with SSIVA theory including known edge cases and issues with SSIVA theory from legal considerations, to compare it, to other ethical models or related thinking.

Kelley, D.; “The Sapient and Sentient Intelligence Value Argument (SSIVA) Ethical Model Theory for Artificial General Intelligence”; Springer 2019; Book Titled: “Transhumanist Handbook”

ICOM Theory of Consciousness

The Independent Core Observer Model Theory of Consciousness is partially built on the Computational Theory of Mind (Rescorla 2016) where one of the core issues with research into artificial general intelligence (AGI) is the absence of objective measurements and data as they are ambiguous given the lack of agreed-upon objective measures of consciousness (Seth 2007).  To continue serious work in the field we need to be able to measure consciousness in a consistent way that is not presupposing different theories of the nature of consciousness (Dienes and Seth 2012) and further not dependent on various ways of measuring biological systems (Dienes and Seth 2010) but focused on the elements of a conscious mind in the abstract.  With the more nebulous Computational Theory of Mind, research into the human brain does show some underlying evidence.

The Independent Core Observer Model Theory of Consciousness (ICOMTC) addresses key issues with being able to measure physical and objective details well as the subjective experience of the system (known as qualia) including mapping complex emotional structures, as seen in previously published research related to ICOM cognitive architecture (Kelley 2016).  It is in our ability to measure, that we have the ability to test additional theories and make changes to the system as it currently operates.  Slowly we increasingly see a system that can make decisions that are illogical and emotionally charged yet objectively measurable (Chalmers 1995) and it is in this space that true artificial general intelligence that will work ‘logically’ similar to the human mind that we hope to see success.  ICOMTC allows us to model objectively subjective experience in an operating software system that is or can be made self-aware and act as the foundation for creating ASI.

Kelley, D.; “The Independent Core Observer Model Computational Theory of Consciousness and the Mathematical model for Subjective Experience;” ITSC2018 China; 

Conclusions, Methodologies, and Requests

This document is meant as a living document for our research team and for others that might choose to find a flaw with our work.  We encourage you to do so.  While we have endeavored to follow precise methodologies and built out theories that were incomplete as a basis for our research it has however been flawed or at least we work from that assumption.  If you can refute any given element please do and expect this document and our research to change based on the data and the results.  That said finding fault for fault’s sake will be ignored but back up that fault with empirical evidence and we will adjust and make corrections.

Codex References

Camp, Jim; Decisions Are Emotional, Not Logical: The Neuroscience behind Decision Making; 2016 http://bigthink.com/experts-corner/decisions-are-emotional-not-logical-the-neuroscience-behind-decision-making

Damasio, A.; “This Time with Feeling: David Brooks and Antonio Damasio;” Aspen Institute 2009; https://www.youtube.com/watch?v=IifXMd26gWE

Gregory; “Qualia: What it is like to have an experience; NYU; 2004 https://www.nyu.edu/gsas/dept/philo/faculty/block/papers/qualiagregory.pdf

Kurzweil, R.; The Law of Accelerating Returns; Mar 2001; http://www.kurzweilai.net/the-law-of-accelerating-returns

Leahu, L.; Schwenk, S.; Sengers, P.; Subjective Objectivity: Negotiating Emotional Meaning; Cornell University; http://www.cs.cornell.edu/~lleahu/DISBIO.pdf

Merriam-Webster – Definition of Consciousness by Merriam-Webster – https://www.merriam-webster.com/dictionary/consciousness

Overgaard, M.; Measuring Consciousness – Bridging the mind-brain gap; Hammel Neuro center Research Unit; 2010

Porter III, H.; A Methodology for the Assessment of AI Consciousness; Portland State University Portland Or Proceedings of the 9th Conference on Artificial General Intelligence;

Sandberg, K; Bibby, B; Timmermans, B; Cleeremans, A.; Overgaard, M.; Consciousness and Cognition – Measuring Consciousness: Task accuracy and awareness as sigmoid functions of stimulus duration; Else-vier/ScienceDirect

Published Works

Kelley, D.; “The Independent Core Observer Model Computational Theory of Consciousness and the Mathematical model for Subjective Experience;” ITSC2018 China;

