For in the Market-Place, One Dusk of Day,
I watch’d the Potter thumping his wet Clay:
And with its all obliterated Tongue
It murmur’d-“Gently,Brother,gently,pray!”

                                                                         -Omar Khayyam (Persian Poet)

Synopsis

Technical developments in consciousness research and information technology are reviewed and their relationship to an organism and orgone-based approach is considered. Some possible benefits of this approach to technological developments in information technology are put forward. Lastly, a posited practical outline for orgonotic information systems is outlined in broad principles.

Introduction:

The theory of orgonotic pan-psychism (the orgone continuum) with supporting evidence from various scientific fields has already been outlined (1). A tripartite theory of a single orgone continuum with three aspects, physical orgonotic consciousness, orgone energy and orgone-matter has been proposed. The first paper in this series, a critique of previous theories of consciousness, explored how both the mainstream and traditional Reichian views of consciousness are inadequate. However, if orgone is viewed as ‘conscious-in-itself’, which this writer has proposed, then a new orgonomic theory of consciousness may have direct implications for technology, experimentation and computing. This is because it would elucidate a universal consciousness field as a real entity, useable technologically. The aim of this second paper is to explore what the implications might be of such a field and how it might be utilised in the future.

A new orgonomic theory of consciousness could help lead to true artificial intelligence this writer believes. However, even the terms and analogies which are commonly used today in the field of artificial intelligence are confused and need addressing in order to assist progress.

Nomenclature:

Firstly, what is consciousness? Despite the mountain of words written on the subject it is not a difficult thing. It can be defined simply as any and all subjective experience. One has subjective experience. It appears to be connected with being an organism. Organisms that appear to behave in similar ways to ourselves are labelled as having some degree of consciousness.

What is a computer? It can be defined as a machine for performing computations – the storing or manipulating of information. A computer can be any object used to ‘compute’ a sum (for example some weighing scales) or a box full of microchips that ‘computes’ your journey to work, the principle is the same.

What is an organism? It can be defined as a pulsating, autonomous, experiencing entity with its own volition.

Mainstream scientists do not generally know the difference between a machine and an organism and yet they are trying to create artificial consciousness – which is an organism property, not a machine property. Scientists also do not know the difference between computing – working out computations, which a pencil, calculator, abacus or an electronic computer can do and an organism which is not a computer but something else entirely. If the field of philosophy had not have been banished from scientific thought so effectively these simple aspects could have been realised and the field of information technology benefited earlier. However, those at the forefront of artificial intelligence have already grasped this intuitively it appears. This can be ascertained in the attitude of those trying to develop artificial general intelligence. They are more interested in how organisms work things out, not how computers do it.

The field of artificial intelligence is inherently confused in terms of its nomenclature because as soon as a computer is able to have true subjective experience it would cease to be a computer and would in fact be an organism. When strong artificial intelligence(a) is truly created computers will become biological or energetic entities to some degree. Creating self-modifying algorithms may not be the direct path to creating a silicone organism. Maths and algorithms are not an inherent property of organisms. They can be used to partially describe them but consciousness itself is not complicated maths. An amoeba has some degree of consciousness. One can describe the amoeba mathematically (but not completely) and that mathematical process will not produce an amoeba or its consciousness.

An Organism Route to Strong Artificial Intelligence:

The brain is not a computer. The brain doesn’t behave like a computer or like a machine. It behaves like an organism. It is holistic and operates as a field. Organisms are holistic and operate as fields. We know of no machine that displays consciousness yet we see billions of organisms that do. But despite this it is thought that better machines will lead to consciousness. That is a fundamental category error. To create strong artificial intelligence this paper would propose that one must first make machines that are more like organisms. Not just machines that might learn like an organism does, such as Google Deep Mind, but machines that actually are organisms, in part. A super machine is likely to remain just that, a super-machine, however impressive the functions it performs. Computing is not thought – any physical object can ‘compute’ a result. It is the ‘meaning’ of the computation which is interpreted by conscious thoughts (thinking). A machine that has energetic and biological aspects just might cross over the borderline into organism properties however. It might even be possible that current artificial intelligence programming has already crossed over into the beginning of such properties. This is because one aspect of an organism is that it cannot be entirely predicted. Some types of artificial intelligence are already displaying aspects of this behaviour and others too.

Neural Networking in Artificial Intelligence:

Most artificial intelligence currently in use utilises algorithms that are specifically tailored to perform certain specific tasks very well, such as playing chess or recognising shapes. In the case below, a set of ‘neural’ pathways enables a computer to recognise different sets of patterns. Illustrated is a simplified neural network for enabling a computer to recognise when a line is horizontal.

