The book The Age of AI and Our Human Future is a graduate school level text. The Age of AI is the future, and it’s coming way too fast. The human race has never been more challenged. We are all about to make some huge decisions.
It is almost a magisterium for human life in the Fourth Industrial Revolution age. It is written by thought leaders of the highest-level, each in their respective fields.
The first author is Henry Kissinger the former Secretary of State and NSC advisor to two US presidents, a philosopher and Nobel Peace Prize Laureate. At age 98 he has seen it all and done it, and remains an international counselor to politicians and business magnates.
The second author, Eric Schmidt consolidated Google into the cutting edge technology giant that it is today. In this role he is a sought out counselor and business mogul.
The third author is Daniel Huttenlocher – the inaugural Dean of the MIT College of Computing. It is the place where AI is reinvented and recreated on self-teaching algorithm development and data aggregation from the global network platforms and the internet that occur 24/7 at a neck breaking pace.
This compendium though incomplete, has more authors, contributors and editors. Schuyler Schouten, a former White House legal counsel. Meredith Potter is a contributor who augments Kissinger’s intellectual pursuits she drafted, edited the texts and made the chapters flowing clearly and seamless. These and other editors made this textbook intellectually rich, informative, and easy to read.
The Age of AI introduces the reader to the occurring changes we experienced in our society today. You are about to encounter many topics that involve the future in its continuing evolution. Every high school student is adapting to the new classroom intellectual reality.
Here are two points to consider.
First, the technology that this text discusses is not available in your community college courses or on other educational websites.
Second, whenever you visit this field knowledge and course material for writing assignments—you may need more than just 15-20 pages. The form of the internet search and browsing is different than an online social group activity. The internet has changed what it means to be educated. Humanity is continuously learning.
This kind of mindset change is concerning to us and the future winning generation.
The age of artificial intelligence is here. The book was not written only for geeks and software engineers. It’s a good core class for every MBA program. It introduces aspects from the humanities in every chapter. It has biblical flair to it. It stitches history and augurs the future, all interwoven in every chapter.
The idea that current programming code automates some jobs, such as translation, give best travel directions or loan prediction, has been proven by computer scientists. We embrace intelligent algorithms to open new opportunities for people with disabilities. Assistive programs will evolve and eventually replace us as we know it. Additionally, we will encounter many scenarios where we may not be sure of what is exactly happening on the other side of the screen.
As the digital world evolves, so it elevates the level of human intelligence. You feel that I like this book about Artificial Intelligence and our future.
So let’s get started with the book.
The Age of AI book has seven chapters. I studied this book thoroughly while writing the book review. I review and comment on each chapter, but not always in their published order. The book is readable even if it’s read in any chapter order. To be honest I studied the book chapters at my own order.
Note: To act properly - whenever I quoted from the book’s text I used quotation marks.
The contents of the first and second chapters are historical and philosophical in nature.
The second chapter is titled How We Got Here.
History is an instructive realm. Particularly fascinating is the evolution of human thought – who we are and how we got here. The Dark Ages were just that - dark. When the printing press was invented in the mid-15th century, knowledge, education and understanding of the world, launched the periods of Enlightenment and the Age of Reason.
At the 15 to 17th centuries knowledge became more available and started to circulate in languages other than Latin. The Christian church lost the monopoly on understanding the world. People started to understand Divinity on their own terms. It became a known fact that there people and large nations in Asia – China, India, and Americas that think differently. Geography, sea-faring navigation, chemistry and physics were developed.
The philosophy of the Age of Enlightenment required freedom of thought. What is real and what is reasonable were subject of intellectual, philosophical debates.
When knowledge accumulated and committed to printed books, the first Encyclopediae was assembled by Denis Diderot during the years 1751-1772.
It had 75,000 entries. So much knowledge. Neither the State nor the Church liked it. They lost control over the body of knowledge territorial colonies.
The radical ideas of personal freedom gave birth to the French Revolution. The Prussian King adopted the armed reason as a cause of war and started the Seven Years War in Europe.
