Christopher Columbus: No Monuments for Murderers?

Twenty-five years ago, I wrote an article, “Once Upon a Genocide,” reviewing the major children’s literature about Columbus. My conclusion was that these books teach young readers that colonialism and racism are normal.

… in fundamental ways, Columbus’ world is not so different from the world we live in today. Big countries continue to dominate “lesser” nations. The quest for profit is still paramount. The world is still sliced in two between the worthy — the owning classes, the corporate masters, the generals — and those the Uruguayan writer Eduardo Galeano called los nadies— the nobodies. The invaded, the owned, the bombed, the poisoned, the silenced.

So yes, let’s pull down the monuments, let’s make the holidays more inclusive, let’s rewrite the textbooks and children’s literature. But let’s also challenge the fundamental structures of ownership, power, and privilege that have given us such a skewed constellation of heroes and holidays.

Don’t pull down the  monuments. Let them stay and remind us about our stupidity which made us to accept that lie and to teach it to our children. Let them stay and remind us about our shame. I.V. 

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What makes a good life? Lessons from the longest study on happiness

What keeps us happy and healthy as we go through life? If you think it’s fame and money, you’re not alone – but, according to psychiatrist Robert Waldinger, you’re mistaken. As the director of a 75-year-old study on adult development, Waldinger has unprecedented access to data on true happiness and satisfaction. In this talk, he shares three important lessons learned from the study as well as some practical, old-as-the-hills wisdom on how to build a fulfilling, long life.

Lessons from the longest study on human development

For the past 70 years, scientists in Britain have been studying thousands of children through their lives to find out why some end up happy and healthy while others struggle. It’s the longest-running study of human development in the world, and it’s produced some of the best-studied people on the planet while changing the way we live, learn and parent. Reviewing this remarkable research, science journalist Helen Pearson shares some important findings and simple truths about life and good parenting.

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Human Nature: Paleolithic Emotions, Medieval Institutions, God-Like Technology

Creativity might just be the defining trait that makes us human, says E.O. Wilson, two-time Pulitzer Prize winner and acclaimed ‘Father of Biodiversity’. But what exactly is the modern Homo sapiens, anyway? Wilson calls us an evolutionary chimera, picking up things from every age without fully transitioning out of any one era. That’s why we are a complicated mix of paleolithic emotions, medieval leftovers like banks and religion, and now the latest addition: God-like technology. Those are the influences we know about, but creativity may actually predate our language, writings, and art—Wilson believes it’s hundreds of thousands of years older than we assume. How can we discover the deepest roots of what has made us so human? Wilson says the humanities need to up their game and help the sciences unlock our creative origins. E.O. Wilson’s new book is The Origins of Creativity. Read more at… Follow Big Think here: YouTube: Facebook: Twitter: Transcript: When we address human creativity I think what we are dealing with right from the start is what makes us human, and there has been a great shortcoming in the humanities in explaining themselves in order to improve the creative powers of the humanities. By that I mean most considerations of human behavior, its origin, and its meaning within the humanities, stops about the time of the origin of literacy when we can deal with symbols and with the first written languages and understand them. Or perhaps it goes back 10,000 years to the beginnings of Neolithic civilization. But that’s just an eye-blink of time in the origin of the emotions and the setup of the human brain that’s permitted our understanding of the humanities and then ultimately science, to the bottoms of their depths. And this then brings us to what I like to call—an acronym—PAPEN, P – A – P – E – N. And that is a designation of the areas of science that are most relevant to the humanities when they address the origins especially of the human species and the appearance of modern Homo sapiens some several hundred thousand years ago. And PAPEN, P – A – P – E – N, stands for paleontology, anthropology, psychology, evolutionary biology and neural biology. These are the branches of science that need information on the origin of humans, and the deep history of pre-human existence is needed to explain the origins of creativity in modern human beings, and the ways and the reasons our emotions exist and rule us, leading to the way that I have tried to put it in saying that modern humanity is distinguished by paleolithic emotions and medieval institutions like banks and religions, and god-like technology. We’re a mixed up and, in many ways, still archaic species in transition. We are what I like to call a chimera of evolution. We walk around and exist in this fairly newly made civilization that we created, a compound of different traits, of different origins and different degrees of forward evolution.

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The success of the Scientific Revolution led to the development of the worldview of scientific naturalism, or the belief that the world is governed by natural laws and forces that can be understood, and that all phenomena are part of nature and can be explained by natural causes, including human cognitive, moral, and social phenomena. The application of scientific naturalism in the human realm led to the widespread adoption of Enlightenment humanism, a cosmopolitan worldview that places supreme value on science and reason, eschews the supernatural entirely, and relies exclusively on nature and nature’s laws—including human nature and the laws and forces that govern us and our societies—for a complete understanding of the cosmos and everything in it, from particles to people.

Dr. Michael Shermer is the Publisher of Skeptic magazine, a monthly columnist for Scientific American, and a Presidential Fellow at Chapman University where he teaches Skepticism 101. He is the author of Why People Believe Weird ThingsWhy Darwin MattersThe Science of Good and Evil, and The Moral Arc. His next book is Heavens on Earth: The Scientific Search for the Afterlife, Immortality & Utopia. His two TedTalks, viewed nearly 8 million times, were voted in the top 100 of the more than 2000 TedTalks.

