Universal Science: Science + Technology + Culture: AI, ML, AGI, ASI = Trans-AI or Meta-AI

Universal Science: Science + Technology + Culture: AI, ML, AGI, ASI = Trans-AI or Meta-AI

"Science is universal and unifying as universal gravitation."- Author

“The Only Constant in Life Is Change.”-?Heraclitus.

Nothing in the world is constant but change, including science. What is a science today could become a pseudoscience tomorrow, non-science day after tomorrow or anti-science in the end of the week.

Today’s science is two fragmented and divided, with the scientists being only narrow specialists and experts, "knowing nothing about everything and everything about nothing".

Meantime, real science is universal and unifying as universal gravitation. Science is the sum of universal knowledge. Real and true science is universal science. Science grows from narrow tasks and special topics to mono-disciplinarity to pluri- multi-, inter-, crossdisciplinarity to trans-disciplinarity to universality, and vice versa, its universal laws and causal patterns are operationalized for special conditions and selected domains of interest.

I argue for the universal science (Real Science) as the universal knowledge of the world, embracing science, engineering, technology and non-science, all parts of human culture as history, literature, art and music, with all the special disciplines and knowledge fields, in all possible combinations.

Up to date the concept of universal science was interrelated with metaphysics or global ontology, initiated by Aristotle. Leibniz viewed the universal science?(Universalwissenschaft;?scientia generalis, scientia universalis) as the true?logic and a branch of metaphysics.

Due to such a holistic approach, Leibniz created the?calculus ratiocinator?and universal characteristics as a theoretical universal logical calculation framework or universal conceptual language to express mathematical, scientific, and metaphysical concepts. He was the founder of computer science and symbolic logic, anticipating mathematical logic/algebra of logic, computer hardware/software, inference engine/computer program and cybernetic systems and reasoning machines. Besides, Leibniz refined the binary number system, the foundation of nearly all digital (electronic, solid-state, discrete logic) computers, including the Von Neuman architecture, which is the standard design paradigm, or computer architecture. On the top, he assumed that the substantive knowledge of reality can be achieved by reasoning from first principles or prior definitions.

Today, universal science as enriched with special theoretical and experimental sciences is enabling the most critical innovation, artificial intelligence as universal man-machine intelligence and learning, with the inventions of general-purpose AI technology, designated as Real AI or Trans-AI or Meta-AI. In its social impact and economic importance, Real AI technology exceeds the Greatest Inventions in the past 1000 years, printing press, electricity, automobile, telephone, computer or the internet.

Meta-AI refers to a modeling and simulation of reality, its entities and phenomena, causal laws and rules, in computing machinery to effectively interact with any environment, physical, natural, mental, social or digital.

Complete computational science, as computational science, with computer science, applied mathematics and normal science, computational non-science and computational engineering, makes its conceptual core.

Western Science, Pseudoscience, Non-Science, and Antiscience

For centuries the authority of Aristotle in?dynamics, of Ptolemy in astronomy, and of Galen in?medicine?had been taken for granted . Beginning in the 16th century their authority was challenged and overthrown, and Western science set out by analysis and reductionism, observation and experiment to establish new explanatory models of the natural world.

Western Science is anti-universal by its design and methods, "resting on three pillars:

  1. René Descartes (1596–1650 CE) separated science and natural philosophy from the Church by claiming that the Universe has two aspects: non-material and material parts of the nature. By separating mind and body, Descartes formalized this outlook. Exclusion of mind (and thoughts, feelings, etc.) from the domain of the material world, prompted Descartes to claim that the world operated like a machine using deterministic and mechanistic principles. As a logical extension, Descartes proposed that the world (like machines) could be understood by taking its pieces apart (i.e., by isolating and focusing only on a specific aspect of the nature) to study them.
  2. Galileo Galilei (1564–1642 CE) promoted a mathematical and quantitative approach to Western Science by negating the existence of qualitative aspects of the nature. Galileo claimed that feelings, emotions, thoughts, etc. don’t exist independent of the material aspects of the nature.
  3. Francis Bacon (1561–1626 CE) developed the empirical method that suggested that scientific knowledge could be gathered only by careful observation of particular events related to a specific part of the nature. Bacon suggested that objective experiments are needed to observe specific aspects of the nature. Evidence collected via these experiments helps one to become surer about the cause-and-effect of the events in nature. Bacon suggested that one could generalize the observations from experiments into universal propositions (or a concept / physical law) using inductive reasoning. Unlike Bacon, Descartes had suggested starting with established facts and using deduction to derive knowledge.