Conclusion - free knowledge and encyclopedias have unintended consequences – such as – personal freedom and sciences.
At the beginning of the 20th century Einstein revolutionized physics. At about the same period Niels Bohr came up with the Quantum Theory and Werner Heisenberg with the Uncertainty Principles. The point is that human knowledge kept evolving in a faster pace. The World Wars did not stop the evolution of ideas and knowledge.
During WWII it became certain that - knowledge is real power! Knowledge is also - physical – It is either constructive, or destructive.
By end of WWII, atomic weapons were developed and deployed. The weaponizing of nuclear energy was followed by peaceful use of nuclear energy for generating - clean energy… We all love clean energy… All of us need electricity to power your computers…
The amount of accumulating knowledge required the perpetual development of powerful and faster computers. The computers were mechanical to begin with, and then data was digitized. All manual tasks from half a century ago are now digitized.
“As information is contextualized it becomes knowledge. When knowledge compels convictions it becomes wisdom… As online information has exploded we have turned to software to help us sort it out, refine it, make assessments based on patterns and guide us.”
This is where AI enters our lives.
The Third Chapter titled “From Turing to Today” gets geeky. Any reader who got this far will understand it.
In 1950 Alan Turing proposed that in order to measure intelligence we have to assess the external behavior – the output of the computers.
“...If a machine operated proficiently that observers could not distinguish its behavior from human’s, the machine should be labeled intelligent.”
It is known as the Turing Test.
In May 2020 an AI platform was released. It was named GPT-3. This name is an acronym for generative pre-trained transformer, 3rd generation.
It can in response to a prompt generate a human readable, sensible text. How so?
Using texts on the internet, GPT-3 is trained to generate realistic human text. GPT-3 has been used to create articles, poetry, stories, news reports and dialogue using just a small amount of input text that can be used to produce large amounts of quality copy.
“Given a partial phrase it can produce possible completions. Given a topic it can produce a paragraph, and given a question it produces possible answers.”
And more. It can draft an essay… It can write poetry… Wow.
All this is done provided that there is information about the subject matter on the internet.
So GPT-3 is an information gatherer and a language model. Better yet, GPT-3 trains itself and becomes more efficient with increasing iterations.
Preceding this development in 2017, Google’s research team developed an AI chess playing program branded as Alpha Zero. This program was given the rules of chess and the chess board game learned to play chess competing against itself. It played against itself and while doing so it trained itself to play chess more skillfully. The chess playing AI developed strategies unknown to human chess players heretofore.
Yes, we are dealing now with Machine Learning. The machine trains itself.
At the heart of the AI capability to learn are specific algorithms. In Machine Learning, the algorithm is a set of steps and rules given to an AI program to help it learn on its own how to improve imprecise results.
The algorithm requires vast amount of data which it gathers from the internet or from its past experience.
Well, unless it plays chess against itself. In that case it performs millions of chess games and chess maneuvers.
Machine Learning algorithms technologies are making progress in research labs out there, right now - as I type and as you read my words.
Better yet, and this is significant - “The modern AI algorithms measure the quality of outcomes and provide means for improving those outcomes enabling them to be more proficiently learned rather than directly specified”.
The AI process has two phases: first phase is the training. Next phase is the AI quality measurement and improvement - algorithms evaluate and amend its model to obtain quality results. The AI reaches conclusions by the model it develops and in response to reward function that human programmers specified.
This is mind boggling.
The concept and construct of these algorithms were inspired by the anatomy and physiology of the human brain.
The most significant progress was made when AI facilitated transcription and translation of texts. Meaningful interlingual translation was enabled by mimicking deep neural networks. The generative algorithms became transformers. And transformers can read the text from left to right (as in English), or from right to left (as in Hebrew).
Are you still with me?
OK. So what really is a transformer?