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The New Yorker published yesterday about the Trump children’s shady avoidance of charges in a 2012 real-estate fraud case.
“Amid the chaos and dysfunction,” Slate’s Jamelle Bouie writes, “it can be easy to miss that this White House is corrupt. Remarkably, unbelievably, corrupt.” Given the number of potential scandals involving personal enrichment — of President Trump, his family or top administration officials — I wanted to create a list of all the major ones. Here goes:
• As The New Yorker, ProPublica and the public radio station WNYC reported yesterday, longtime Trump lawyer Marc Kasowitz donated more than $50,000 to a Manhattan district attorney who later dropped a case against Ivanka Trump and Donald Trump Jr.
• The presidency is benefiting Trump’s business in numerous ways. Government officials have stayed in hotels that bear Trump’s name, for example, while Trump’s Mar-a-Lago club doubled its membership rates after he won the White House.
Also: Eric Trump has been giving his father quarterly updates on the financial health of his businesses, despite promises that the president would have no involvement. Those businesses have also done deals with foreign governments, despite the president’s pledge that they wouldn’t.
• Trump has spent more than $30 million of taxpayer money traveling to properties he owns, by one estimate.
• Ryan Zinke, Trump’s secretary of the interior, is under investigation for chartering a $12,000 flight from Las Vegas to Montana at taxpayers’ expense.
• David Shulkin, the secretary of Veterans Affairs, charged taxpayers for a trip to Europe that included stopovers at Wimbledon and Westminster Abbey, plus a river cruise for him and his wife.
• Scott Pruitt, who runs the Environmental Protection Agency, regularly dines with donors and lobbyists from industries his department is regulating. He also used public money to pay for a soundproof booth in his office and chartered private and military overseas flights.
• Steve Mnuchin, the Treasury secretary, tried to use a government plane to fly him to Europe for his honeymoon. He may also have availed himself of a taxpayer-funded military plane to view the solar eclipse in August, though he says the trip had a different purpose.
• Tom Price, the former secretary of health and human services who resigned last week, spent hundreds of thousands of taxpayer dollars on private planes. Trump hired Price despite Price’s history of using his position in Congress to receive sweetheart stock deals.
• Jared Kushner has reportedly used his closeness with Trump to secure foreign investment in Kushner’s family-owned business, in exchange for granting visas.
• A Chinese government office approved trademarks for a company owned by Ivanka Trump on the same day that China’s president met with President Trump.
• Paul Manafort, Trump’s former campaign chairman, may have used his position to repay a Russian oligarch.
• Michael Flynn lobbied on behalf of the Turkish government, but Trump selected him as national security adviser anyway (before later ousting him).


Human: relationships which satisfy our inherited needs and longing for great happiness, which provide deep and universal fulfillment, which fills everyday life, our thoughts and behavior with deep balance, tranquility and order.

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Arhitekts Vents Vīnbergs KDi 18 01.2017:

“… māksla vairāk nekā viss cits nodrošina visprecīzāko īstenības atspulgu ….”

Visprecīzāko īstenības atspulgu nodrošina īstenībai iespējami tuvu esoši ārējās pasaules modeļi, kas ļauj droši un pareizi prognozēt ārējās pasaules reakcijas. Ar profesionālu šādu modeļu veidošanu nodarbojas eksaktā zinātne.

Māksla ir viena no daudzajām cilvēku valodām, kas apraksta ārējās pasaules modeļus ne tikai iespējami precīzi, bet galvenais, emocijām bagāti. Psihoterapeiti zina, ka cilvēkus pārliecina nevis loģiski argumenti, bet emocijām pildīti ‘argumenti’ – stāsti (eksaktie tos sauc par modeļiem), kas klausītājā ierosina dziļas emocijas. Un, tā kā mēs galvenokārt esam ’emociju mašīnas’, tad nereti tieši šie ‘stāsti’ (mākslas darbi) veido un iespaido mūsu rīcību.

Jau gadu tūkstošiem, bet sevišķi mūsdienu cilvēku dzīves (iekšējās pasaules) bagātību veido valodas, kurās mēs izsakām, aprakstām un izdzīvojam savu iekšējo pasauli: mūzika, teātris, kino, literatūra, un, galvenokārt, cilvēku attiecības. Šeit, protams, zinātne un dažādi māņticības veidi arī pieder.

Mākslas vērtība.  Plašā skatījumā valodas un mākslas vērtību var mērīt ar tās skaistumu, evolucionisti saka, ka skaists ir tas, kas nodrošina izdzīvošanu lielā laika mērogā. Skaistumu un izdzīvošanu mēs augstu vērtējam.  Tādēļ var teikt, ar vērtībām, ar to, vai tās ir vai nav, mēs mākslu vērtējam. Remarka, Džeka Londona, Iļjas Glazunova un Džuzepes Verdi darbos tās nepārprotami redzamas, mēs baudām ne tikai ‘stāstu’, bet arī domas par savu dzīvi un tās jēgu. Ja kādā darbā ir tikai pirmā daļa, vai arī otrā daļa ir neīsta, nepatiesa, tad tādu darbu nereti sauc par  ‘modernu’ vai, kā raksta autors, par ‘postpatiesību’.

