What’s Existentially Wrong with Today's AI?

Real AI as a synthesized man-machine intelligence and learning (MIL) is one of the greatest strategic innovations in all human history.

It is fast emerging as an integrating general purpose technology (GPT) embracing all the traditional GPTs, as electricity, computing, and the internet/WWW, as well as the emerging technologies, Big Data, Cloud and Edge Computing, ML, DL, Robotics, Smart Automation, the Internet of Things, biometrics, AR (augmented reality)/VR (virtual reality), blockchain, NLP (natural language processing), quantum computing, 5-6G, bio-, neuro-, nano-, cognitive and social networks technologies.

But today's narrow, weak and automated AI of Machine Learning and Deep Learning, as implementing human brains/mind/intelligence in machines that sense, understand, think, learn, and behave like humans, is an existential threat to the human race by its anthropic conception and technology, strategy and policy.

The Real AI is to merge Artificial Intelligence (Weak AI, General AI, Strong AI and ASI) and Machine Learning (Supervised learning, Unsupervised learning, Reinforcement learning or Lifelong learning) as the most disruptive technologies for creating real-world man-machine super-intelligent systems.

Why We Must Be Worried About the Existential Risk of Artificial Intelligence

The list of those who have pointed to the risks of AI numbers such luminaries as Alan Turing, Norbert Wiener, I.J. Good, Marvin Minsky, Elon Musk, Professor Stephen Hawking and even Microsoft co-founder Bill Gates.

RISKS OF ARTIFICIAL INTELLIGENCE

• AI, Robotics and Automation-spurred massive job loss.
• Privacy violations, a handful of big tech AI companies control billions of minds every day manipulating people’s attention, opinions, emotions, decisions, and behaviors with personalized information.
• 'Deepfakes'
• Algorithmic bias caused by bad data.
• Socioeconomic inequality.
• Weapons automatization, AI-powered weaponry, a global AI arms race .
• Malicious use of AI, threatening digital security (e.g. through criminals training machines to hack or socially engineer victims at human or superhuman levels of performance), physical security (e.g. non-state actors weaponizing consumer drones), political security (e.g. through privacy-eliminating surveillance, profiling, and repression, or through automated and targeted disinformation campaigns), and social security (misuse of facial recognition technology in offices, schools and other venues).
• Human brains hacking and replacement.
• Destructive superintelligence — aka artificial general human-like intelligence

“Mark my words, AI is far more dangerous than nukes.” With artificial intelligence we are summoning the demon.Tesla and SpaceX founder Elon Musk 

“Unless we learn how to prepare for, and avoid, the potential risks, “AI could be the worst event in the history of our civilization.” “The development of full artificial intelligence could spell the end of the human race….It would take off on its own, and re-design itself at an ever increasing rate." "Humans, who are limited by slow biological evolution, couldn't compete, and would be superseded." the late physicist Stephen Hawking

“Computers are going to take over from humans, no question...Will we be the gods? Will we be the family pets? Or will we be ants that get stepped on?” Apple co-founder Steve Wozniak

“I am in the camp that is concerned about super intelligence,” Bill Gates

AI has the ability to “circulate tendentious opinions and false data that could poison public debates and even manipulate the opinions of millions of people, to the point of endangering the very institutions that guarantee peaceful civil coexistence.” Pope Francis, “The Common Good in the Digital Age”

When we all hear about artificial intelligence, the first thing to think of is human-like machines and robots, from Frankenstein's creature to Skynet's synthetic intelligence, that wreak havoc on humans and Earth. And many people still see it as a dystopian sci-fi far away from the truth.

Humanity has two polar future worlds to be taken over by two polar AIs.

The first, mainstream paradigm is a AAI (Anthropic, Apocalyptic, Applied, Automated, Weak and Narrow AI), which is promoted by the big tech IT companies and an army of AAI researchers and scientists, developers and technologists, businessmen and investors, as well as all sorts of politicians and think tankers. Such an AI is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the most simple to most complex.

The second true paradigm is a RAI (Real AI), or a hybrid human-AI Technology, which is mostly unknown to the big tech and AAI army. Its goal is NOT to mimic human cognitive skills and functions, capacities and capabilities and activities.

What is AAI ?

AAI "refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions". Artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience.

It may also be applied to any machine that exhibits traits associated with a human mind such as vision, language, learning and problem-solving.

Machine learning refers to computer programs that can automatically learn from training data and adapt to new data without being assisted by humans. Deep learning techniques enable this automatic learning through the absorption of huge amounts of unstructured data such as text, images, or video.

A Superhuman Narrow Automated AI without Deep Understanding, Common Sense and Self-awareness is amplifying all sorts of human biases, cognitive, social, etc., using badly biased machine learning datasets.