A transformer is a deep learning model (algorithm) that adopts the mechanism of self-attention, differentially weighting the significance of each part of the input data. It is used primarily in the field of natural language processing (NLP) and in computer vision (CV).
Transformers do not necessarily process the data in order. Rather, the attention mechanism provides context for any position in the input sequence. For example, if the input data is a natural language sentence, the transformer does not need to process the beginning of the sentence before the end!
Attention mechanisms let a model draw from the state at any preceding point along the text. The attention layer access previous states and weights them according to a learned measure of relevancy, providing relevant information about far-away items.
OK. Let’s parse it in spoken English.
This Generator that is Pre-trained to create language has this clever Transformer that reads from the start to end, or from the end (of the sentence) to the beginning and assign weight to the content context of the sentence in its context.
Here is what happens. Buckle your seat belt…
The generator can create text, or images. Give it an outline and key words and it will write a story.
If a generator can create a story it can also create a false story – deep fake stories -that can’t be distinguished from reality. In that case you need an algorithm that will distinguish and discriminate which ideas are realistic or fake.
Now we have a struggle between Generative Adversarial Networks (GAN).
I call this scenario - The Wars of The AIs.
This Machine Learning is now yesterday’s news. Most of it already happened in 2017.
AI is used for more than games and story tales. Google’s Deep Mind project built an AI that temperate the energy by 40% greater efficiency in Google’s data centers. There the AI performs better than humans. But it takes a human to train the AI to meet its whims and wishes…
There is a danger in this clever AI model. Personalizing the output can bias it towards certain sources and away from other sources. In plain English we call it censorship… Censorship by AI…
A user does not know how the AI reached its conclusion and selected its offerings. Even the programmer loses control on the over the end-results. Yes. AI may make mistakes but its owners-designers have no idea why.
The AI does not reflect on its results. It processes the data that was handed to it and in line with the instructions it received.
AI has no common sense. AI has no feelings, has no regrets and no grudges.
The continuous evolution of AI depends on three constraints. Those are the human talents that write (engineer) the parameters of the AI. Second are the objectives - of what it is to optimize. And third, AI processes only what it designed to recognize. In other words AI does not write its own code as of yet.
Example. Since this book went to print DeepMind, the subsidiary of Alphabet/Google reported the existence of a new and improved artificial intelligence algorithm that can perform a wide range of language tasks—from reading comprehension to answering questions on a broad range of subjects—better than any existing similar software.
DeepMind’s language model, which is called Gopher, is significantly more accurate than these existing ultra-large language models on many tasks, particularly answering questions about specialized subjects like science and the humanities, and equal or nearly equal to them in others, such as logical reasoning and mathematics, according to the data DeepMind published.
Gopher is smaller than other ultra-large language software. Gopher has some 280 billion different parameters, or variables that it can tune. That makes it larger than OpenAI’s GPT-3, which has 175 billion.
AI research, development, and commercialization happens mostly in the US and China. Unfortunately, one of this book’s short-comings is assessing and scoring AI in China.
A report in the Hong Kong daily paper South China Morning Post, on November 20, 2021 describes advances in a powerful exascale supercomputer in China that has made a massive increase in its Artificial Intelligence performance.
Aided by a breakthrough in memory management technology, the New Generation Sunway supercomputer recorded a 75,839-fold boost in handling data for machine learning. The overall performance of the computer increased 88 times when processing some of the most challenging AI-related tasks.
The authors of this book concede that “the state-funded Beijing Academy of Sciences has developed a generative language model with 10 times as many weights as GPT-3.” This is still 104 times fewer than the estimated of the human brain synapses. (There are estimated 125 trillion synapses in human brain).
A just published report, from the Harvard Kennedy School of Public Policy concludes that in AI, China is already a “full-spectrum peer competitor” of the US, according to the Harvard report, citing a quote from former Google chief executive Eric Schmidt. It indicated that China is laying the intellectual groundwork for a generational advantage in AI.