Autors ir nodemonstrējis māku uzrakstīt rakstu vienā teikumā (aptuveni 300 vārdu). Vai tas liecina par apdāvināta cilvēka necieņu pret nesaprotošo pūli? Domāju, ka nē. Vairāk tas liecina par kultūru un sabiedrību, kuras nesējs un izteicējs viņš ir.

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…something to get your poor, caring and sharing and intelligent self out of this cesspool of ignorance

“Once again I ask if anyone here has an exit strategy out of this cesspool of greed, heartless indifference, and breathtaking stupidity that is the US. I am seriously considering the options these days…”

…there are at least three reasons I can’t give you an answer that will satisfy you –

…I haven’t traveled enough to enough places, but I have traveled a little

…you and I are probably so different that you probably wouldn’t like my recommendations, …the wording of this sentence highlights the differences so much that even attempting to find you a “better” place is doomed to failure.

This is long…you might want to jump down to “Suggestions and recommendations”

If you pay attention and believe the mainstream media, and perhaps with your other reasons, including perhaps a negative attitude to begin with, you can come to believe that we or you are in a “cesspool”.

I have my own reasons for not trusting the mainstream media (“the lamestream media”, the MSM or Ministry of Smoke and Mirrors, etc.), and so I am turning to other sources of info, trying to observe more and reflect on my own experience, as everyone must.

But let me give an answer and another perspective.

Some years ago a married couple of Jewish family physicians moved in next door. We shared a lot of things, and perhaps it was our mutual pleasure with the fairly new Macintosh that got us started, but we made and stayed lifelong friends. The two were part of an extended family…one side had a root in Peta Luma California but had since migrated East. Of the four children, one became a music producer in LA, another a music professor on the East coast, the third became the physician who is our friend. The fourth and last brother also became a doctor, but faced anti-Semitism in the U.S. and so at a fairly early age moved to Israel…marrying into what had been a Socialist commune which has since mostly privatized.

The other of the pair had grown up in New Jersey, his father ran an electrical subcontracting business where he helped out as a youngster, spent high school summers running a fishing boat off the coast (even having a little fresh sushi with some of his Japanese clientele before putting back into port). He’s a sailor, a sports car enthusiast, a doer.

Occasionally, one of the two had a brush with depression. When I say “brush with”, I don’t mean they were depressed personally…often physicians have patients who are depressed. But this friend’s observation has stuck with me for decades: ‘smart people often get depressed because they can see how a cause of pain can be so easily avoided.’

The two neighbor physicians were active here in Durham, even starting a suburban clinic on behalf of Duke Hospitals, as “intrapreneurs”…helping with real estate decisions, hiring the staff, computerizing and networking the whole office complex in the early 1990s when this was still new, and setting the medical practices. The clinic grew and prospered. But one day a patient, an ex-con, threatened the life of one of the doctors, the lives of all the staff and the lives of my friend’s family. My friend responding by beefing up clinic security and…arming up with personal weapons – shotgun, pistols, a rifle or two including a family heirloom M1 rifle.

The Duke clinic was taken over by UNC hospitals, as the two systems began eating up independent practices. These two physicians, who had previously started an entire clinic and been responsible for everything, found themselves ordered about by bureaucratic office managers sent by the UNC Systems. By 2008 it became too much, and by 2010 they moved out of state.

They now live in Alaska and they became Alaskans…carrying a loaded pistol on the front seat (for bears on long walks, perhaps), and flying their plane to medical assignments all over the state.

If you are a determinist, they you can see how two “intrapreneurs” became Alaskans. If you are a determinist and you mean what you write, then you’re not much longer for the U.S..

Two summers ago at my local atheists’ ethical society Sunday meeting, I found myself in a “roots” exercise sitting next to a woman who had just returned to the U.S. from six years living in Israel. She, also, had grown up in Peta Luma California, but since this was a “roots” morning, I learned much more about her past from her. Her grandfather was a young man in Czarist Russia, and a hundred years ago found himself with two choices: join the Czar’s Army, which would mean 20 years’ service, or join the Communist Revolution. He chose the Revolution. Years later, he was part of a group that emigrated from Russia, came to the U.S. and journeyed across the country and finally settled in Peta Luma California, where they started a chicken-raising commune. Apparently this is pretty famous. But my new roots friend also explained that her father, at family gatherings, would also say “without the Revolution we would have nothing.” I found it interesting that this new person’s ancestors came from Russia and kept strong Communist/Socialist beliefs, and my father’s family came from the same part of Russia, but he did well in business. My new friend and I might find ourselves on two different sides of political opinion, but we were both being “true to our roots”, we were both atheists and didn’t need the 10 Commandments to ‘honor our fathers and our mothers’.

Wherever your attitudes come from, they probably go as deep and there’s nothing much anyone can say or do or point out to you that’s going to change them. Attitude is a ‘country’ too, and you and I live on different sides of an ocean.

I have traveled to and lived in just a few other countries for short stretches. I don’t find America a cesspool. When I walk through malls and markets in my region, bi-racial couples are everywhere, something I wouldn’t have seen in my native Cleveland Ohio when I was growing up. I don’t find neighbors and friends , business acquaintances and casual acquaintances ‘greedy, heartlessly indifferent, or breathtakingly stupid’. The biggest divide I’ve seen in my small slice of the country was last year, and it was about the last election, when people argued about their picture of the world and its prominent people. Day to day people are not at each others’ throats. In general, they know enough to stay away from people they disagree with and leave each other alone.

