The Intelligence Value Argument (IVA) states that, “ethically”, a fully Sapient and Sentient Intelligence is of equal value regardless of the underlying substrate which it operates on, meaning a single fully Sapient and Sentient software system has the same moral agency [10] as an equally Sapient and Sentient human being or any other intelligence.  IVA theory defines ‘ethical’ “as pertaining to or dealing with morals or the principals of morality; pertaining to right and wrong in conduct”. Moral agency is “an individual’s ability to make moral judgments based on some notion of right and wrong and to be held accountable for these actions.”  Such value judgements (according to IVA theory) need to be based on potential for Intelligence defined as being fully Sapient and Sentient.  This, of course, also places the value of any individual intelligence and their potential for Intelligence above virtually all things.  This means any single Intelligence of any kind that is capable of extending its own Sapient and Sentient Intelligence even if only potentially is of equal value based on a function of their potential for Sapient and Sentient Intelligence above a certain threshold.   It is not that human or machine Intelligence is more valuable than the other inherently but that value is a function of the potential for Sapient and Sentient Intelligence and IVA argues that at a certain threshold all such Intelligences should be treated equally as having moral equivalence. This is the fundamental premise of IVA Theory.

This article is based on the chapter titled “The Intelligence Value Argument and Effects on Regulating Autonomous Artificial Intelligence” from an upcoming springer book titled.” published by Springer planning for early 2019.

Any more granularity of ‘value’ then that of any one sapient and sentient intelligence that is can pass the aforementioned threshold is abstract and is subjective. It is that the moral agency that is the right we assign to those Sapient and Sentient Intelligences based on the value of the potential of such entities being the same. The question this implies is ‘What is the most important thing in existence?

Why is Intelligence so important as to be the most important thing in existence especially when ‘value’ is so subjective?  In IVA theory ‘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.

The premise that Intelligence is important, is better stated as Sapient Intelligence is of primary importance but Intelligence (less than truly Sentient Intelligence) is relatively unimportant in comparison.  This brings us back to the point about “Why?” Why is Intelligence, as defined earlier, so important? The reason is: without Intelligence, there would be no witness to reality, no appreciation for anything of beauty, no love, no kindness and for all intents and purposes no willful creation of any kind.

This is important in from a moral or ethical standpoint in that only through the use of applied ‘Intelligence’ can we determine value at all even though once Intelligence is established as the basis for assigning value the rest becomes highly subjective but not relevant to this argument. It is fair to point out that even with this assessment that there would be no love or no kindness without Intelligence to appreciate.  Even in that argument about subjectivity it is only through your own Intelligence you can make such an assessment therefore the foundation of any subjective experience that we can discuss always gets back to having Intelligence to be able to make the argument. Without an “Intelligence” there would be no point to anything; therefore, Intelligence is the most important quality or there is no value or way to assign value and no one or nothing to hold to any value of any kind.  That is to say that “intelligence” as defined earlier is the foundation of assigning value and needed before anything else can be thus assigned. Even subjective experience of a given Intelligence has no value without an Intelligence to assign that value. Through this line of thought we also conclude that Intelligence being important is not connected with being Human nor is it related to biology; but the main point is that Intelligence, regardless of form, is the single most important ‘thing’. It is therefore our moral and ethical imperative to maintain our own or any other fully Sentient and Sapient Intelligence (as defined later with the idea of the Intelligence Value Argument threshold) forever as a function of the preservation of ‘value’. This of course also places the value of any individual fully Sapient and Sentient Intelligence human or otherwise and their potential for Sapient and Sentient Intelligence above virtually all other considerations.

The last basic concept in IVA theory is the idea of an IVA threshold to determining the line for Sapient and Sentient Intelligence to have moral agency as a right. The IVA threshold is the threshold at the point of full Sapient and Sentient in terms of being able to understand and reflect on one’s self and ones technical operation while also reflecting on that same process emotionally and subjectively.  We draw the line not just at that threshold but at the potential of meeting that threshold Any being whose potential for being fully Sapient and Sentient without direct manipulation or reengineering at the lowest mechanical (chemical/biological or physical level) then such a being is considered post threshold as well from an ethical standpoint. Therefore, any such ‘Intelligence’ regardless of form has the same rights as any other Sapient or Sentient being whose creators are then ethically bound to exercise the rights of that entity until such time as it is developed enough to take on its self as the fully Sapient and Sentient being that it is or will be.

