Hazel Henderson: Billions are spent by governments, corporations and investors in training computer-based algorithms (i.e. computer programs) in today’s mindless rush to create so-called “artificial” intelligence, widely advertised as AI. Meanwhile, training our children and their brains (already superior to computer algorithms) is under-funded, schools are dilapidated, sited in run-down, often polluted areas while our teachers are poorly paid and need greater respect. How did our national priorities get so skewed?

In reality, there is nothing artificial about these algorithms or their intelligence, and the term “AI” is a mystification! The term that describes the reality is “Human-Trained Machine Learning”, in today’s mad scramble to train these algorithms to mimic human intelligence and brain functioning. In the techie magazine WIRED, October 2018, we meet a pioneering computer scientist, Fei-Fei LI, testifying at a Congressional hearing, who underlines this truth. She said, “Humans train these algorithms” and she talked about the horrendous mistakes these machines make in mis-identifying people, using the term “bias in—bias out” updating the old computer saying, “garbage in—garbage out”.

Professor LI described how we are ceding our authority to these algorithms to judge who gets hired, who goes to jail, who gets a loan, a mortgage or good insurance rates — and how these machines code our behavior, change our rules and our lives. She is now back at Stanford University after a time as an ethicist at Google and has started a foundation to promote the truth about AI, since she feels responsible for her role in inventing some of these algorithms herself. As a celebrated pioneer of this field, Professor LI says “There’s nothing artificial about AI. It’s inspired by people, it’s created by people and more importantly, it impacts people”.

So how did Silicon Valley invade our culture and worldwide technology programs with its short-term, money -obsessed values: “move fast and break things”; disrupt the current systems while rushing to scale and cash out with an IPO? These values are discussed by two insiders in shocking detail, by Antonio G. Martinez in “Chaos Monkeys” (2016) and Bloomberg’s Emily Chang in “Brotopia” (2018). These authors explain a lot about how training these algorithms went so wrong: subconsciously mimicking their mostly male, misogynist, often white entrepreneurs and techies with their money-making monopolistic biases and often adolescent, libertarian fantasies.

I also explored all this in my article “The Future of Democracy Challenged in the Digital Age”, CADMUS, October 2018, describing all these issues of the takeover by AI of our economic sectors; from manufacturing, transport, education, retail, media, law, medicine, agriculture, to banking, insurance and finance. While many of these sectors have become more efficient and profitable for the shareholders, my conclusion in “The Idiocy of Things” critiqued the connecting of all appliances in so-called “smart homes” as quite hazardous and an invasion of privacy. I urged humans to take back control from the over-funded, over-invested, over-paid computer and information science sectors too often focused on corporate efficiency and cost-saving goals driven by the profit targets demanded by Wall Street.

I have called for an extension of the English law, settled in the year 1215: “habeas corpus” affirming that humans own their own bodies. This extension would cover ownership of our brains and all our information we generate in an updated “information habeas corpus”. Since May 2018, European law has ratified this with its General Data Protection Regulation (GDPR), which stipulates that individuals using social media platforms, or any other social system do indeed retain ownership of all their personal data.

So, laws are beginning to catch up with the inhuman uses of human beings, with our hard-earned skills being used to train algorithms that then replace us! The computer algorithm trainers then employ out of-work people surviving in the gig economy on Mechanical Turk and Task Rabbit sites, in minimum, hourly- paid data entry tasks to train these algorithms!

Scientist Jaron Lanier in his “Ten Arguments for Deleting Your Social Media Accounts Now” (2018) shows how social media are manipulating us with algorithms to engineer changes in our behavior, by engaging our attention with clickbait and content that arouses our emotions, fears and rage, playing on some of the divisions in our society to keep us on their sites. This helps drive ad sales and their gargantuan profits and rapid global growth. Time to rethink all this, beyond the dire alarms raised by Bill Gates, Elon Musk and the late Stephen Hawking that these algorithms we are teaching will soon take over and may harm or kill us as did HAL in the movie “2001”.

Why indeed are we spending all this money to train machines while short-changing our children, our teachers and schools? Training our children’s brains must take priority! Instead of training machines to hijack our attention and sell our personal data to marketers for profit — let’s steer funds into tripling efforts to train and pay our teachers, upgrade schools and curricula with courses on civic responsibility, justice, community values, freedoms under habeas corpus (women also own their own bodies!) and how ethics and trust are the basis of all market and societies.