I do not trust concentrations of power, which means I have little trust for Washington and the largest corporations. For example, I am de-Googling myself as fast as practical. But that’s off subject.

What I have found true about travel is that people that come from different places have many differences, and they work up their own local ways of dealing with reality, their environments, survival, and each other.

My closest former-Russian friend left the U.S. because he was told this was the “land of the free”, and all he’s seen is laws, corrupt politicians, and corporations telling the sheeple what to do and what to believe. He left to seek more freedom and a cheaper cost of living. He’s now living in Vietnam.

Whenever I think I have a good picture of reality, I remind myself that my descriptions, political and otherwise, are probably missing a great deal of information and hence might be completely wrong. Further, when I’m reminded of huge differences, say between me and another American over politics, politics being the vying for power over individuals and groups…that we have 7 and a half billion people living on the planet, most are not killing each other, (to paraphrase Vic praising science when he described its resulting aging populations ‘so many that the very large number of people themselves are a problem’)  and that alone tells me that humans are doing something socially and politically correct.

Suggestions and recommendations

1…If you so dislike the place, quit writing so much, quit reading so much that’s feeding your doom, gloom, and disgust, and do something about it. “Get off your ass” as some politician recently advised. I admit I have a prejudice towards action over speech, and this is what my prejudice advises you.

2…Cut out MSM…and even cut out atvoid-2 for a spell. I myself stay on for about four reasons, the largest being nostalgia for Vic. But I open less than a tenth of the posts…the rest of the posts are pretty predictable. Cut off cable TV. Use the savings to start a travel fund.

3…Take some of your savings and travel…as far away as possible for as long as possible and as soon as possible. I’ve heard that only 15 percent of U.S. citizens even has a passport. If you include all the immigrants to the U.S. who keep their passports active to visit relatives in their country of origin, this is a sorry figure of a majority of parochial sticks-in-the-mud. If I had a lot of money I’d buy as many U.S. citizens as I could a one-way plane ticket to as far away as possible, and give them an allowance to buy a ticket back, but not from the same airport. In traveling you will see what you will see – both good and bad in other places, and if you stay away long enough, you will feel somewhat alien when you return – perhaps you will find, as I did, the U.S. is weird, in its own way. But “weird” is not “a cesspool”.

And most Americans, never having traveled or lived somewhere else, are also ungrateful. Those who listen to the MSM telling them that everything is shit leave their domiciles framed and prepped to see nothing but shit, and….voila! All they see is shit. This is a positive feedback loop and confirmation bias all rolled into one.

When you travel you’re going to find so many differences, you won’t be able to deny them. You may find that you agree with non-Americans you meet on issue A, but disagree on issue B. You’re going to find that you agree on some major issues, but you really don’t like what they eat or how they smell or how they live day to day. Travel has a way of putting you deep in to these situations and you won’t need a politically-incorrect person like me to notice them.

4…Try Estonia. Cold, dark, stark, but they vote with their phones.

Try Eastern Europe, where I spend some time each year (prices are cheap, families are tight, but half the population earn their money outside the country and send it home…they can’t seem to get their post-Yugoslavian economy humming). All in all, you might choose family over economy – it’s warmer, and let’s face it, a humming economy can break up families. England was expensive when I was there last…if its guns you’re afraid of, few guns there. Try Isreal. Try China, where a close friend of mine spent time on construction projects and now says what our media reports about China is almost always wrong. Try Japan, where another classmate has found home…became the sole Gai-jin judo instructor in the country’s most prominent judo club, but who informs me that most young Japanese men are being raised as prissy boys. Try Vietnam, and if you run into my Russian freedom-seeking friend, tell him “hello”.

5…If a country move seems too much, try another state – try Alaska. Totally different than the lower 48. Of course I can’t even ask you to visit Flyover country, but you might visit, or at least pick up a National Geographic and read about it.

6…Try …something to get your poor, caring and sharing and intelligent self out of this cesspool of ignorance, because frankly, with your attitude, you couldn’t see positive things or solutions worth putting your shoulder to if you bumped into them.

Somewhat relevant perhaps, though I think I recall some people on this list say that they dislike/disagree with Chris Hedges.


…I think this is plausible, though maybe not the timescale. The US will not be overthrown militarily, and is not an empire in the same way as the others he mentions, with dominions and colonies to maintain. And the modern world, with its rapid communications, is very different even from the one that saw the sun set on the British Empire 60 years ago. Nor do I think that it will be supplanted, as Hedges suggests. I think it will remain a player. Even little UK remains a significant economic power, and Russia is again one of the world’s big actors less than 30 years after the “end of history”. For the US, the question is not so much whether it will remain a big player on the world stage (even perhaps primus inter pares, at least in the military domain), as whether it will maintain/restore its political traditions, or move closer to the Russian model of a gangster oligarchy (which seems more likely than China’s authoritarian state capitalism). I suppose the other question is whether the rest of the “democratic” world can hold together if the US fails. There are good reasons why Russia (and perhaps Trump too) is keen to see the EU implode – it is imperfect, badly tainted by the neoliberal virus, and democratically flawed, but it nevertheless embodies a particular political vision, as well as a powerful trading bloc. If the EU fragments, Canada may become the only option, if you want to remain in a world that is at least partly familiar. If you are prepared for profound dépaysement, your options are wider…