The above three, therefore, laid the foundations of the materialistic, mechanistic and reductionist evidence-based western science. Experimental and empirical approach, together with induction and deduction, became the fundamental building blocks of the western science".?

In accordance with Britannica, "science is any system of knowledge that is concerned with the physical world and its phenomena and that entails unbiased observations and systematic experimentation. In general, a science involves a pursuit of knowledge covering general truths or the operations of fundamental laws".

Its key feature is the scientific method, as involving characterizations of the unknowns/unsolved problems (observations, definitions, and measurements of the subject of inquiry), making conjectures (hypothetical explanations of observations and measurements of the subject), deriving predictions (inductive and deductive reasoning from the hypothesis or theory), and then carrying out experiments or empirical observations based on those predictions.

The algorithm of scientific inquiry implies the "process by which scientists make predictions, observations, and inferences; develop, carry out, and critique investigations; gather evidence; propose explanations and conclusion based on evidence; and communicate findings to others".

Now, in accordance with the Oxford English Dictionary (OED), pseudoscience is

“A pretended or spurious science; a collection of related beliefs about the world mistakenly regarded as being based on scientific method or as having the status that scientific truths now have.”

A?non-science ?is an area of study that is not scientific, especially one that is not a natural science or a social science.?

Pseudoscience consists of statements, beliefs, or practices that claim to be both scientific and factual but are incompatible with the scientific method.

Antiscience is a set of attitudes that involve a rejection of science and the scientific method; science is not accepted as an objective method that can generate universal knowledge.

As models of scientific inquiry go everything, Classical model; Hypothetico-deductive model; Pragmatic model; Invariant explanation, but the causal model of the world.

Today's empirical science is downgrading to pseudoscience with all the prospects of degenerating to antiscience, the?rejection of universal science and causal scientific method,?and its replacement with statistics and ad hoc hypotheses, often for financial, commercial and political gains.

This all comes from the fragmentarity, ignorance, narrow specialization, reductionism, scientism, and extensive commercialization of today’s science, failing to pursue universal knowledge.

Science is thus becoming antiscience, the "denial of universality and... legitimisation of alternatives", and that the results of scientific findings do not always represent any underlying reality, but can merely reflect the ideology of dominant groups within society.

One of the worst ramifications is still the same as mentioned by I. Asimov, ignorance mixed with scientific illiteracy at all levels of human society, including experts and specialists, academics and researchers, as well as top-level politicians.

There is a cult of ignorance in the United States, and there has always been. The strain of anti-intellectualism has been a constant thread winding its way through our political and cultural life, nurtured by the false notion that democracy means that?"my ignorance is just as good as your knowledge".

Isaac Asimov , "A Cult of Ignorance",?Newsweek, 21 January 1980

As a ramification of today's science, a large percentage of global population lacks scientific literacy, not adequately understanding scientific principles and?method, having corrupted worldviews, if any at all, widely believing in statistics, religious mythology, paranormal phenomena or geo-centric and flat Earth theories.

Rejection of real science and holistic medicine has become a key feature around the world, making the global pandemics a new normality…

The demarcation between science, antiscience and pseudoscience have philosophical, economic, political, historical, scientific and practical implications, as in the case of health care, expert testimony, environmental policies, and science education .

Distinguishing scientific facts and theories from anti-, pseudo-scientific beliefs, such as those found in climate change, astrology, alchemy, alternative medicine, occult beliefs, intelligent design, and creation science, is part of science education and literacy.

Anti-, pseudo-science can have dangerous effects, as losing the public trust in science and technology, mass vaccine global policy to the prejudice of the natural immune system, leading to deaths and ill-health and infertility. Anti-, pseudo-scientific ideas about racial and ethnic and religious classifications have led to religious wars, racism and genocide.