The report indicated that in deep learning – AI’s hottest subfield – China has six times more patent publications than the US. It cited an assessment of the Allen Institute for Artificial Intelligence, which forecast the US to fall to second place in the top 1 per cent of most-cited AI papers by 2025.
Fact: In 2019, Chinese universities produced 49,498 PhDs in STEM fields, while U.S. universities produced 33,759. Based on current enrollment patterns, the report projects that by 2025 China's yearly STEM PhD graduates (77,179) will nearly double those in the United States.
That’s the end of geek-speak. From here on we’ll talk Tik Tok stuff…
Chapter 4 in the book deals with Global Network Platforms.
Those are the likes of Google, Meta (Facebook), Amazon (Web Services) and the thousands of Social Media platforms that utilize AI and algorithms to read our thoughts and sell us their “stuff” and rake a profit. I bet that this chapter was authored by Eric Schmidt – the former CEO of Google.
Google, Facebook Amazon and their likes, won’t be today who they are, without AI and their notorious algorithms.
Social Media is all around us – web searches, streaming videos, dating online, ride-sharing, job hunting, car navigating, political advertising, fund raising, and… shopping. All make use of AI and algorithms.
The SM network platforms deliver valuable daily services and products that provide services to their users by aggregating the users in large numbers on national and global scale. The network’s platform utility value grows as its attractiveness grows when additional users join it.
All these global networks rely on AI. All the major global networks are now geopolitically significant. Commercial competition between global networks affects geopolitical and diplomatic considerations. Materials in a global network may be considered disinformation in some certain country. Freedom of expression in one country is defamation in another country.
The common example is Facebook with its billions of users. Because of these billions of users and many billions of viewers “community standards” were created. But who are the humans that can monitor those community standards?
Here comes the AI to help. AI does the analysis to determine which content is within the community standards. From my user experience; can human supervisors always explain why certain experience was removed? AI has a mind of its own.
On another front in 2015 Google incorporated AI to the search process with improvement of the quality and usability of the search results. That accomplished but at the same time the developers can’t always explain why a particular page ranks higher than another page… AI has a mind of its own.
One well-guarded, secretive global network platform is Amazon that turned into Amazon Web Services. Amazon is influential to its customers because of its clever algorithms that analyzed my shopping needs and anticipates what I, the shopper, want to buy, and keeps remind me what else I want to buy. Amazon is not shy to state that” based on my previous purchases I may be interested in” buying today this other widget or book… No wonder that Amazon turned also to be a provider of digital web services such as cloud computing and hosting smaller platforms.
One thing of note. Amazon is not mentioned in this book. Amazon is not listed in the index at the back of this book. Wonder why?
So this book is not a perfect compendium….
The author of Chapter Four on Global Network Platforms proposes a simple explanation of the naked truth that we are all aware of, as users of Google, Twitter, Facebook, Amazon, Netflix, Tik Tok and the other popular SM platforms.
It is known as the positive network effect.
“Positive network effect occurs for information-exchange activities in which the value rises in this manner, success tends to produce further success and a greater likelihood of eventual predominance. People naturally gravitate toward existing gatherings which lead to larger aggregations of users.
For network platform relatively unconstrained by borders, this dynamic leads to a broader, often transnational geographic scope with correspondingly few major competing services.”
This quote deserves to be studied, internalize and learned from. My guess is that this chapter was written by, or mostly written by Eric Schmidt who led Google for 10 years. He walked the talk. Traders in international stock exchanges know it best.
On global network platforms we watch the operation of nonhuman intelligence at global scale.
Presently at the end of 2021, after two years of pandemic caused social distancing AI was placed in certain networks in a critical and essential resource substitute maintaining the social glue of society, political governance, and maintenance of business continuity in terms of remote office work. I am referring to the rise of Zoom.
Yet the users of Zoom and similar platforms have no idea where and when AI is managing the video conferencing processes.
Zoom owners and operators gained access to the users’ personal information and faces and the interiors of their kitchens, studios or bedrooms. Same holds for Facebook. Facebook probably holds the facial images of a billion people on planet Earth. Maybe more.