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Physicists report new, solid observation of gravitational waves

Although Henri Poincaré first suggested that in analogy to an accelerating electrical charge producing electromagnetic waves, gravitational waves are tightly associated to Albert Einstein, who first predicted their existence in 1916, in his famous general theory of relativity. His mathematical equations showed that massive accelerating objects (namely neutron stars or black holes orbiting each other) would disrupt the fabric of space-time, sending waves in the process, much like a stone thrown into a pond sends ripple in the water. However, later on in his work, Einstein started to doubt their existence. In 1936, Einstein and Nathan Rosen submitted a paper to Physical Review in which they argued that the gravitational waves could not exist in the full theory of general relativity. The paper was anonymously reviewed by mathematician Howard P. Robertson, who pointed out some miscalculations within the paper. Furious, Einstein withdrew the paper, but ultimately, one of his assistants, who had been in contact with Robertson, convinced Einstein that the criticism was correct. They rewrote the paper, but with exactly the opposite conclusions, supporting the existence of gravitational waves.

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What computers teach us about getting along


From an office at Carnegie Mellon, my colleague John Miller and I had evolved a computer program with a taste for genocide.

This was certainly not our intent. We were not scholars of race, or war. We were interested in the emergence of primitive cooperation. So we built machines that lived in an imaginary society, and made them play a game with each other—one known to engender complex social behavior just as surely as a mushy banana makes fruit flies.

The game is called Prisoner’s Dilemma. It takes many guises, but it is at heart a story about two individuals that can choose to cooperate or to cheat. If they both cheat, they both suffer. If they both cooperate, they both prosper. But if one tries to cooperate while the other cheats, the cheater prospers even more.

The game has a generality that appeals to a political philosopher, but a rigorous specificity that makes it possible to guide computer simulations. As a tool for the mathematical study of human behavior, it is the equivalent of Galileo’s inclined plane, or Gregor Mendel’s pea plants. Do you join the strike, or sneak across the picket line? Rein in production to keep prices high, or undercut the cartel and flood the market? Pull your weight in a study group, or leave the work to others?

Woe to those who did not know the code.

Our simulation was simple: In a virtual world, decision-making machines with limited powers of reasoning played the game over and over. We, as the unforgiving account-keepers, rewarded the ones who prospered and punished the ones who did not. Successful machines passed their strategies to the next generation, with the occasional slight variations designed to imitate the blind distortions typical of cultural evolution.

We also gave the machines a simple language to think with and enough resources to have memories and to act on them. Each generation, paired machines faced each other multiple times. This is how life appears to us: We encounter our trading partners over and over, and how we treat them has consequences. Our model for the world was two Robinson Crusoes encountering each other on the sands.

When we ran these little societies forward, we expected to confirm what many believed to be the optimal strategy for playing Prisoner’s Dilemma: tit-for-tat. A machine playing this strategy begins by keeping its promises, but retaliates against an instance of cheating by cheating, once, in return. Tit-for-tat is the playground rule of honor: Treat others well, unless they give you reason otherwise—and be reasonably quick to forgive.

Yet when we looked at the output of our simulations, where the strategies were free to evolve in arbitrary directions, we saw something very different. After an early, chaotic period, a single machine would rise rapidly to dominance, taking over its imaginary world for hundreds of generations until, just as suddenly, it collapsed, sending the world into a chaos of conflict out of which the next cycle arose. An archaeologist of such a world would have encountered thick layers of prosperity alternating with eras of ash and bone.

Instead of an orderly playground ruled by cautious, prideful cooperators, the population produced bizarre configurations that made no sense to us. That is, until one evening, in the office and after filling up pads of graph paper, we stumbled onto the truth. The dominant machines had taken players’ actions to be a code by which they could recognize when they were faced with copies of themselves.

SHIBBOLETH MACHINES: Simulations of our machines show initial levels of apparently random behavior giving way, around generation 300, to high rates of cooperation that coincide with near-complete domination by a single machine that drives others to extinction. This enforced cooperation collapses around generation 450. From then on, the system alternates between these two extremes. Green and yellow bands correspond to eras of high and low cooperation, respectively.

In the opening moves of the game, they would tap out a distinct pattern: cooperate, cheat, cheat, cooperate, cheat, cooperate (for example). If their opponent responded in exactly the same fashion, cheating when they cheated, cooperating when they cooperated, they would eventually switch to a phase of permanent cooperation, rewarding the opponent with the benefits of action to mutual advantage.

Woe, however, to those who did not know the code. Any deviation from the expected sequence was rewarded with total and permanent war. Such a response might take both machines down, in a kind of a digital suicide attack. Because the sequence was so hard to hit upon by accident, only the descendants of ruling machines could profit from the post-code era of selfless cooperation. All others were killed off, including those using the tit-for-tat strategy. This domination would last until enough errors accumulated in the code handed down between generations for dominant machines to stop recognizing each other. Then, they would turn against each other as viciously as they once turned against outsiders, in a kind of population-level autoimmune disease.