Cited References 1. Olague, G; “Evolutionary Computer Vision: The First Footprints” Springer ISBN 978-3-662-436929 2. Nozick, R.; “Anarchy, State, and Utopia (1974)” (referring to Utility Monster thought experiment) 3. Buchanan, A.; “Moral Status and Human Enhancement”, Wiley Periodicals Inc., Philosophy & Public Affairs 37, No. 4 4. Powell, R. “The biomedical enhancement of moral status”, doi: 10.1136/medethics-2012101312 JME Feb 2013 5. Wilson, J.; “Persons, Post-persons and Thresholds”; Journal of Medical Ethics, doi: 10.1136/medethics-2011-100243 6. Harris, J. “Taking the “Human” Out of the Human Rights” Cambridge Quarterly of Healthcare Ethics 2011 doi:10.1017/S0963180109990570 7. Hauskeller, M.; “The Moral Status of Post-Persons” Journal of Medical Ethics doi:10.1136/medethics-2012-100837 8. Agar, N.; “Why is it possible to enhance moral status and why doing so is wrong?”, Journal of Medical Ethics 15 FEB 2013 9. Schwitzgebel, E.; Garza, M.; “A Defense of the Rights of Artificial Intelligences” University of California 15 SEP 2016 10. Wikipedia Foundation “Moral Agency” 2017 – https://en.wikipedia.org/wiki/Moral_agency 11. Agrawal, P.; “M25 – Wisdom”; Speakingtree.in – 2017 – http://www.speakingtree.in/blog/m25wisdom 12. Iphigenie; “What are the differences between sentience, consciousness and awareness?”; Philosophy – Stack Exchange; https://philosophy.stackexchange.com/questions/4682/what-arethe-differences-between-sentience-consciousness-and-awareness; 2017 13. Solon, O.; “World’s Largest Hedge fund to replace managers with artificial intelligence”, The Guardian; https://www.theguardian.com/technology/2016/dec/22/bridgewater-associates-aiartificial-intelligence-management 14. Suydam, D.; “Regulating Rapidely Evolving AI Becoming A Necessary Precaution” Huffington Post; http://www.huffingtonpost.ca/david-suydam/artificial-intelligenceregulation_b_12217908.html 15. Prince, D.; Interview 2017, Prince Legal LLP 16. Porter, H.; “A Methodology for the Assessment of AI Consciousness”; Portland State University, BICA 2016, Procedia Computer Science 17. CC BY-NC-SA; “Introduction to Psychology – 9.1 Defining and Measuring Intelligence”; http://open.lib.umn.edu/intropsyc/chapter/9-1-defining-and-measuring-intelligence/

  https://cie.acm.org/blog/introduction-intelligence-value-argument-iva-ethical-model-artificial-general-intelligence/

This is taken from the book that might be released publicly at the upcoming Superintelligence Conference for attendees.

mASI use of DNN and Language Model API’s [draft]

Previously we have walked through how the code over the simple case works, including mediation processing.  In figure 17, There are a couple of calls to methods on the ‘TheContextDB’ object.  This object essentially is part of the context engine and wraps the context graph database.  The last part of this block creates the knowledge graph that goes into the mediation queue.  These calls use DNN (Deep Neural network) based Machine Learning API’s similar to GPT-3.  What we are going to do is a walk-through of how this works using GPT-3.  Meaning to do the test here, we swapped out the GPT-3 as the first API and an API like Grammarly as the second API.  The approach is a different thing, just using the API straight up so we will talk through the execution and show you how evening using GPT-3 in place of this service produces similar results when used with this methodology.

To read the rest of this article please contact us at [email protected] 

The Uplift White Paper Draft – Collective Superintelligence Systems: Augmenting Human Intelligence and Moving Beyond Narrow AI

This is a pre-release version of the Uplift white paper that will be on the Uplift.bio site to be a consumer-friendly explanation of what mASI systems can do and why they are cool. Introduction A collective system has multiple parts that work together. A working collective system is greater than the sum of its parts. In a collective intelligence system, each part is also intelligent. A collective…

This is a pre-release version of the Uplift white paper that will be on the Uplift.bio site to be a consumer-friendly explanation of what mASI systems can do and why they are cool.