Modern science is a huge collection of different people with different personal biases and technical biases and educational and?cultural biases.

Besides, human life is full of stupid things, predilections and prejudices, decisions, acts and doings. But there are unharmful, harmful and lethal stupid biases. The range of stupidity is numberless, from the highly academic stupidity of simulating human intelligence/brains/mind/behavior in machines to the geopolitical?tension between NATO and Russia, where both sides are stuck in their socio-ideological partialities, preconceptions, prepossessions, predilections, presumptions, preferences, pretensions, or biases to the prejudice of the whole world.?

In toxicology, the median?lethal dose (MLD) as an indication of the lethal toxicity of a given toxin, radiation or pathogen, as the Omicron variant, is based on the standard person concept, not existing in reality. As a result, we have the never-ending pandemic, as figured below:

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Real Science is an OPEN SYSTEM OF ALL FIELDS

SCIENCE MUST BE OPEN TO ALL AND EVERYBODY, INCLUDING HOW AND WHICH RESEARCH PROBLEMS SHOULD BE PUBLICLY FUNDED.

Science should and must be publicly debated on the internet for several reasons:

  • Science is a public enterprise with the public funding.
  • Science is an open world knowledge, embracing traditional knowledge, experimental science, theoretical science, nonsciences, as pure logic and mathematics, social sciences and the humanities, arts and literature and citizen science.
  • Science is not a fragmented mono-disciplinary activity, as most of scientific R & D are organized today. [ERC is wasting up to EUR 2 billion annually for low-quality narrow topics as parts mono-disciplinary projects with no general scientific or social or economic effects. It is plain and clear all the competition must be transparent and open to the general public].
  • Scientists suffer from the Dunning-Kruger effect,?a type of cognitive bias?that causes narrow-minded experts and specialists to overestimate their knowledge or ability, particularly in areas with which they have little to no experience. The bottom quartile of performers tend to see themselves as being part of the top two quartiles.
  • Science is a pluri- ( multi-, inter-, cross-) and trans-disciplinary research and development .

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Research Topic: Discovery of a particular drug

Host discipline: Pharmacology

Complementing disciplines: Biochemistry, Chemistry, Medicine.

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Research Topic: Biologically Inspired Engineering

Host disciplines: Engineering, Material science

Complementing disciplines: Biology, Zoology

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Crossdisciplinarity is concerned with the study of a research topic at the intersection of multiple disciplines, and with the commonalities among the disciplines involved.

Example

Research Topic: Biologically Inspired Engineering

Host disciplines: Engineering, Material science

Complementing disciplines: Biology, Zoology Interactions are very strong with commonalities in the way biological systems and engineering counterparts are viewed.

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Transdisciplinarity is concerned at once with what is under, in, between, across and beyond all the disciplines with the goal of understanding the present world under an imperative of unity of knowledge.

Example

Research Topic: Synthetic Biology, Cognition, Artificial Intelligence

Trans-Science = Science + Non-Science

Transdisciplinary science is about studying, modeling and simulating all reality, with its causality, nature, humanity, mentality, and society, by applying reasoning, observation, experimentation, and digital technologies.

Trans-Science involves a pursuit of world's knowledge covering general truths or the operations of fundamental laws by integrating all science and non-science.

It is key source of information is the real science as the sum of universal knowledge, the world's information as coordinated and systematized.

Modern science ?is reduced to an empirical science where "knowledge is ONLY or PRIMARILY based on sensory experience" and "knowledge is tentative and probabilistic, subject to continued revision and?falsification ".

Such science is just "any system of knowledge that is concerned with the physical world and its phenomena and that entails unbiased observations and systematic experimentation" .

It is typically divided into three major branches that consist of the following:

  • the natural sciences (e.g., biology, chemistry, and physics), which study nature in the broadest sense;
  • the social sciences (e.g., economics, psychology, and sociology), which study individuals and societies;
  • the formal sciences (e.g., logic, mathematics, and theoretical computer science), which deal with symbols governed by rules.

Disciplines that use existing scientific knowledge for practical purposes, such as engineering and medicine, are described as applied sciences.