As long as the codes lasted we called them Shibboleths, after the tribal genocide recounted in the Old Testament Book of Judges:

And the Gileadites took the passages of Jordan before the Ephraimites: and it was so, that when those Ephraimites which were escaped said, Let me go over; that the men of Gilead said unto him, Art thou an Ephraimite? If he said, Nay; / Then said they unto him, Say now Shibboleth: and he said Sibboleth: for he could not frame to pronounce it right. Then they took him, and slew him at the passages of Jordan: and there fell at that time of the Ephraimites forty and two thousand.

Shibboleths are a common feature of human culture and conflict. Finns who could not pronounce yksi (meaning “one”) were identified as Russians during the Finnish Civil War. Tourists in downtown Manhattan quickly out themselves if they pronounce Houston Street like the city in Texas.

Here our machines had used them to dominate a population so effectively that no others could survive. Even after the era was over, it was their descendants that inherited the ashes. The blind hand of evolution had found a simple, if vicious, solution.

It was a stark and brutal social landscape. But we had given our machines very limited resources to think with. How would two perfectly rational machines act in a conflict, if they each knew the other was similarly perfectly rational? By the very nature of rationality, two completely rational beings, confronted with the same problem, ought to behave in the same fashion. Knowing this, each would choose to cooperate—but not out of altruism. Each would recognize that if it were to cheat, its opponent would too, making them both losers in the game.

The two endpoints establish a spectrum. At one end are our minimally-calculating machines, parochial zero-points of culture that naturally, we found, distilled down to a vicious tribalism. At the other end is the inevitable cooperation of the perfectly rational agent.

On this line between beastly machines and angelic rationality, where do we find the human species?

If we humans are super-rational, or at least on our way there, there is reason to be optimistic. Francis Fukuyama might have been thinking along these lines when he penned his end-of-history thesis in 1992. Though Fukuyama’s argument was rooted in 19th-century German philosophers such as Friedrich Nietzsche and Georg Wilhelm Friedrich Hegel, we might rewrite it this way: A sufficiently complex simulation of human life would terminate in a rational, liberal-democratic, and capitalist order standing against a scattered and dispersing set of enemies.

Fukuyama’s argument was based not just on philosophical speculation, but on a reading of then-current events: the collapse of communism, the flourishing of electronic media, the apparently frictionless opening of borders, and a stock market beginning an epic bull run.

Today his thesis seems like a monument to the dreams of an earlier era (one chapter was titled “The Victory of the VCR”). Our cultures are evolving today, but not, it seems, toward any harmony. The chaos of the 21st century makes our simulations feel immediately familiar. Two decades after 9/11, even the Western liberal democracies are willing to consider dark models of human behavior, and darker theorists than Fukuyama.

Carl Schmitt, for example, who saw the deliberative elements of democracy as window dressing on more authoritarian forms of power. Or Robert Michels, whose studies of political inequality led him to see democracy as a temporary stage in the evolution of society to rule by a small, closed elite. As intellectuals at both political extremes increasingly see the possibility of a rational political order as a fantasy, Shibboleths take up their role in defining racial, national, and religious boundaries and appear once again to be ineradicable features of political life.

There is a great, and rich, valley between these philosophies, and another between the computer models that match them—between the simple, violent and less-than-rational agents that John Miller and I simulated, and the super-rational cooperators that Fukuyama might have considered to be waiting at the end of history. The models, at least, encourage a guarded optimism.

Researchers associated with meetings at the Machine Intelligence Research Institute (MIRI) in Berkeley have studied the behavior of rational but resource-limited machines who could inspect each other’s source code. Such transparency might seem to solve the problem of cooperation: If I can predict what my opponent will do by simulating his source code, I might decide cheating is not worth the cost. But what if my opponent’s code includes a simulation of what I will do as a consequence of running that simulation, and tries to exploit that knowledge? Without the symmetry of perfect rationality, this problem leads to some extreme mental contortions.

Some of the machines in MIRI’s bestiary might remind you of people you know. “CliqueBot,” for example, simply cooperates with anyone who shares the same source code. It only cares about codes that match its own letter-for-letter. “FairBot,” on the other hand, tries to look beneath surface differences to prove that an opponent will cooperate with someone like itself. Informally, FairBot says, “if I can prove that my opponent will cooperate with me, I’ll cooperate with him.”

How do these machines get along? While the full solution is a paradox of regress, studies of predictive machine behavior in a Prisoner’s Dilemma standoff provide the comforting answer that mutual cooperation remains at least possible, even for the resource-limited player. FairBot, for example, can recognize similarly-fair machines even if they have different source code, suggesting that diversity and cooperation are not impossible, at least when intelligence is sufficiently high.1

Even the genocidal machines at the violent end of the spectrum may carry a heartening lesson. They emerged from the depths of a circuit board, simulated on a supercomputer in Texas. They had no biological excuse to fall back on. Maybe we, too, shouldn’t make excuses: If a behavior is so common as to emerge in the simplest simulations, perhaps we ought neither to fear it, nor to idolize it, but to treat it, the same way we do cancer, or the flu.

What if we saw tribalism as a natural malfunction of any cognitive system, silicon or carbon? As neither a universal truth or unavoidable sin, but something to be overcome?


Simon DeDeo is an assistant professor at Carnegie Mellon University, where he runs the Laboratory for Social Minds, and external faculty at the Santa Fe Institute.