It is like deep learning-based video and audio generation tools to create so-called deep fakes (deep learning and fake), convincingly fabricating fake videos, fake news, all the fake world of events that never took place.

All current AI systems can be classified as narrow AI. Any software or computer program, using special technologies such as machine learning, data mining, pattern recognition and natural language processing to mechanically make decisions can be typed as narrow AI.

As such, narrow AI systems include expert systems as well as spam filters, self-driving cars and Facebook’s newsfeed.

The most sophisticated one is IBM’s Watson supercomputer, which applies cognitive computing, machine learning and natural language processing to act as a “question answering” machine, the champion on the popular game show, Jeopardy! Still, it is a type of expert system, a computer program that uses AI technologies to simulate the knowledge and cognitive ability of a human within a narrow field and particular realm. Whatever expert systems created with Watson are narrowly superintelligent AI, be it an artificially-intelligent attorney or an AI doctor.

Most narrow AI applications are much less sophisticated than Watson.

Narrowly Superintelligent AI systems, mimicking human brains, minds and bodies, are under R&D&D by big tech-bubbles, techno-powers and techno-startups:

• superintelligent expert systems,
• superintelligent language translators,
• superintelligent conversational agents,
• superintelligent digital assistance systems,
• superintelligent engineering assistants,
• superintelligent gamers,
• superintelligent traders,
• superintelligent drivers,
• superintelligent automation,
• superintelligent robotic systems, etc.

Last not least, narrow AI (weak AI) systems are to replace virtually all human jobs as far as most works, occupations and professions are narrowly specialized following the principle of division of labour, the intensive specialization in industrial societies. The concept of specialization of labor can be applied on the scale of an individual, a department, a company, an entire industry, a nation, or a region.

As Marx argued: the specialization may also lead to alienation: workers become more and more specialized and work becomes repetitive, eventually leading to complete alienation from the process of production.

The division of labour creates less-skilled workers. As the work becomes more specialized, less training is needed for each specific job, and the workforce, overall, is less skilled than if one worker did one job entirely.

In the end, the worker becomes "depressed spiritually and physically to the condition of a machine"...just to be replaced by machines and algorithms.

Globalization and global division of labour mean any job is worst divided into elemental parts, microwork of microtasks, as disaggregated work, of a large unified project completed by massive crowd-sourcing over the Internet.

Narrow AI systems are designed to replace the workers specializing in particular parts of the job, dubbed as specialists or professionals. The workers doing a portion of a non-recurring work may be called contractors, freelancers or temporary workers might stay longer on the human workforce market due to the Internet-driven sharing economy and online marketplaces of various kinds of disaggregated work.

During the industrial revolution, disaggregation replaced tradesmen (blacksmiths, carpenters, and weavers) with steam-powered machines manned by unskilled laborers and “the assembly line style of job specialization where employees are given a very narrow set of tasks or one specific task”.

Modern-day disaggregated labor market is organized via crowdsourcing internet websites or mobile apps maintained by for-profit firms acting as labor market intermediaries. It is like Amazon Mechanical Turk that offers work in a piecemeal fashion, or freelance services like TaskRabbit or Fiverr that offer temporary work to freelance contractors. Employers post jobs known as Human Intelligence Tasks (HITs), such as identifying specific content in an image or video, writing product descriptions, or answering questions, among others. Workers, colloquially known as Turkers or crowdworkers, browse among existing jobs and complete them in exchange for a rate set by the employer.

“MTurk enables companies to harness the collective intelligence, skills, and insights from a global workforce to streamline business processes, augment data collection and analysis, and accelerate machine learning development”. Amazon Mechanical Turk

These services resemble the simplest models of labor markets, with the work relationships that became traditional during the last century being largely absent: micro-payments, no benefits, no medical insurance, no unions, no career concerns, and so on. "Digital sweatshops" instead of brick-and-mortar sweatshops in the manufacturing industry exploiting workers and maintaining poor human conditions.

Most uses of microtasking services involve processing data, especially online, but manually, such as driving traffic to websites, gathering all sorts of data like email addresses or labeling or tagging data online or translating or transcribing audio clips and pictures to improve upon and test machine learning algorithms.

It is plain that all these special activities, as given by MTurk as artificial artificial intelligence for processes outsourcing some parts of a computer program to cheap labor, are better suited to AI computers and automated algorithms than humans.

What is RAI ?

RAI refers to the modeling and simulation of reality and mentality in machines that are programmed to complement humans and their actions.

The Real and True AI is overruling the Fake and Human-mimicking AI, as a way of "making software think and act intelligently in a similar way the intelligent humans think and act".