Empiricism is stating that knowledge comes only or primarily from?sensory experience. Modern science excludes as a Non-Science both the philosophical sciences, and the formal sciences, as well as mathematics as sciences as they do not rely on empirical evidence.

Non-science includes all areas of study that are not science . It encompasses the study of abstract concepts, pure mathematics and the humanities, including:

history, with the history of science,

the language arts, such as linguistics, specific languages, and literature,

philosophy, ethics, and religion,

art, including music, performing arts, fine arts, and crafts.

Non-sciences offer information about the meaning of life, human values, the human condition, and ways of interacting with other people, including studies of cultures, morality and ethics.

It is plain and clear, data or information or knowledge have real value in the context, in its wholeness and totality, if only coordinated and systematized and organized.

Due to an exponentially increasing fragmentarity and narrow specialization of scientific R & D, today's science is broken and disjointed consisting of small disconnected parts, losing its mission to pursue a unified knowledge and understanding of the world (natural and social world and digital world) following a systematic scientific methodology.

Today's science is marked with all the indicators of pseudoscience

Use of vague, exaggerated or untestable claims: Lack of understanding of causality, basic and established principles of the world

Over-reliance on confirmation rather than refutation: Assertion that claims which have not been proven false must therefore be true, and vice versa; appeal to reductionism as opposed to holism

Lack of openness to testing by other experts

Absence of progress: Statistical significance of supporting experimental results does not improve over time and are usually close to the cutoff for statistical significance. If statistical significance does not improve, this typically shows the experiments have just been repeated until a success occurs due to chance variations.

Personalization of issues: Tight social groups and authoritarian personality, suppression of dissent and groupthink can enhance the adoption of beliefs that have no rational basis. In attempting to confirm their beliefs, the group tends to identify their critics as enemies.

Use of misleading language: Creating scientific-sounding terms to persuade non-experts to believe statements that may be false or meaningless.

Here are some selected research topics funded by ERC Advanced Grants: 209 top researchers awarded over €500m :

What is bedouin-type Arabic? The linguistic and socio-historical realities behind the millennia-old dichotomous concept of nomadic and sedentary people in the Middle East and North Africa

Beyond solving static datasets: Deep learning from streaming data

What does it take to build an artificial virus?

As advanced AI systems and ML models show, such an overspecialized science with its narrow-minded scientists is easy to be replaced by over-specialized DNNs algorithms, like with the narrow?AI AlphaFold ?predicting 3D models of protein structures.

It is becoming cheaper just to train deep learning algorithms running on artificial neural networks in all the gamut of overspecialized fields, from?Acanthochronology to Zythology


Trans-Science and Trans-AI Technology

One can use automatic feature selection techniques of deep machine learning (DNNs) to cluster all the key concepts of fragmented knowledge fields:?physics, chemistry, biology, psychology, sociology, economics, archaeology, anthropology, medicine, pharmacology, computer science, artificial intelligence, philosophy, ontology, metaphysics, ethics, aesthetics...

As a result, each branch of science will come with its foundational terms, which could be classified further up, with a few top classifications or meta-categories, as?

  • Everything/reality/the world/universe/metaverse
  • Entity/thing/object/individual/item
  • Substance/object/matter/body/mind
  • State/property/feature/attribute/quality/quantity/variable/
  • Change/action/process/event/computation
  • Relationship/causality/time/space/correlation/communication/function
  • Data/information/facts/knowledge/intelligence (categorical data, ordinal data, interval data, ratio data, cardinal data).

This is?a scientific, inductive, statistical or empirical way to generate the reference metascience with its fundamental categories, named as the standard ontology/scientific meta-physics.

It could be visualized as the Venn diagrams?depicting how sciences relate to each other against an overall backdrop, universe, data set, or environment, which is the standard ontology.

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Trans-Science is the product of data sets union of all knowledge fields, scientific or non-scientific, including any possible combinations and relationships, interdisciplinary or multidisciplinary. Its core is the product of data sets intersection or overlapping of all knowledge fields, comprising meta-scientific, meta-physical categories.