On this line between beastly machines and angelic rationality, where do we find the human species?”

 Humans are just somewhere in a middle, but with some additional and rather tricky features: very often they have poor rationality (because of poor knowledge of facts and poor understanding) and some evolutionary inherited needs: besides the need for elementary survival, shelter and procreation they have some specific  needs for self-actualization (which often is expressed as the need for material goods and conditions far above the elementary), the need for limbic attachment, love and, at the end, the need for something sacred, for something higher than daily survival, for some end and sense. 

“What if we saw tribalism as a natural malfunction of any cognitive system, silicon or carbon? As neither a universal truth or unavoidable sin, but something to be overcome?”

Tribalism, or, a bit wider, human nature, is not a natural malfunction or unavoidable sin, it is a great gift from our evolution we can understand and use properly, i.e., for our benefit. 

“we might rewrite it this way: A sufficiently complex simulation of human life would terminate in a rational, liberal-democratic, and capitalist order standing against a scattered and dispersing set of enemies”.

To day we can rewrite it in this way: scientific simulation of human life will terminate in a rational and emotion-rich world, where all rules are not only based on real human features but use them. I.V. 

Posted in Human Evolution, Understand and Manage Ourselves | Leave a comment

Кен Йебсен: Наш враг – это СМИ порождающие в нас безразли

Pareizi. Bet mūsu problēmas ir daudz, daudz plašākas. Viens no labākajiem skatījumiem ir Noam Chomsky.

Bet arī šeit viens ir ieraugāms: Peļņas pacelšana vērtības līmenī noved pie tā, ka sabiedrībā izplatās, neapzināti tiek kultivēta vienaldzība, cinisms un vērtību vakuums. Tā ir ekonomiska parādība, vai, ja plašāk, tad – Homo sapiens ģenētikas izpausme. I.V.

Posted in Are We doomed?, Understand and Manage Ourselves, Values and Sense of Life | Leave a comment

Why political correctness fails – Why what we know ‘for sure’ is wrong

Why political correctness fails – Why what we know ‘for sure’ is wrong

Myth 8. We don’t need religion; our leaders are all knowing and all powerful.

What has been astounding to me, as I have looked into the situation, is that the scientific evidence seems to point in the direction of a literal Higher Power governing our Universe. It is not clear whether this higher power is the Laws of Physics, or whether it is some outside “God” that created the Laws of Physics.

We humans live on Earth. It is easy for us to think that our primary purpose in life is to care for and protect the Earth. Unfortunately, with our need for supplemental energy, this is not possible. Even at an early date, our need for resources exceeded what was sustainable. Joshua (in Joshua 17:14-18 relating to the period around 1400 BCE) instructs the tribes of Joseph to clear the trees from the hill country to have enough land for his tribe. This practice was clearly unsustainable; it would lead to erosion of the soil on hilltops. Even at that early date, high population and the need for resources to provide for this high population was conflicting with earth’s sustainability.

If our God is either the Laws of Physics, or some force giving rise to the Laws of Physics, then our God is really the God of the Universe. The limitations of the current Earth are no problem. God (or the Laws of Physics) could create a new Earth, or 1 million new Earths, if He chose to. Thus, from God’s point of view, it is not clear that there is any point to today’s environmentalism. There is a need not to poison ourselves, but “saving the earth” for other species after humans, or for a new set of humans who somehow will use much less energy, doesn’t make much sense. Humans can’t use much less energy; even if we could, our energy use would always be on an upward slope, headed to precisely where we are now.


In practice, people need a religion or a religion-substitute. People need a basic set of beliefs with which to order their lives.

Our leaders today have proposed the Religion of Success, with its belief in Science, and the power of today’s leaders, as the new religion. This religion has appeal, because it denies the limits we are up against. Life will continue, as if we lived on a flat earth with unlimited resources. This story is pleasant, but unfortunately not true.

Donald Trump, with his version of conservatism, presents another religion. This religion seems to be focused on justifying the allocation of wealth away from the poor, toward the rich, through tax breaks for corporations and the wealthy. This is part of the process of “freezing out” the poor people of the world, when there are not enough resources to go around.

I personally am not in favor of religions that originate from political groups. I would prefer the “old fashioned” religions based on ancient documents from one or another of the world’s religions. We are clearly facing a difficult time ahead. Perhaps early people had insights regarding how to deal with troubled times. Admittedly, we don’t know for certain that heaven can be in our future. But when things look bleak, it is helpful to see the possibility of a reasonable outcome.

Gail Twerberg!

You have trespassed the Occam’s razor principle. If we assume that some deity has created the laws of Physics, then we must answer the question: Where did this Higher Power come from?

The Myth 8: we don’t need religion. You write: “In practice, people need a religion or a religion-substitute. People need a basic set of beliefs with which to order their lives.”

We are genetically pre-programmed for something bigger than our daily existence, for something sacred and holy, for some sense, some goal and objective, and, at the end, for some hope for eternal life. Contemporary science gives to us all of this: Our task, possibility and responsibility is a long-term survival of humanity, or, as Carl Sagan said, to preserve our Universe’s matter to get conscious of itself. No greater task is possible. If we will solve the task of transferring our consciousness to other physical environment, we will obtain even some sort of ‘eternal life’. 