Real ML refers to computer programs that can automatically learn from any data (structured or unstructured data such as text, images, or video) in synergy with humans. Deep learning techniques enable this autonomous automatic understanding through a deep structured world-data-intelligence modelling.

The applications for AI are VIRTUALLY endless. Its technology can be applied to any sector and industries.

Now, the field of AAI is making great successes in mimicking mental activities such as learning, reasoning, and perception, to the extent that to develop systems that exceed the capacity of humans to perceive, learn or reason out any domain or subject.

With many industries looking to digitize and automate all jobs through the use of specialized robots and intelligent machinery, there is a real prospect that people would be pushed out of the workforce. Robots and automation increase productivity, lower production costs, and manufacturers may easily replace human labor with machines, making people's skills obsolete.

What's Wrong with National AI Strategies and Policies

Most national AI strategies and policies, as imaged in the picture, narrowly assume AI as AAI, "the simulation of human intelligence in machines"; "the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings". It is like the recent National Security Commission on Artificial Intelligence (NSCAI) Final Report. 

The Rise of the Human-like Machines

Capital drives productivity growth via investments in smart technology, machines, computers, and robotics for multi-factor productivity.

AAI systems and robots are becoming present in more and more situations in our life and business. They work right alongside human workers or completely replace them.

For example, Amazon uses a variety of robots in its warehouses to stock inventory, and retrieve and package items.

Tesla Motors Inc. boasts robotic and automated assembly lines for its electric cars and batteries.

AAI/Robots are replacing jobs and are a significant threat to low-skilled and high-skilled workers, blue and white-collar workers.

It is plain that smart robots and AAI automation are to take away entire categories of jobs across all industries, as the GICS identified: 11 economic sectors; 24 industry groups; 68 industries; 157 sub-industries.

So, there is a little doubt that human-like robots are first taking your jobs.

Real AI: GLOBAL HUMAN-MACHINE PLATFORM: A Digital SuperMind of Human Minds and Machine Intelligence

Human and machine powers are most productively harnessed by designing hybrid human- machine superintelligence (HMSI) cyber-physical networks in which each party complements each other’s strengths and counterbalances each other’s weaknesses.

HMSI [RealAI] is all about 5 interrelated universes, as the key factors of global intelligent cyberspace:

• reality/world/universe/nature/environment/spacetime, as the totality of all entities and relationships;
• intelligence/intellect/mind/reasoning/understanding, as human minds and AI/ML models;
• data/information/knowledge universe, as the world wide web; data points, data sets, big data, global data, world’s data; digital data, data types, structures, patterns and relationships; information space, information entities, common and scientific and technological knowledge;
• software universe, as the web applications, application software and system software, source or machine codes, as AI/ML codes, programs, languages, libraries;
• hardware universe, as the Internet, the IoT, CPUs, GPUs, AI/ML chips, digital platforms, supercomputers, quantum computers, cyber-physical networks, intelligent machinery and humans

How it is all represented, mapped, coded and processed in cyberspace/digital reality by computing machinery of any complexity, from smartphones to the internet of everything and beyond.

AI is the science and engineering of reality-mentality-virtuality [continuum] cyberspace, its nature, intelligent information entities, models, theories, algorithms, codes, architectures and applications.

Its subject is to develop the AI Cyberspace of physical, mental and digital worlds, the totality of any environments, physical, mental, digital or virtual, and application domains.

AI as a symbiotic hybrid human-machine superintelligence is to overrule the extant statistical narrow AI with its branches, as machine learning, deep learning, machine vision, NLP, cognitive computing, etc.

It presents an existential danger to humanity if it progresses as it is, as specialized superhuman automated machine learning systems, from task-specific cognitive robots to professional bots to self-driving autonomous transport.

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

Why doubts of a close reality of Superintelligent Human-AI Platform, let me remind one old story about industrial prospects of nuclear reactions. On September 11, 1933, Lord Rutherford, perhaps the world’s most eminent nuclear physicist, described the prospect of extracting energy from atoms as nothing but “moonshine.” Less than 24 hours later, Leo Szilard invented the neutron-induced nuclear chain reaction; detailed designs for nuclear reactors and nuclear weapons followed a few years later. 

Yes, We Are Worried About the Existential Risk of Artificial Intelligence

“The creators of AI must seek the insights, experiences and concerns of people across ethnicities, genders, cultures and socio-economic groups, as well as those from other fields, such as economics, law, medicine, philosophy, history, sociology, communications, human-computer-interaction, psychology, and Science and Technology Studies (STS). This collaboration should run throughout an application’s lifecycle — from the earliest stages of inception through to market introduction and as its usage scales.”