Why all the expensive efforts to enhance machine learning to teach algorithms to recognize human faces, guide killer drones, falsify video images and further modify our behavior and capture our eyeballs with click bait, devising and spreading content that angers and outrages — further dividing us and disrupting democracies?

Let’s rein in the Big Brother ambitions of the new techno-oligopolists. As a wise NASA scientist, following Norbert Weiner’s Human Use of Human Beings (1950), reminded us in 1965 about the value of humans: “Man (SIC) is the lowest-cost, 150 pound, nonlinear all-purpose computer system which can be mass-produced by un-skilled labor”, quoted in Foreign Affairs, July-August, 2015, p. 11. Time for common sense!

Hazel Henderson© 2018

Hazel Henderson D.Sc.Hon., FRSA, is founder of Ethical Markets Media, LLC and producer of its TV series. She is a world renowned futurist, evolutionary economist, a worldwide syndicated columnist, consultant on sustainable development, and author of The Axiom and Nautilus award-winning book Ethical Markets: Growing the Green Economy (2006) and eight other books.

Her editorials appear in 27 languages and 200 newspapers syndicated by Inter Press Service, and her book reviews appear on SeekingAlpha.com. Her articles have appeared in over 250 journals, including (in USA) Harvard Business Review, New York Times, Christian Science Monitor; and Challenge, Mainichi (Japan), El Diario (Venezuela), World Economic Herald (China), LeMonde Diplomatique (France) and Australian Financial Review.

Photo by Ferrari + caballos + fuerza = cerebro Humano 

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Collins is a sociologist. In his book “Artifictional Intelligence – Against Humanity’s Surrender to Computers”, out today from Polity, Collins does many interesting things. To begin with, he argues what qualifies him to have an opinion on AI.

Collins is a sociologist of science at the School of Social Sciences, Cardiff University, Wales, and a Fellow of the British Academy. Part of his expertise is dealing with human scientific expertise, and therefore, intelligence.

It sounds plausible that figuring out what constitutes human intelligence would be a good start to figure out artificial intelligence, and Collins does a great job at it.

The impossibility claims

The gist of Collins’ argument, and the reason he wrote the book, is to warn against what he sees as a real danger of trusting AI to the point of surrendering critical thinking, and entrusting AI with more than what we really should. This is summarized by his 2 “impossibility claims”:

1. No computer will be fluent in natural language, pass a severe Turing test and have full human-like intelligence unless it is fully embedded in normal human society.

2. No computer will be fully embedded in normal human society as a result of incremental progress based on current techniques.

There is quite some work to back up those claims of course, and this is what Collins does throughout the 10 Chapters of his book. Before we embark on this kind of meta-journey of summarizing his approach, however, it might be good to start with some definitions.

The Turing test is a test designed to categorize “real” AI. At its core, it seems simple: a human tester is supposed to interact with an AI candidate in a conversational manner. If the human cannot distinguish the AI candidate from a human, then the AI has passed the Turing test and is said to display real human-like intelligence.

The Singularity is the hypothesis that the appearance of “real” artificial intelligence will lead to artificial superintelligence, bringing unforeseen consequences and unfathomable changes to human civilization. Views on the Singularity are typically polarized, seeing the evolution of AI as either ending human suffering and cares or ending humanity altogether.

This is actually a good starting point for Collins to ponder on the anthropomorphizing of AI. Why, Collins asks, do we assume that AIs would want the same things that humans want, such as dominance and affluence, and thus pose a threat to humanity?

This is a far-reaching question. It serves as a starting point to ask more questions about humanity, such as why people are, or are seen as, individualistic, how do people learn, and what is the role of society in learning.

Social Science

Science, and learning, argues Collins, do not happen in a monotonous, but rather in a modulated way. What this means is that rather than seeing knowledge acquisition as looking to uncover and unlock a set of predefined eternal truths, or rules, the way it progresses is also dependent on interpretation and social cues. It is, in other words, subject to co-production.

This applies, to begin with, to the directions knowledge acquisition will take. A society for which witches are a part of the mainstream discourse, for example, will have very different priorities than one in which symptomatic medicine is the norm.