To remind, metaphysics?is about the nature of reality. It includes ontology, the study of being, and epistemology, the study of knowledge. Metaphysics is concerned with examining our most basic assumptions about what is, was and will be and how we can come to know it. Ontology deals with the nature of categories of reality, being and existence, while epistemology deals with our knowledge of these categories.

Again, drawing on pattern recognition and computational learning theory, Meta-ML is dedicated to the study of problem-solving by computer programs in general, enabling computers to reason about the world and learn from data, to effectively interact with any realities, physical, mental, social, digital, or virtual.

The Meta-AI's core is complete computational science, scientific computing or scientific computation, as computational science, with computer science, applied mathematics and normal science, computational non-science or computational engineering.

The CCS must be the kernel of real AI and true ML, as it is involved in the development of models and simulations to understand the world, effectively interacting with its any realities and domains, material or mental or virtual, and its natural, mental, social or digital systems.

And since it is concerned with the design, implementation and use of mathematical and computational models to analyse and solve scientific, engineering and humanities problems, with the use of computers to perform simulations or numerical analysis of systems or processes.

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There must be included both science and non-science as well as engineering.

Complete computational science is the last mode of science, observations, experimentation, theory, and simulation.

Again, today's AI of ML/DL/ANNs is just the applications of predictive computational science, operating both with numerical computation and symbolic computation or computer algebra, including symbolic computation in statistics, equation solving, algebra, calculus, geometry, linear algebra, tensor analysis (multilinear algebra), optimization.

Last not least, the Trans-AI modelling should consist of the following necessary features and functions:

  • Prime Assumptions:?prior knowledge,?the basis of our knowing, understanding, or thinking about the whole world or a domain problem (primary causes, principles and elements).
  • World Model:?the representation of our world's views and key assumptions in a way that we can reason (i.e., conceptual, ontological/causal, logical, scientific, or mathematical/statistic models, as an equation or a simulation or the neural network model of pictures and words).
  • World Data:?what we measure, calculate, observe or learn about the real world (facts and statistics; variables and values).

Conclusion

Transdisciplinary Research and Development is ignored and left unnoticed by the political institutions, educational systems, and funding agencies.

Facing exponentially accelerating changes and complexity of the world, we need Transdisciplinary Science and Engineering (Trans-Science), as including Empirical Science, Traditional Knowledge, Pseudoscience, and Non-Science, namely:

Philosophical sciences

Natural Sciences

Social Sciences

Formal and Mathematical Sciences

Engineering sciences

Computing science and engineering

The Humanities, Art, Literature, Religion

Trans-Science is about the world’s knowledge of all possible forms and kinds of reality:

Meta-physical reality

Physical/Chemical/Biological reality

Mental reality

Social Reality

Information reality

Digital Reality, AR, VR, ER, MR, Metaverse

The most valuable scientific discoveries could come from the Trans-Science R &D as the Meta-AI or Trans-AI Technology.

Trans-AI or Meta-AI is to enable the real science and disruptive emerging technologies:

AI/ML/DL, and Emerging Nano-, Bio-, Robotic, Cognitive and Neuro-Technologies

Digital Reality, VR/AR and Metaverse Technologies

Real Superintelligence and Trans-AI Technology

Man-Machine Superintelligence and Trans-human Technology

I-World of Meta-AI Technology

Resources

Global Ontology Intelligent Technology: from Narrow/Spurious AI/ML/DL/NNs to Global/Real/Causal/General AI

Trans-Science and Technology, Scientific ToE, Trans-AI and I-World

TRANSDISCIPLINARY ARTIFICIAL INTELLIGENCE AS FUTURE INTELLIGENCE: The Trans-AI Platform of AI/ML/DL/NNs

Causal Learning vs. "Deep Learning" : on a fatal flaw in human knowledge and machine learning

Engineering a Symbiotic Superintelligence by 2025: meeting Musk's concerns for $100 billion

Meta AI or Trans-AI as an emerging Machine Intelligence and Learning trend

https://www.dhirubhai.net/pulse/why-has-artificial-intelligence-gotten-bad-name-ai-azamat-abdoullaev/?published

How Causal Revolution is shaking up Science and Technology

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