So the global network platforms possess and exercise social and political influence. They bear political influence that affects the most democratic elections.
The fact is that they muted and banned a sitting US president. The global networks decide what it is the “community standard”, unless their algorithm decides it faster and ahead of its human managers. Nonetheless, the global network platforms are social glue.
The following quote is ominously significant, being a confession by the book chapter author that wrote it.
“AI operates according to its own processes…
AI develops its own approaches for fulfilling whatever objective functions were specified. It produces outcomes and answers that are not characteristically human and that are largely independent of national or corporate cultures.”
The effects are that information or recommendations are put out to the info-verse while the operators and users don’t know nor understand what is occurring in real time. The common end result is that the owners-operators are frequently embarrassed by the outcomes and legislatives bodies go after them with reprimands and occasional legal consequences.
When we talk about production and distribution of disinformation there is more unsettling news. The language-generation AI GPT-3 can create synthetic meanings, fake personalities. Those fake users can produce any fake and any hate contents.
While writing this last sentence I’m reminded of the billion dollars phenomenon known as Harry Potter series and the question- doubt who wrote all that Hogwarts School of Witchcraft and Wizardry? Just ponder the possibilities…
This book chapter describes in a disappointingly short and fleeting form the growing Tik Tok phenomenon of vulgarization in social media. Actually TiK Tok is emblematic of all the potential concerns about AI that I listed above. And more are yet to come.
Tik Tok was released for Android and iOS phones in 2017. It was downloaded over 2 billion times. It has over 130 million users in the US. It carries every negative feature that modern day global AI platform can provide. It offers whimsical, stupid, sometimes salacious short video clips aimed at youth aged 13 and over. It records and saves the biometrics – face print and voice print - of its users. It carried disinformation of any kind and sort. Governments, both autocratic and democratic, objected to it. Blocked it, sued it. It is considered a spying agent by proxy of the Chinese authorities. Tik Tok is all over the planet and it is not known for sure who controls it, if any. India and America tried to restrict Tik Tok, Good luck to them.
Global Network Platforms can change, and do change the norms of societies. The increase consumption, enabled education through novel modalities, enabled remote work place, changing fashion trends and electing politician to positions of power.
Global Network Platforms require a huge amount of original talents. The affluent countries – rich in resources and rich in talent can afford their own Global Network Platforms. Most countries can’t afford it. At the same time “public figures” are able to use the global platforms to their advantage, their enhanced visibility and economic exploitation.
Chapter Five deals with country and state security and warfare.
Going back to Proverb 24:6: “With cunning you shall wage war.”
Sun Tzu said: “All warfare is based on deception.”
Carl von Clausewitz, the military theorist, said in1832: “Force to counter opposing force, equips itself with the inventions of art and science.”
Every army has a Corp of Engineers. The nuclear weapons technology was developed and deployed to win an end to WWII. Next it was used for civilian purposes and still used in nuclear powered submarines. Biologic warfare is always forbidden but always developed in the dark back labs…
Satellites can be deployed for reconnaissance and military uses. So are rocket sciences.
AI is now integrated in all these physical armaments.
AI is used to disseminate disinformation as part of psychological warfare.
AI has the potential to convert military conflicts beyond restraint. Civilian airplanes already fly and land with little or no pilot intervention. So can fighter jet during on-air dogfights. The point is that the race for AI advantage is already taking place between the U.S., China and Russia.
What really happens behind the scenes of military R&D remains unknown.
Analysis of the Chinese Communist Party’s five-year plan by the cyber threat intelligence company SecAlliance reveals that China is increasingly confident and, no doubt, hostile in its cyber behavior. This will have implications on the future cyber landscape and potentially a detrimental effect on industrialized democracies.
