Universal AI literacy: AI brainwashing: Artificial Human Intelligence (AHI) vs. Techno-Scientific Intelligence
"You can fool all the people some of the time and you can fool some of the people all the time but you can't fool all the people all the time." A. Lincoln
Introduction
Humanity is on the grand quest for new alien intelligence, artificial intelligence or machine intelligence and learning as techno-scientific intelligence vs. artificial human intelligence,
We proceed with our educational initiative of building universal AI literacy, considering the fact that a lot of today's AI is about “spying, brainwashing, or killing”, all is under the aegis of powerful governments or military organizations or large corporations oriented toward AI advertising and marketing and profiteering.
The word “artificial intelligence” (AI) has been used to describe the workings of computers for decades, without any common or precise meaning shifting with time.
Artificial intelligence is a concept that has been the subject of increasing attention in cybernetics and computer science and engineering, cognitive science and psychology, technology and philosophy, fiction literature and movies during the last 70+ years.
The first step to create AI is to understand its conception, reified or illustrated by all its actual and potential applications, instances and examples, whether as physical hardware machines or software applications or digital platforms.
However, a long-short history of the subject shows that the concept of AI is the subject of controversy, requesting a conceptual framework to define machine intelligence answering main research questions (why, what, who, when, where, how) for three main domains: Academic, Industrial and Governmental.
AI commonly describes how to teach computers to imitate human "Intelligence?defined in many ways: the capacity for?abstraction,?logic,?understanding,?self-awareness,?learning,?emotional knowledge,?reasoning,?planning,?creativity,?critical thinking, and?problem-solving. Or, the ability to perceive or infer?information; and to retain it as?knowledge?to be applied to adaptive behaviors within an environment or context".
There are two contradictory assumptions with the mainstream AHI:
The whole domain is stuck in its paradoxes:
Artificial intelligence is Artificial Human Intelligence.
Artificial Intelligence is Machine learning.
Machine learning is NOT Artificial Human Intelligence.
In all, the AHI involves?
A rational scientific definition of AI is a non-human or non-anthropomorphic Artificial intelligence (AI), "the intelligence of machines or software, as opposed to the intelligence of humans or animals. It is also the computer science and engineering that develops and studies intelligent machines."
A real and true or scientific and factual AI is all about reality and truth and data, or science and technology, engineering and mathematics, being techno-scientific intelligence rather than human-like subjective intelligence.
The AHI's reification is the emergence of stochastic large language models (LLMs), such as GPT-4 from OpenAI, PaLM 2 from Google, Claude from Anthropic, LLaMA 2 from Meta, etc. There is an increasing understanding that its validity consists in scientific intelligence reflecting the capabilities of AHI/LLMs within the context of natural science research, as "the extent of GPT-4’s proficiency in scientific research". [The Impact of Large Language Models on Scientific Discovery: a Preliminary Study using GPT-4]
AI as techno-scientific intelligence is the power to input, learn, infer?and output information; and to retain it as?data units, structures, models and patterns and relationships (AI world knowledge and intelligence)?to be applied to interactive behaviors within an environment, virtual reality, cyber world or the real world.
It is very logical that AI as AHI is viewed today as an existential threat to the world like as human-caused climate change and environmental degradation or nuclear war or pandemics:
In all cases the same perverted logic. It is fooling or making false or misleading statements about the environmental or technological benefits of a product or practice, going as "greenwashing" and "AI brainwashing".
It is not surprising that typically the same organizations are actively involved in the same brainwashing activities.
Brainwashing: from "greenwashing" to "AI washing"
Brainwashing (mind control, menticide, coercive persuasion, thought control, thought reform, and forced re-education) is altering or controlling the human mind by certain psychological techniques, as a rigid system of reward and punishment in terms of obedience and unwillingness to cooperate,
It is aimed "to reduce its subject's ability to think critically or independently, to allow the introduction of new, unwanted thoughts and ideas into their minds, as well as to change their attitudes, values, and beliefs".
Simply, brainwashing is the use of?propaganda?or commercial ads and big mass media to?persuade?the clients or to sway?public opinion or to control the population's thoughts and feelings.
Now, what is "greenwashing"?