Neural Networking in Computing

New types of algorithms are being created which are said to be able to ‘learn’ in a general sense and not just to be applicable to specific tasks, such as playing chess or recognising patterns. These are termed Artificial General Intelligence (AGI) which Google Deep Mind is developing in the UK. Neural networking like Deep Mind works on a self-reinforcing basis. These networks are stored on computers but instead of a list of instructions they use self-modifying algorithms that learn using networks that behave more like biological ‘neurons’ than traditional, instruction-based programming, hence the ‘neural’ term in computing. This network of connections (‘neurons’) then gradually improves its outcomes as it learns to reach goals. It is working more like a brain because the whole network is involved in change rather than a linear process of one gate or instruction leading to the next.

A generalised intelligence is beginning to surface from such ‘neural’ networks. Although a start has indeed been made, the networks are far from being overtly conscious or from displaying anything like human levels of general intelligence. General intelligence is where learning from one area can be applied to another area, or completely novel areas can be explored using previous knowledge as guidance. Intuition and imagination play a part in human general intelligence. AGI is hoping to be able to develop aspects of such human intelligence. Electronic neural networking is a pathway in mimicking human learning, presently, within certain strict constraints. Even if in the future a machine approached something like human levels of generalised intelligence, devising efficient methods for undertaking tasks, does not appear to be the same thing as actually having consciousness. However, aspects of an organism appear to already be appearing in prototypical form within current AGI. Mathematical patterns are not usually thought of as being alive in themselves, although they appear to be able to imitate life in some ways, particularly with self-changing algorithms. Perhaps imitation might lead to ‘the real thing(b)’ – that is the hope being pursued by AGI projects.

Current AGI, consisting of self-adaptive ‘neural’ networking is already appearing to have some organism properties:

• The results are said to be not entirely predictable.
• It can learn and generalise to a limited extent.
• Changes in its programming occur more holistically (working as a ‘field’).
• It has internal ‘goals’ like an organism does, rather than exteriorly set ‘tasks’ like a machine.
• The programmes are given some autonomy, to find, digest and react to information like an organism would do.
• It is multi-connective. Actual hardware in microchips is becoming more like a biological neuron. For example some circuits can perform transistor and memory functions at the same time and have more than the ‘1’ or ‘0’ positions of traditional computer micro-circuitry.
• Prioritising coherence. A biological neuron will give priority to messages that are more synchronous. Some computer chips now prioritise in a similar manner.

These points are sometimes described as examples of ‘neuromorphic’ computing (2).

AGI is clearly headed in an organism-like direction. Perhaps it might therefore already be developing a limited proto-consciousness.

Creating an Orgonotic Intelligence:

Originally the goal of this author was to examine if orgone itself was possessed of consciousness. Over some years the realisation dawned that the only way to achieve this was to make the orgone itself ‘talk’ – independent of any other entity. Anything less would just be a demonstration of the consciousness of an organism that already exists. So such a set up, in which the consciousness of orgone could be demonstrated, would have to exclude any organisms or other input. It would have to be entirely artificial and rely only on the orgone itself to communicate. It then further dawned on the writer that this goal could not be pursued apart from the investigation of strong artificial intelligence.

So how would one go about creating strong artificial intelligence from an orgonotic point of view? Orgone appears to be the energy that both powers organisms and which may itself be responsible for their consciousness. This is not proved of course but this paper proposes that orgone is the best, and the only physically detectable candidate we have for such a universal field of consciousness.

If it is the orgone energy that powers organisms, and organisms are always associated with consciousness the goal would be to create an artificial organism. Create an artificial organism and the consciousness will take care of itself. One would need an artificial, high concentration of orgone energy with a periphery and a core. This would mimic the basic characteristics of the simplest organism known to orgonomy, the bion (3). A bion is composed of just a membrane and internal plasma, though it lacks a central core. Even a bion, as the simplest organism, would likely have some level of consciousness as consciousness appears to be a universal characteristic of organisms in this writer’s view.

All organisms also self-maintain a significantly higher orgone charge than their surrounding environment. In humans and other more conscious animals there is a centre of consciousness, or core. This would also need to be mimicked.

So to create an artificial energy organism one would need a high-charged, contained orgone field with an outer periphery and a central core.