Earlier this year, (2021) the UK Ministry of Defense’s “Digital Strategy for Defense” paper outlined how the armed forces will access data via a secure, singular, modern digital backbone. The backbone and a strategy itself are multi-layered. One of the main aims is to create the ability to exploit vast amounts of data in a simple way to dominate the battle-space.
On December 17, 2020, the US Air Force announced the successful flight of an AI algorithm controlled, known as ARTUµ, (with the pilot) on a U-2 Dragon Lady high-altitude reconnaissance aircraft. The Secretary said that “Putting AI safely in command of a US military system for the first-time ushers in a new age of human-machine teaming and algorithmic competition. Failing to realize AI’s full potential will mean ceding decision advantage to our adversaries.”
Who are the adversaries was not specified… We can count on them - the adversaries – that they are also doing their R&D in due diligence.
For example, The head of defense contractor manufacturer, Raytheon, Gregory Hays, has said this last October, that the US is years behind China in its pursuit of hypersonic weapons which can bob and weave through the atmosphere at more than five times the speed of sound.
His comments followed reports that China conducted two hypersonic weapons tests over the summer of 2021, including one of a so-called hypersonic glide vehicle. Launched from a missile or rocket, the craft separates and zips toward a target while maneuvering through the atmosphere.
Such weapons can reach speeds of 22,000 miles per hour, he said. “We have to have automated systems to defend the homeland, and we are focused on that.”
A missile of this capability flies at 6 miles per second. Let’s be clear, an AI piloting an aircraft, is scanning for targets - it follows its own logic - proceeding faster than the speed of human thought.
Another example, the Chinese military could be spending as much or even more than the United States on artificial intelligence (AI), according to a report.
The analysis, by the Centre for Security and Emerging Technology (CSET) at Georgetown University in Washington, also found just 22 of the 273 companies known to supply the People’s Liberation Army (PLA) with AI equipment were not subject to US Commerce Department restrictions – meaning they may be able to access US technology and pass it on to the PLA.
Given the secrecy surrounding the issue, it is difficult to calculate exactly how much each side spends on AI. Researchers looked at more than 18,300 publicly available contracts awarded by the PLA and state-owned defense companies last year. They estimated that Chinese military spending on AI-related technologies amounted to between US$1.6 billion and $2.7 billion each year.
Artificial intelligence can outperform humans in designing futuristic weapons, according to a team of Chinese naval researchers who say they have developed the world’s smallest yet most powerful coil-gun.
The prototype weapon developed by Professor Zhang Xiao and her team at the Naval University of Engineering in Wuhan has a 12cm (4.5-inch) barrel, about the size of a pistol, which contains three battery-powered coils that generate an electromagnetic field.
AI can start with an imperfect design and make continuous improvements by learning from previous mistakes, according to Zhang.
The AI gave the human designers a huge set of optimized data points that nearly doubled the weapon’s efficiency compared with the US rifle by maximizing the joint performance of many different components, she said. This resulted in a massive reduction in the weapon’s size and increased its output energy.
The point here is well made that AI assisted research and development is used to improve military armament.
“An algorithm knows only its instructions and objectives, not morale or doubt… When two AI weapons systems are deployed against each other, neither side is likely to have a precise understanding of the results of their interaction will generate or their collateral effects.”
What clear is, that no democratic system accountability or verifiable international equilibrium exists today. There are no known defined AI strategy doctrines. Therefore no international comparisons are possible.
Before we leave this subject we must keep in mind that AI generated false content can be used in psychological warfare. It can generate fake but plausible images of leadership, photos and videos. It can generate false speeches.
AI can generate to produce false images of a country or industry. Both adversarial sides can employ this process.
One may assume that the big international powers have each what I call military “Cyber Command.” But I don’t expect these command units existence to be confirmed in public.
This book does not name specific countries with such capabilities, like China, North Korea, Iran, UK or Israel. And there are others.
The Fifth Chapter that deals with National Security and World Order and includes a sub-chapter discussing the question on how to manage A.I.