But it also applies to the way observations, and data, are interpreted. This is a fundamental aspect of science, according to Collins: the data is *always* out there. Our capacity for collecting them may fluctuate with technical progress, but it is the ability to interpret them that really constitutes intelligence, and that does have a social aspect.

Collins leverages his experience from social embedding as practiced in sociology to support his view. When dealing with a hitherto unknown and incomprehensible social group, a scholar would not be able to understand its communication unless s/he is in some way embedded in it.

All knowledge is social, according to Collins. Image: biznology

Collins argues for the central position on language in intelligence, and ties it to social embedding. It would not be possible, he says, to understand a language simply by statistical analysis. Not only would that miss all the subtle cues of non-verbal communication, but, as opposed to games such as Go or chess that have been mastered by computers, language is open-ended and ever-evolving.

Collins also introduces the concept of interactional expertise, and substantiates it based on his own experience over a long period of time with a group of physicists working in the field of gravitational waves.

Even though he never will be an expert who produces knowledge in the field, Collins has been able to master the topics and the language of the group over time. This has not only gotten him to be accepted as a member of the community, but has also enabled him to pass a blind test.

A blind test is similar to a Turing test: a judge, who is a practising member of the community, was unable to distinguish Collins, a non-practising member, from another practising member, based on their answers to domain specific questions. Collins argues this would never have been possible had he not been embedded in the community, and this is the core of the support for his first impossibility claim.

Top-down or Bottom-up?

As for the second impossibility claim, it has to do with the way AI works. Collins has one chapter dedicated to the currently prevalent technique in AI called Deep Learning. He explains how Deep Learning works in an approachable way, which boils down to pattern recognition based on a big enough and good enough body of precedents.

The fact that there are more data (digitized precedents) and more computing power (thanks to Moore’s Law) today is what has enabled this technique to work. It’s not really new, as it has been around for decades, it’s just that we did not have enough data and processing power to make it work reliably and fast enough up until now.

In the spirit of investigating the principal, not the technicalities behind this approach, Collins concedes some points to its proponents. First, he assumes technical capacity will not slow down and soon reach the point of being able to use all human communication in transcribed form.

Second, he accepts a simplified model of the human brain as used by Ray Kurzweil, one of AIs more prominent proponents. According to this model, the human brain is composed of a large number of pattern recognition elements. So all intelligence boils down to is advanced pattern recognition, or bottom-up discovery of pre-existing patterns.

Top-down, or bottom-up? Image: Organizational Physics

Collins argues however that although pattern recognition is a necessary precondition for intelligence, it is not sufficient. Patterns alone do not equal knowledge, there needs to be some meaning attached to them, and for this language and social context is required. Language and social context are top-down constructs.

Collins, therefore, introduices an extended model of the human brain, in which additional inputs are processed, coming from social context. This, in fact, is related to another approach in AI, labeled symbolic AI. In this top-down approach, instead on relying exclusively on pattern recognition, the idea is to encode all available knowledge in a set of facts and rules.

Collins admits that his second impossibility claim is weaker than the first one. The reason is that technical capacity may reach a point that enables us to encode all available knowledge, even tacit one, a task that seems out of reach today. But then again, many things that are commonplace today seemed out of reach yesterday.

In fact, the combination of bottom-up and top-down approaches to intelligence that Collins stands behind, is what many AI experts stand for as well. The most promising path to AI will not be Deep Learning alone, but a combination of Deep Learning and symbolic AI. To his credit, Collins is open-minded about this, has had very interesting conversations with leading experts in the field, and incorporated them in the book.

Technical understanding and Ideology

There are many more interesting details that could not possibly fit in a book review: Collins’ definition of 6 levels of AI, the fractal model of knowledge, exploring what an effective Turing test would be, and more.

The book is a tour de force of epistemology for the masses: easy to follow, and yet precise and well-informed. Collins tiptoes his way around philosophy and science, from Plato to Wittgestein to AI pioneers, in a coherent way.

He also touches issues such as the roots of capitalism or what is driving human behavior, although he seems to have made a conscious choice of not going into them, possibly in the spirit of not derailing the conversation or perhaps alienating readers. In any case, his book will not only make AI approachable, but will also make you think on a variety of topics.

And, in the end, it does achieve what it set out to do. It gives a vivid warning against the Surrender, which should be about technical understanding, but perhaps even more so about ideology.