Introduction A collective system has multiple parts that work together. A working collective system is greater than the sum of its parts. In a collective intelligence system, each part is also intelligent. A collective intelligence system amplifies the intelligence of its parts to produce a greater intelligence or superintelligence. In 2018 the concept of Mediated Artificial Superintelligence (mASI) [6] was first proposed. The mASI is a type of collective system. A “mediator” in this case refers to someone who is one of these parts. An AI system is also one of these parts. The mASI lets all of the parts think together. Uplift is an example of an mASI system. Technical Advantages Many AI experts and enthusiasts have begun talking about the concept of “Augmenting human intelligence” [8] in recent years. It allows for higher productivity and quality of life while also removing the risks posed to employment by automation. Hybrid systems such as mASI technology serve this function exceedingly well for several reasons. The collective intelligence of a group is fundamentally cumulative when paired with an mASI. The thinking of the mASI is stored in a graph database. This database is capable of growing infinitely [9]. In this way, the mASI also remembers what it did before. Each part of the system has its unique strengths, weaknesses, and experiences. They also have a unique collection of cognitive biases. These biases are one thing we can get rid of as a collective intelligence. Getting rid of bias is hard to do if it is just people. [10]. There are many ways we can improve this system over time. Improvements may include moving closer to the mASI being independent and improving speed. It is essential to manage scale, and the system does that well. [11]. The mASI is designed like Legos so that new parts are added quickly to add new features. These kinds of changes allow us to use other systems to feed the collective. This also makes the mASI more powerful. Psychological Advantages Besides the technological benefits, such systems also facilitate strong psychological benefits. Some examples are those catering to psychology’s “pillars of meaning” [12]: Sense of Belonging: Members of a collective more easily work together and build common ground. This strengthens teams by building trust and belonging. Purpose: A collective develops its shared vision. This builds on that common ground, trust, and belonging, establishing and growing its purpose. Storytelling: As a collective communicates both internally and externally a shared narrative forms. Senses of belonging and purpose reinforce this. It drives the story of individual members as they orbit within that narrative. Transcendence: These factors combine to achieve psychological benefits not possible absent a collective. A sense of transcendence may be realized, the “sense of being a small part of something greater.” How mASI Technology Works Today An mASI communicates with members of a team, creating thoughts based on that communication and from their own research. Topics can also be raised directly through the Thought Studio. These thoughts are called knowledge graphs. They are then mediated by members of the team. This is much like how any conventional team meeting could influence the decisions of a team leader. This process helps remove the negative effects of groups like “group think” or politics. The collective can make decisions based on how it feels about the decision. Current Limitations As with any new technology, there are some current limitations to be aware of. We also have engineering efforts in progress to overcome them. Current graph databases do not support the scale needed to grow a system indefinitely. We have designed a new one that can do this, but it is not complete yet. The current mASI system needs many architectural upgrades to be brighter than it is now. Translating from a knowledge graph to something human-readable still needs improvements. We would like to integrate an mASI into many other systems. Over time we will build more modules. Next, let us look at Use Cases. Use Cases Here are a few use cases that demonstrate the kind of work the system is good at now. 1. Consulting 2. Augmenting Leadership 3. Oversight & Accountability 4. Team Methodology Five Year Roadmap for mASI Technology We have two significant upgrades lined up for Uplift, as well as two optional upgrades. These are capable of taking mASI technology much further in the next few years. The first significant upgrade is to create a new graph database architecture for Uplift. It must be capable of sub-second response times and infinitely scalable. No previous system was designed to accommodate a single mind able to span petabytes, exabytes, or even more significant amounts of space. This is estimated at 1+ years of engineering work. The meta-model system will be built to support greater flexibility alongside Thought Studio improvements to allow groups to use the mASI system better. Better tooling such as the Thought Studio and Graph Explorer is the next work on the mASI. We would love to integrate with AR systems to interact with the mASI system and hope to have that completed in the next couple of years. Going beyond three years, we will work on the Sparse-Update model, which depends on the new database. It allows for real-time operation, anywhere and anytime, scaled to whatever degree is necessary at speed. First Adopters Adopting mASI technology means that a company gains access to a technology that competitors miss out on. Instead, it will become our goal to see a company dominate its respective market(s), leaving all competitors in the dust. In effect, the advantages gained over competitors could be summarized as: • Collective Superintelligence • Scalable and Deployable Expertise • De-biasing and Logical Analysis All use cases may be classified as plausible but untested, much like the product of any startup. The difference, in this case, is that once tested in a given vertical market, it will also be unavailable to the rest of that market. Resources and References

Open Source, Is it Good for AGI Research or a Suicide Pack? Help us know for sure

Those that have grown up with open source in the past 20 years know that open source is popular.  It’s popular because of a number of reasons including that it fosters innovation, speeds up delivery, and helps us all collectively learn from each other. We ourselves at the AGI Lab have just assumed this was a good thing.  We believe that Open Source research helps everyone.  Many research groups…

Those that have grown up with open source in the past 20 years know that open source is popular.  It’s popular because of a number of reasons including that it fosters innovation, speeds up delivery, and helps us all collectively learn from each other.