The concern stems from the recognition that most capable countries are now engaged in an AI armament race. It is recognized that the world faces cyber weapons. AI is weaponized. Whatever I have quoted here about American and Chinese AI capabilities is convincing evidence available in the public square. Those capabilities can fall in the hands of rogue nations and terrorists. Small nations that are not rich in human, economic, and technological resources can find, recruit and retain the needed intellectual talent and resources to create AI systems to fit their national needs.
It is suspected that lethal autonomous weapon system capabilities that once activated will continue to act without human intervention or control.
Potential AI managed weapons systems are like R&D in the field of virology that experimented in “gain of function”. When virus products escape the lab they incite a global pandemic. Same applies to cyber weapons. There is no sure way to supervise or control national AI weapons development. The best example is use of stock market trading algorithms that create flash crashes.
In the U.S. the government does not control AI R&D. It is done by entrepreneurs, inventors, and universities’ research labs. It’s dynamic and unrestricted. It is recognized that there are AI-enabled weapons and AI weapons. The later make aggressive decisions without human input or human supervision. The challenge before humanity is to develop and agree upon non-use of AI weapons.
International treaties regarding control of AI weapons will require international discussions and negotiations. The AI weapons possessing powers will have to make disclosures of their current capabilities, will have to outline doctrines of “within-boundaries-AI R&D”, and preclude attacks on existing nuclear AI inspection capabilities. Controlling or abating AI nuclear weapons related capabilities have to occur before hostilities break.
Artificial General Intelligence (AGI) is the hypothetical ability of an intelligent agent to understand or learn any intellectual task that a human being can perform. Stated otherwise, AGI is the representation of generalized human cognitive abilities in software so that, faced with an unfamiliar task, the AI system could find a solution.
However we are not there yet. But the concept is be important when we review .Chapter Six
Chapter Six in this book pivots to the realm of Heideggerian philosophy and social as its title says it all: AI and the Human Identity.
The central question posed in this chapter is:
“How will we come to see ourselves and our role in the world? How will we reconcile AI with concepts like human autonomy and dignity?”
Human societies traditionally saw themselves as central to their reality. Those are represented by the traditional or revolutionary leaders, prophets, martyrs, explorers, inventors, artistic creators, and business moguls.
Thinking used to be about faith and reason. Human self-understanding is now gradually changing. The boundaries of reason are stretched and expanded. AI makes better predictions. AI makes improved products and processes. GPT-3 showed that it can create better texts and write improved codes for algorithms. Recall the definition of the upcoming AGI – it is the hypothetical ability of an intelligent agent to understand or learn any intellectual task that a human being can perform. This is not science fiction. Human identity is in a state of transformation.
For people who create, operate and adapt to live with AI, it is going to be an empowering experience.
For people who lack technical prowess - the passive consumers of AI - it will pose challenges of understanding why things happen the way they do. The algorithm does not explain why it happens.
Those consumers will lose their sense of autonomy, sense of fulfillment and sense of identity.
AI generator based GPT-3 can today write poetry. Will this poetry be awarded a Nobel Prize in literature?
There will be societal dislocations.
Every technological revolution brings with it social dislocations.
When a non-human intelligence, reasonable, yet inexplicable to humans, makes decisions that affect humans, then who are the deciding supervisors over the utilization, the benefits, and the revenue from these AI platforms?
Example. The AlphaFold platform is barely 4 years old.
AlphaFold is an artificial intelligence program developed by Google's DeepMind project which performs predictions of protein structure? The program is designed as a deep learning system. DeepMind is known to have trained the program on over 170,000 proteins from a public repository of protein sequences and structures. The program uses a form of attention network, a deep learning technique, that focuses on having the AI algorithm identify critical parts of a larger problem, and then piece it together to obtain the overall solution. That is the protein’s 3-D structure.
Creating molecules of proteins became critical to production of mRNA. The beneficiaries of the mRNA vaccine are billions of people living on Earth today. Yet Pfizer’s and Moderna’s vaccine brings a bounty of riches transferred from the American tax payers to the big pharma shareholders. I call it wealth transfer.