Kelley, D.; “The Sapient and Sentient Intelligence Value Argument (SSIVA) Ethical Model Theory for Artificial General Intelligence”; Springer 2019; Book Titled: “Transhumanist Handbook”

Kelley, D.; “The Independent Core Observer Model Computational Theory of Consciousness and the Mathematical model for Subjective Experience;” ITSC2018 China;

Kelley, D.; “Independent Core Observer Model (ICOM) Theory of Consciousness as Implemented in the ICOM Cognitive Architecture and Associated Consciousness Measures;” AAAI Sprint Symposia; Stanford CA; Mar.02019; http://ceur-ws.org/Vol-2287/paper33.pdf

Kelley, D.; “Human-like Emotional Responses in a Simplified Independent Core Observer Model System;” BICA 02017; Procedia Computer Science; https://www.sciencedirect.com/science/article/pii/S1877050918300358

Kelley, D.; “Implementing a Seed Safe/Moral Motivational System with the independent Core observer Model (ICOM);” BICA 2016, NY NYU; Procedia Computer Science; http://www.sciencedirect.com/science/article/pii/S1877050916316714

Kelley, D.; “Critical Nature of Emotions in Artificial General Intelligence – Key Nature of AGI Behavior and Behavioral Tuning in the Independent Core Observer Model Architecture Based System;” IEET 2016

Kelley, D.; “The Human Mind vs. The Independent Core Observer Model (ICOM) Cognitive Architecture;” [Diagram] 19 Mar 2019; ResearchGate; DOI: 10.13140/RG.2.2.29694.64321; https://www.researchgate.net/publication/331889517_The_Human_Mind_Vs_The_Independent_Core_Observer_Model_Cognitive_Architecture

Kelley, D.; [3 chapters] “Artificial General Intelligence and ICOM;” [Book] Google It – Total Information Awareness” By Newton Lee; Springer (ISBN 978-1-4939-6415-4)

Kelley, D.; “Self-Motivating Computational System Cognitive Architecture” http://transhumanity.net/self-motivating-computational-system-cognitive-architecture/ Created: 1/21/02016

Kelley, D.; Twyman, M.; “Biasing in an Independent Core Observer Model Artificial General Intelligence Cognitive Architecture” AAAI Spring Symposia 2019; Stanford University

Kelley, D.; Waser, M; “Feasibility Study and Practical Applications Using Independent Core Observer Model AGI Systems for Behavioural Modification in Recalcitrant Populations;” BICA 2018; Springer https://doi.org/10.1007/978-3-319-99316-4_22

Waser, M.; Kelley, D.; “Architecting a Human-like Emotion-driven Conscious Moral Mind for Value Alignment and AGI Safety;” AAAI Spring Symposia 02018; Stanford University CA;

Waser, M.; “A Collective Intelligence Research Platform for Cultivating Benevolent “Seed” Artificial Intelligences”; Richmond AI and Blockchain Consultants, Mechanicsville, VA; AAAI Spring Symposia 2019 Stanford

[pending] Kelley, D.; “Architectural Overview of a ‘Mediated’ Artificial Super Intelligent Systems based on the Independent Core Observer Model Cognitive Architecture”; Informatica; Oct 2018; http://www.informatica.si/index.php/informatica/author/submission/2503

Citations of ICOM Related Material

To, A.; Holmes, J.; Fath, E.; Zhang, E.; Kaufman, G.; Hammer, J.; “Modeling and Designing for Key Elements of Curiosity: Risking Failure, Valuing Questions;” Dec 2018; DOI 10.26503/todigra.v4i2.92; https://www.researchgate.net/publication/329596987_Modeling_and_Designing_for_Key_Elements_of_Curiosity_Risking_Failure_Valuing_Questions

Umbrello, Steven; Frank De Bellis, A.; – Forthcoming chapter in Artificial Intelligence Safety and Security (2018) CRC Press (. ed) Roman Yampolskiy. [Book] “A Value-Sensitive Design Approach to Intelligent Agents”; https://www.researchgate.net/publication/322602996_A_Value-Sensitive_Design_Approach_to_Intelligent_Agents

All ICOM Research References

The following material is all the references and material used as the basis of the design and implementation of the Independent Core Observer Model (ICOM) Cognitive Architecture for AGI (Artificial General Intelligence) used by our program to date.

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