Have you ever asked yourself why we still pollute the planet by the fossil fuel destroying the environment and triggering climate change, soil erosion, poor air quality, and undrinkable water?
The answer is as simple as massive "greenwashing", making a product that is environmentally damaging appear to be environmentally friendly, making unsupported, false or misleading claims about the sustainability of products, services or business operations or promising green deals in dark future.
Here are some greenwashing words and terms: "green," "eco-friendly," "environmentally friendly," "natural," "sustainable", "recycled" or "carbon-neutral".
In the same ways, “AI brainwashing” involves claiming a product or service to employ AI technology which simulates or mimics or replicates human intelligence, as AHI, when it does not.
Here are some AHI brainwashing words and terms: "artificial intelligence". "artificial neural networks," "training data", "machine learning," "deep learning," "human-like AI," "generative AI", "pattern recognition software", "understanding", "cognitive computing", "chatbot", "AI chips", "AI supercomputers", "weak AI", "general AI".
AHI brainwashing commonly means that it simulate or mimics the human brain or human intelligence, with all the consequences, as what what announced in the Bloomberg press release:
Artificial Intelligence (AI) denotes the concept and development of computing systems capable of performing tasks customarily requiring human assistance, such as decision-making, speech recognition, visual perception, and language translation. AI uses algorithms to understand human speech, visually recognize objects, and process information".
Government's AHI Brainwashing
Truth can be hard to comprehend. But a dedicated pursuit of truth characterizes the true scientist, the true historian, and the true politician, or simply the true man and woman.
In the wake of the commercial overhype in generative AI, governments are racing to adopt national and transnational or international policies and develop global regulatory cooperation.
Several initiatives are underway, involving the EU, OECD, the G7, G20, and United Nations, such as the G7’s Hiroshima Process on Generative Artificial Intelligence (AI).
We have seen and to see all sorts of global, international, and national AI summits, world conferences and other fora, like as:
I don't mention the virtual generative AI conferences, as incoming AI World Barcelona or AI World Congress 2023, with keynote speakers from WPP, Telus, McKinsey, Kingfisher, etc.
There are presidents and prime-ministers, ministers, MEPs, diplomats and ambassadors among the key speakers, who are professionally ignorant about AI, be it ML, DL, Generative AI or LLMs.
This political trend was initiated by the Russian president who started politicizing about AI technology, like the nation that leads in AI ‘will be the ruler of the world’, having no idea about it, but just repeating the script.
But where he was right, it is the statement “Artificial intelligence is the future, not only for Russia, but for all humankind”.
So, all politicians, big and small, as well as all minds, from philosophers to artists and businessmen, MUST learn the ABC truths about AI, the leading future technology, and its basic truth.
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Real or True AI is completely human-friendly, complementing human intelligence, posing no risk to humanity.
Why AI is not real AI and Why the AI Brainwashing Must Be Stopped
Today's AI is a big sophisticated fakery. It is largely mathematical programming and algebraic or geometric curve fitting techniques:
fitting functions to data points, or constructing a mathematical function best fitting to a series of data points, while subject to constraints, as sampled below.
Polynomial curves fitting points generated with a sine function. Red line is a first degree polynomial, green line is second degree, orange line is third degree and blue is fourth degree
All "machine intelligence" here is in the input-output data relationships among two or more variables, like in agriculture the inverted logistic sigmoid function (S-curve) is to describe the relation between crop yield and growth factors..
There are a lot of CF Software Statistical Packages, which include commands for doing curve fitting in a variety of scenarios; as statistical R and numerical analysis programs as GNU Scientific Library, MLAB, Maple, MATLAB, Mathematica, GNU Octave, and SciPy, etc. Category: Regression and curve fitting software - Wikipedia
What is AHI is NOT Machine learning.
What is ML is NOT AHI.
AHI is NOT Real AI.
AI is dealing with pattern understanding, where patterns are regularities in the world, while ML with pattern recognition or matching in data by the curve-fitting, with overfitting or underfitting, or "overtraining" and "undertraining". It is to overcome with all sorts of techniques, as model comparison, cross-validation, regularization, early stopping, pruning, Bayesian priors, or dropout, not to fail severely when making predictions.