Education and lifelong learning receive now a changed meaning. A new generation of “AI Natives” is growing up with AI assistants. It started with Alexa and Google Home and it keeps developing into more complex AI agents. When the children talk to Siri they don’t know that twenty years ago a cell phone had no voice assistants. There are anticipated question about the social adaptation of children who grow up with AI controlled gadgets. Somewhere else on the globe other children have no 5G phones, no voice assistants and no AI based educational devices.
There is a growing chasm around the world between people who are AI literate and other folks who haven’t heard of - AI oblivious. Soon the AI literate folks will have much greater earning power than the AI ignorant. Civilian occupational fields such as financial derivative, legal information, library services, meteorology, air traffic control, car repair, travel guidance, airplane pilots and more have AI integrated into their working devices.
A new social order will emerge. The AI-haves already wield greater earning power than the AI-have-not.
The future will see a different human identity. Humans will have to strike a partnership with their AI-integrated machines.
The survival of Democracy depends on retention of human qualities, maintenance of personal communication and equal level of reason.
The EU community is seeking to regulate AI. In China AI is used for surveillance and control the population.
In America AI is largely left, so far, to non-governmental organizations. But that will change. The U.S. department of Defense is having its closely guarded R&D programs. A National AI Initiative Office was established in accordance with the recently passed National Artificial Intelligence Initiative Act of 2020. It will be integral to the Federal Government’s efforts to maintain AI leadership position for many years to come.
Ethics in the Age of AI. This is Chapter 7 - the last chapter is actually titled: “AI and the Future.” But who knows what is going to be the future? Do you know the future?
From the forgoing chapters’ reviews and discussions it may safely be expected that human ethics as we know now will also change.
“Technology will transform knowledge, discovery, healthcare, communication, and individual thought. Artificial Intelligence is not human. It does not hope, pray or feel. Nor does it have awareness or reflective capabilities.”
The boundaries of knowledge are expanding. More data and faster analysis processes will open panoramic landscapes unknown heretofore.
Consequently humanity will have three choices: to Confine AI, or to partner with AI, or to let AI loose and defer to it.
Would AI unveil more than one truth?
We are gradually entering the phase of the AGI. At this phase AGI will learn and execute a broad range of tasks. Much like, but more efficiently than humans can perform. Who will control all of that? AI may compel some of those decisions.
AI is in some instances was shown to be unpredictable. If that is the case, who will bear responsibility for the outcomes?
Example. AI is gradually integrated into nuclear weapons arsenals.
The trigger to the nuclear weapon is thus carried in a thumb drive.
Read this last sentence again and let it sink in.
What do you propose to do?
The Age of AI is a scholarly document authored by distinguished architects that formed the reality in which live. Each is an intellectual visionary in his field.
The book serves readers from the two ends of the rainbow. At one end are the STEM scholars who get a refresher view in the history and future of the humanities in the Western civilization. On the other end are the scholars in the humanities and social studies who get introduced to the cutting edge technology explained in easy to understand language.
It is a recommended text to be required in any college major tracks for students in their senior year. Be they in philosophy, political science, law, art and design, engineering, computer sciences, mathematics or accounting.
Humanity as we know it, is already being divided into two classes. Those are the AI literate and the AI ignorant classes. The outcome results in a difference in economic status and standard of living.
The book has its limitations. Some of its technical contents has already fallen behind since it went to press.
Certain influential players in the field of AI are not mentioned. For example, Amazon Web Services and Apple products. China is a major player in AI R&D and advances but is barely mentioned. China’ AI accomplishments today, have possibly exceeded the U.S. in AI technologies.
Last words – study this book - be AI Literate.
I enlisted the help of a GPT-3 based AI copy-writer for a few ideas prompts while writing the review.
I purchased on Amazon my reading and study copy of the book. I didn’t have an advanced copy of the book, nor did I get to read the book before its release date on November 3, 2021.