Collins, Harry M. (2018). Artifictional Intelligence: Against Humanity’s Surrender to Computers. Cambridge, UK; Malden, Massachusetts: Polity. ISBN 9781509504121.

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“Faced with a systemic crisis of the mainstream economy, there is an abundance of initiatives, but a systemic crisis can only be solved by equally systemic alternatives. How to fit them together in a fundamental transformative change, and which elements need to be combined to obtain vital synergies – this is the crucial aspect addressed in this important book.” » Michel Bauwens – Expert in Peer to Peer and Commons economy and Founder of The P2P Foundation

Emmanuel Mossay, the co-author of Shifting Economy, has written the following introductory text specially for the P2PF blog. It is followed by the book’s Preface, written by Mark Eyskens. You can download the book in PDF through this link: Shifting Economy

What is Shifting Economy?

Shifting Economy is a road book to start a new business, or redesign existing business, with the nature & human beings at the heart of the business models.

You will discover an alternative ocean to the blue and the red one. The green ocean is based on the cooperation.

Follow the 20 models & methodologies to become a “commoner”. These tools will show you some ways to:

• understand the cultural shifts of the new economy
• link macro future trends with your projects
• draw the sustainability journey for your organization
• define new business models
• build agile alliances with citizens, public and private stakeholders with 7 levels of shared values co-creation
• get ready for the arrival of AI and robots
• fine-tune the “speed” of your actions according to the complexity of your company
• learn how become bilingual old/new economy
• discover the growing industries
• find the money to convert expenses into sustainable investments

Please download, use, share, comment Shifting Economy.

Preface, by Mark Eyskens

Homo sapiens is now evolving into post economy. The New Economy must manage scarcity and affluence, a dual problem that is not integrated into the main classical economic theories. There will be an important shock between opulence, described by the economist John Kenneth Galbraith in The Affluent Society, and scarcity on planet Earth. The only planet we have. There is no planet B.

The West grew strongly particularly at the beginning of industrialization, thanks to dualism, an old paradigm stemming from Plato. This logic of contradictions, was very useful because it forced the Westerners to make choices between “either/or”, between alternatives, between right or wrong in order to progress and to act. The steam engine is a good example, invented three centuries earlier in China as a piece of entertainment, but installed only in the eighteenth century at the heart of the industry in Europe by Westerners. Platonic dualism is at the core of creativity but was and still is at the origin of many conflicts and even wars which ranked the 20th century as the bloodiest of the human history.

Asian wisdom however teaches us another different basic paradigm: the Yin and Yang principle: the complementarity of dual oppositions which merge into a synthesis. In Chinese writing moreover, there is a single ideogram for the words « crisis » and « opportunity ».

This concept matches perfectly with the discovery of quantum physics that light is both a wave and a beam of particles, the photons. Niels Bohr, one of the founding fathers of quantum physics, summarized this insight by the Latin phrase “Contraria complementa sunt”, replacing the old “either/or” logic by the revolutionary “and/and” principle, that frees the way to cooperative solutions.

This awareness is progressively rising in Western thinking and will have far reaching consequences. It will lead us to a new holistic approach, exploring the hidden energies of diversity, divergence, oppositions and promoting synthesis and all kinds of creative compromises, in a world of interdependence, where national governments are too small for the big problems and too big for the small ones. Economic praxis has already adopted what is coined as: « Coopetition », when competition and cooperation are no longer exclusive along Darwinian principles but complementary, even inclusive according to quantum mechanical rules.

The rising of this inclusive, global approach is a challenge for political and economic leaders facing local populism emerging from fears and misunderstanding of what is going on in the global world of today and the world village of tomorrow. The nationalistic definition of “people” has become obsolete. The “people” has become a “population” with multicultural features in most countries. Nationalism and populism are perfectly understandable but they have become counterproductive because no longer future oriented. Protectionism is the economic and cultural translation of nationalism. To a certain extent protectionism existed already before economics and politics, even before human beings: the first membranes protecting living cells, stressed in our bodies. This selfish vitalism is still attractive but suicidal in a changed world as soon as ego nationalists propose to build walls instead of bridges.