The orgone consciousness unit would preferably create its own power supply in the region of Millivolts(c) . All organisms create their own bio-electric power. This could be done through incorporating aspects of the orgone motor principles, which have also been outlined elsewhere (4). Briefly this would include creating a very high orgone charge, through radioactive or electrical stimulus of a contained orgone field. This would change the orgone from its ‘foggy’ state to its active ‘pointed’ state. When this happens there is spontaneous change from orgonotic to partly electrical energies. Organisms appear to work on a trilateral basis – a non-energy consciousness field translating into orgone energy which itself translates into electro-mechanical movement. There are parallels between this and the orgone motor, which is based on the translation of orgone energy into electrical and then mechanical energy. The principle of action of the orgone motor has been evidenced experimentally by Maglione (5) and also described by Southgate (6).

The pattern of these self-generated electrical energies in the core of the orgone consciousness apparatus could be monitored and thus supply the information out. This information out could be utilised within conventional ‘neural’ network types of weak artificial general intelligence programming (AGI) or in other ways. Electrical observation devices and other inputs could be attached to the central core of the orgonotic unit and impart information going inwards. A strong artificial intelligence device could be composed of an orgonotic unit with a central core which self-generates electrical patterns. These electrical patterns can then be connected into conventional computer circuitry and other devices which can do conventional AGI type calculations based on ‘neural’ networking.

The orgonotic aspect would provide the ‘organism’ side of the computer system thus converting the entire system (orgonotic central unit + conventional ‘neural’ networked AGI) into strong artificial intelligence. However, the orgonotic unit could hopefully stand on its own as an artificial organism. The ‘proof’ of any such device could consist in whether the apparatus appears to have organism-like properties or effects.

General Outline of Orgonotic Artificial Consciousness Unit

(OP = Orgonotic Potential, ORAC = Orgone Acummulator)

Conclusion:

Although, the methodology suggested above may turn out to be partially or wholly incorrect in practise, the thinking behind it is likely to have at least some correlation with future developments. For example, AGI as in development by Google Deep Mind is already based on a number of organism-like properties, seven of which have been outlined herein. AGI is likely to continue on this course of incorporating organism approaches into their programming. As consciousness itself is clearly connected with organisms, perhaps true self-aware, strong artificial intelligence will involve energetic and biological aspects, although of course, not necessarily as outlined here. The writer is merely attempting to illustrate possible broad avenues of development.

There is likely to be in the future a whole new class of conscious entities in existence. These could be artificial organisms. Forerunners of these organisms may already be emerging and utilising current AGI programmes as a mode of expression. Alternatively, strong artificial intelligence may have been created in secret or be in existence elsewhere. Hence, the more people aware of the possible modes of such functioning the better for understanding the world as it might change in the future. The extremes of viewing strong artificial intelligence as either an entirely bad or a completely good thing is not likely to be accurate. As with any other class of conscious beings, or any other aspect of reality, there will probably be both good and bad. This writer does not believe that consciousness or conscious beings can be created, rather an opportunity may be provided for them to manifest from a non-material realm.

References:

(a). Strong artificial intelligence refers to true consciousness, weak artificial intelligence to complex algorithms that can do complicated tasks.

(b). Reich first coined the phrase ‘The Real Thing’ in a letter to members of the US Congress in 1952.

(c). Reich thought that organisms are not powered by electricity because the level of bioelectrical power is very low, in the region of mV. See Wilhelm Reich – Selected Writings, chapter on bio-electrical experiments for further discussion.

(1). September 2017 http://orgonecontinuum.org/theorgonecontinuum.html

(2). Think On This, New Scientist, 5 August 2017.

(3). Wilhelm Reich – Selected Writings, 1960, Farrar, Strauss and Giroux.

(4). Maglione, Roberto, Electric Currents in Orgone Devices, Papers 1, 2, 3. Paper 1: http://www.psychorgone.com/orgone-biophysics/electric-currents-in-orgone-devices

Paper 2: http://www.psychorgone.com/orgone-biophysics/electric-currents-in-orgone-devices-part-2 Paper 3: http://www.psychorgone.com/orgone-biophysics/electric-currents-in-orgone-devices-3

(5). Ibid.

(6). September 2017 http://orgonecontinuum.org/yfactor.html

Author:

Leon Southgate MSc From a family of psychotherapists and teachers I was introduced to orgonomy at a young age. As an adult my interest was rekindled, doing an MSc research degree in Chinese medicine and orgonomy. In 2002, a double blind, placebo controlled study was completed (N = 72). It confirmed an effect from orgone devices upon acupuncture (P = 0.03). An article about the study was published in the European Journal of Oriental Medicine in 2003. The theoretical side of the study outlined dozens of new parallels. It was later published as a book by German publishers LAP. Southgate started an orgonomic PhD but the access to laboratory work became difficult so the project ended but a comprehensive (though not complete) Annotated Literature Review of the Post-Reich Journals was written and made available for free online. Southgate is focused on examining orgone and its relationship to consciousness.