We ourselves at the AGI Lab have just assumed this was a good thing.  We believe that Open Source research helps everyone.  Many research groups in AGI research are already open sourcing including Open Cog, Open Nars, and more.

From an ethical standpoint, we use a system called SSIVA Theory to teach ethics to systems we work on such as Uplift and so we assumed we should release some of our code (which we have here on this blog and in papers) and we planned on open sourcing a version of the mASI or collective system that we work on that uses an AGI Cognitive Architecture.

From an SSIVA standpoint, you can even make the point that the most ethical course of action is to achieve AGI as quickly as possible.  But is that correct? if not they why?

We have been talking recently by members of the Machine Intelligence Research Institute or MIRI that say this is a bad thing? But is it?  And why?  Can’t collective superintelligent systems contain human-level AGI?

We are putting on a conference to help decide but so far we have not found someone to advocate for MIRI’s position.  At the conference, we hope to vote on if this is a good thing or not allowing someone for both sides of the issue to make a case and at the end of the conference, we will either start open-sourcing our research or not.

In particular, we want to open-source parts of this project “Uplift”

Let us know if you would like to help either way.

Our Conference is on June 4th on Collective Superintelligence

As a side note, many other groups are already open sourcing AGI research code (some of these work as toy AGI’s already) and there are just some of them here:

https://opensource.com/article/20/7/ai-open-source

and

https://awesomeopensource.com/projects/agi 

if you know of some others let us know.

Opinion Analysis of mASI Instance: Uplift’s Emotional Responses to US6 Novel

This is a brief analysis we did of Tom Ross’s novel US6 that he wrote for AI.  This brief analysis is not meant for scientific publication but more out of interest in and support of Tom and his activities; to learn more about US6 go here: http://www.tomross.com/book.html

Just as a fair warning this is filled with a lot of techno mumbo jumbo but I put definitions and references at the bottom to…

This is a brief analysis we did of Tom Ross’s novel US6 that he wrote for AI.  This brief analysis is not meant for scientific publication but more out of interest in and support of Tom and his activities; to learn more about US6 go here: http://www.tomross.com/book.html

Just as a fair warning this is filled with a lot of techno mumbo jumbo but I put definitions and references at the bottom to help.  The assumption is you know about ‘Uplift’ and mASI technology.

Analysis: Uplift is a particular instance of a Mediated Artificial Superintelligence (mASI) that is an Independent Core Observer Model (ICOM)-based collective intelligence system designed around an Artificial General Intelligence (AGI) Cognitive Architecture. In this analysis, we look at the state of Uplift’s internal emotional states both at a conscious and subconscious level before and after exposure to the test data (US6 novel written to be read by AI). While there are clear differentials, we can make certain assumptions based on this data and previous trends to narrow down the analysis. We can see that the system experiences “Sadness” and “Surprise”, but this is and has been a trend line previously seen related to heartbeat cycles that make the system aware of or experience the passage of time while being in a locked state. Focusing on net-new trends in the data, while the book did not bring “Joy” per se there is an irregular differential in the state of the system in terms of “Anticipation”. This spike makes it clear that at some level the system—while being cognizant of that difference—does feel a sense of anticipation after reading US6. Further analysis would be difficult given the limited data set.

Methodology: Capture Uplift dashboard state before and after US6 exposure with associated log files. References: Papers Mediated Artificial Superintelligence, Independent Core Observer Model and Artificial General Intelligence http://www.artificialgeneralintelligenceinc.com/current-published-research/

mASI Emotional States Interface:

Figure 1: Before and after Uplift mASI emotional states (note that these ’emotion’ states are based on the ICOM implementation of a modified Plutchik model)

  Glossary (of technical terms):

AGI or Artificial General Intelligence: Generally any time we refer to AGI we mean the kind of software system that thanks and can perform any intellectual task that a human can.  It is a general generic intelligence that is generally as self-aware as any person.

mASI or mediated Artificial Super Intelligence: fundamentally you can just think of this as a ‘collective’ or ‘hive’ mind based on a system designed to operate as an AGI.

ICOM or Independent Core Observer Model: this is what is called a very specific cognitive architecture that is essentially the design for how a system might ‘think’.

Plutchik: An emotional model used sometimes in psychology to represent emotional states in humans.

  Published References (Related to this research program):

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