As Ray Kurzweil explains in his book How to Create a Mind, we perceive the world in a hierarchical manner, composed of simple patterns increasing in complexity. Pattern recognition forms the foundation of all thought, from the most primitive patterns up to highly abstract and complex concepts.
Machine learning is just a statistical method of data analysis that automates analytical model building, as involving Statistical Learning Theory, Data Analytics and Mathematical Programming.
The faster we recognize it, the less chances for the last big tech AI winter.
Organizations commit the AI brainwashing because:
The last one refers to the big tech, from Apple and Amazon to Microsoft and Meta, which ML/DL/NNs products and services have nothing with real and true AI, really being AI brainwashing products and services, as pictured below.
If to continue to misuse the term “AI,” it will likely become just another largely ignored marketing buzzword, governments and investors will stop financing the technology, the faith of the public in AI will disappear and the entire industry will suffer.
Shaping the future of human life across virtually every sides and industries, the hype around the AI technology can be much more dangerous than greenwashing or cloudwashing.
Real AI Technology: RAIT: Techno-Scientific Intelligence
Real AI is not about some advanced software tools or machine pseudo-intelligence or mimicking or simulating or counterfeiting human intelligence in machines.
It is essentially techno-scientific intelligence, being from reality and truth and data, of reality, truth and data and by reality, truth and data, with the real system architecture:
Real AI Technology (RAIT) = the environment (the real world, the internet, virtual reality, etc.) + reality modeling and simulation and interaction engine [perception (sensors, the internet of things, robotics) + knowing/conception/classification + inference/reasoning/decision making (GOFAI) + learning (ML&DL&ANNs) + actuation (actuators, robotics)] + the environment (the real world, the internet, virtual reality, etc.)
To our surprise, OECD Council on 8 November 2023 adopted the new definition of AI to be incorporated in the EU’s new AI rulebook, which is in line with our real AI approach:
“An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that [can] influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment,” reads the new definition.
Resources
Supplement
The hidden truths about ANNs, ML, DL, Generative AI and ChatGPT
The truth number 0. Artificial Neural Networks are Not Real AI, Not mimicking how the human brain works, or "learning" the rules, algorithms or models from finding patterns in historical data sets.
The truth number 1. ML is Not Real Artificial Intelligence, but predictive modeling, statistical classification algorithms and predictive data analytics.
The truth number 2. Deep Learning is Not Real Artificial Intelligence, but predictive modeling, statistical classification algorithms and predictive data analytics.
The truth number 3. Generative AI, combining various statistical algorithms to represent and process content as "hallucinating transformer NN models with attention mechanisms", is Not Real AI, but predictive modeling, statistical classification algorithms and predictive data analytics.
The truth number 4. LLMs, models with billions or even trillions of parameters, are Not Real AI, but predictive modeling, statistical classification algorithms and predictive data analytics.
The truth number 5. OpenAI's ChatGPT or Google's BERT are Not Real AI, but predictive modeling, statistical classification algorithms and predictive data analytics.
"Norvig and Russell book -and other authors-, saying that machine learning is equivalent to artificial intelligence is grossly misleading. ML is a contributing discipline of AI, just like search, reasoning, planning, decision making, natural language processing, vision, and robotics.
For instance, ML by itself cannot be intelligent because lacks reasoning, planning, logic, and doesn’t interact with the environment. ML detects patterns and performs predictions based on statistical analysis of data using math based algorithms. These algorithms are not intelligent per se...So, today’s Artificial intelligence, Machine Learning, and Data Science atmosphere is charged with false stories, inflated achievements. That’s bad for all of us. Because in the end what we receive is pseudo-science".
The recent buzz and overhype around generative AI, LLMs and ChatGPT have been driven by the simplicity of new user interfaces for creating deepfakes or digitally forged images or videos, text or graphics, audio, or simple coding in a automatic mode.
Such a ML technology is as old as "neural networks" and "generative AI".
Developed in the 1950s and 1960s, the neural networks work due to computational power and big data sets, running in parallel across the graphics processing units (GPUs) used in the computer gaming industry to render video games.
The only principal difference from Eliza, now its textual tokens or images are transformed into numerical vectors using multiple encoding techniques, while encoding the biases and prejudices, racism and deception, disinformation and puffery contained in the training data, non-legally web-scraped from the internet.