In times of growing complexity democracy is caught between web and spider. Some citizens are saying “We have a vote, but we do not have a voice”. This is a serious warning addressed to politicians. Societal problems are extremely complex and the decision making process is most opaque. Governments, authorities “they” decide, they rule, they legislate, they impose…

There is a far reaching “they-ification” of politics, which makes governing impersonal, abstract and looking like a non figurative painting. We need to reinvent democracy by introducing elements of participative decision making, by informing and explaining and replacing demagogues by pedagogues. Most important is to modify the democratic voting systems. One model could be the promoting of «point voting», an electoral system by which each voter would get a plural number of votes, for instance ten votes, which he could freely cast and spread over different parties and candidates according to the intensity of his preferences. This would lead to a fine tuning of the voters choices. Also at the micro-economic level of enterprises and companies democratic cooperation between all stakeholders, transcending their exclusive interests, is at stake in the post economic era. Still more Herculean is the task of organizing steadily ways and means of international, possibly worldwide economic and political government.

On a much larger scale the European institutions also suffer of several functional problems and have to cope with great challenges. A European Fiscal Community should be created according to the principle “no representation without taxation.” Today the EU Parliament has no taxation power, so it is difficult to implement new strategies and new legislation. We need also to simplify and clarify the taxation systems. Budgetary expenses with respect to defence, security, energy, development policy, integration of immigrants, research, digital communication… should be Europeanized. A strong European public budget is needed. The EU Institutions budget equals 1% versus 27% in the USA for the federal expenses.

The Euro-zone, in order to cope with distortions of competition among member states, has to impose severe measures of austerity implying the reduction of public spending, of wages, of all kinds of allowances. The management of exchange rates by individual countries is no longer possible inside a monetary zone. Austerity measures being considered as an “internal devaluation” make the European Union unpopular and may lead to economic deflation. Only an efficient budgetary policy conducted by the EU could stabilize the Euro-zone.

Europe should unite in front of the ongoing scientific and technological revolutions.

History of mankind has indeed been steered by discoveries and scientific innovations, starting with the discovery of fire, 300.000 year ago.

Today scientific inventions are overwhelming in all domains. The acronym B.I.N.C. is useful in summarizing the ongoing scientific revolutions:

• Biogenetics, fabulous progress of medicine, average life span of 100, 150, 200 years??
• Information technology (computer apps, AI, virtual reality and physical robots, 3-D printing). Emergence of the “robo sapiens”.
• Nanotechnology. Tomorrow, we will be able to speak to every citizen on earth in our own language, and understand all the worlds’ languages thanks to nano computers (wireless or implanted in our own body).
• Cognitive science, human brain research and manipulation. The socio-economic consequences of the tsunami of scientific and technological innovations will be overwhelming and dramatic for the world community and the members of mankind.

Digitalization and robotization will considerably reduce working time, wage earners will be replaced by independent employees, the existence of world markets will go hand in hand with home work, multinationals will compete but also cooperate in lot of domains, intellectual property will no longer be protected, interconnectivity will eliminate all kind of intermediaries on the markets, e-commerce will take over from shopping. AIRBNB, Uberisation, circular economy, pooling, personal manufacturing, on line open courses, worldwide universities will spread, cash payments will disappear.

The development of solar and nuclear fusion energy will completely change the worldwide economic and political power balance. Wealth will be transformed in welfare and the pursuit of happiness will become a societal goal. A post-economic era would emerge

Nevertheless a lot of shadows of progress will have to be dealt with: demography, aging, climate, food scarcity, AMR (antimicrobial resistance), weapons of mass destruction, the difficulty to transform multiculturality in interculturality …

It goes without saying that the ongoing tsunami of scientific and technological innovations will revolutionize the world community for better and for worse. As a consequence the ultimate question will be and is already the question of ethics. How to transform all these changes into human progress? How should we manage ethics in politics, in economy, in business? And what’s the “right ethic”? Who is deciding on those values? Which are the rules applicable for everyone? Do we stick and apply to the lowest common denominator?

Buddha, Jesus Christ, Kant and other moral leaders said: “Do not do to others what you do not want done to yourself”. But is this rule sufficient to improve human life on earth?

The guideline of SHIFTING ECONOMY is the quest of purpose in economy, the quest of ethics in business – with tools that can be used on the field. It is also an invitation to all decision-makers to imagine and implement new dreams to connect human beings, and transform the grief of the planetary village into human happiness.

Mark Eyskens
Professor Emeritus Economics and former Prime Minister of Belgium

Download Shifting Economy

Photo by bdsmith84

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