Posted in Human Evolution, Values and Sense of Life | Leave a comment

Max Tegmark: ‘Machines taking control doesn’t have to be a bad thing’

” development of AI is an even more pressing concern than climate change. Yet if we’re looking at creating an intelligence that we can’t possibly understand, how much will preparation affect what takes place on the other side of the singularity? How can we attempt to confine an intelligence that is beyond our imagining?

Tegmark acknowledges that this is a question no one can answer at the moment…”

Let us try to answer this question. Intelligence behind our imagining will have external world models (EWM) we don’t know now. This means that we will not understand this higher intelligence’s decisions and behavior. How we can attempt to confine it? Wrong question. We will not, if we will be clever. We must to think about this issue to day, now. We have to teach the new systems in the best way possible in accordance with our contemporary knowledge, to create the best human values we know. Is there a basic, a most important value we can teach our future machines? Yes. It is the long-term survival of humanity, IOW, the consciousness in matter of any form. I.V. 

Of course, the question of how we will use the accomplishments  of humanity remains: 

BAE Systems’s Taranis stealth aircraft

BAE Systems’s Taranis unmanned stealth aircraft prototype, described as ‘the first autonomous drone’. It looks that we will not avoid some self-destruction.

Posted in Artificial Intelligence, Values and Sense of Life | Leave a comment

Dažas domas par svarīgāko cilvēka dzīvē

Jau lasījām, ka mēs esam emociju mašīnas (skat., piemēram, Marwin Minsky, The Emotion Machine), tas nozīmē, ka galvenokārt mūsu domāšanu un rīcību nosaka vairāk vai mazāk apzināta vēlēšanās saņemt, piedzīvot pozitīvas emocijas, vai, kā tautā saka, laimi.

Šī laimes sajūta cilvēkiem ir unikāla, stipra, var teikt, visaptveroša, visu pārveidojoša. Šī vajadzība un piepildījums, lidojums, harmonija un laimes sajūta, kad gadās vajadzību piepildīt, ir mūsu ģenētiskais mantojums. Visi gribam, cenšamies, bet kāpēc tikai nedaudziem izdodas? Bērnībā, jaunībā mēs neapzināti veidojam tā cilvēka tēlu, ar kuru kopā būsim laimīgi. Un to mēs nedomājam kā loģiski izteiktu domu, bet jūtam. Kad šo cilvēku satiekam, šīs sajūtas ir kā gandrīz kā atklājums: tās ir subjektīvi nemaldīgas sajūtas, kaut kas līdzīgs reibonim, kurš piepilda ar laimes, visa varēšanas, pilnības, sakārtotības sajūtu ķermeni un apziņu, uzlabo ķermeņa sajūtas, intelekuālās, emociju un fiziskās spējas. Izskatās, ka evolūcija ļoti pārliecinoši mūs ir sagatavojusi kopdzīvei un bērnu audzināšanai. Vai tam var sagatavoties, vai to var optimizēt? Vai padarīt ilgstošu? 50% šķirto laulību skaits rāda, ka šeit ir problēmas. Kā visas spējas, mūsu spēja mīlēt un sajust mīlestību ir jāizkopj, tāpat kā valodu – to jāiemācās. Katrs sāk ar no vecākiem mantoto gēnu loteriju. Tālāk nāk iedzimto spēju, tendenču un vajadzību izkopšana. Amerikāņu sabiedrībā iegūto rezultātu izteic ar vārdiem nature times nurture (daba, reizināta ar izkopšanu jeb ‘barošanu’). No psihologu un ārstu sarakstītām grāmatām zinām, ka galvenais veselīga cilvēka psihes un iekšējās pasaules un, var teikt, arī laimīgas dzīves veidošanas noteikums ir – ar vecāku mīlestību pildīta bērnība. Valodas mēs visvieglāk un labāk iemācāmies bērnībā. Mīlestība arī ir valoda. Nekavēsimies pie tiem, kam nav paveicies, kas gēnu loterijā vai bērnībā no vecākiem ir mazāk saņēmuši. Pateikšu tikai vienu psihoterapeitu bieži atkārtotu domu: jebkuru valodu var iemācīties jebkurā vecumā. Vajag gribēt (pa īstam) un strādāt.

Kad lasu žurnālos par tiem laimīgajiem otro vai trešo reizi precētajiem, kas viens otru ‘beidzot atraduši’, tad apziņu pilda domu lavīnas. Kāpēc tas viss tik neilgi (viena no mūsdienu pasaules lielākajām speciālistēm mīlestības jautājumos Dr. Helen Fisher raksta, ka ‘reibonis’ parasti ilgst no dažiem mēnešiem līdz dažiem gadiem), kāpēc viņiem bija jānodzīvo daudzus gadus, lai saprastu un sajustu, ka tas, ar ko dzīvo kopā, vairs nav tas, ar ko precējās, kāds pamats ir domāt, ka šoreiz viņi, kā pasakās rakstīts, dzīvos laimīgi ‘līdz mūža galam’? Vai uz šiem jautājumiem ir atbildes? Fakts, ka visā pasaulē šķir laulības un mānās un krāpjas, saka, ka vienkāršas atbildes nav. Bet, dažas pamatpatiesības ir, un tās der zināt.

Pirmais iespaids. Ir visspēcīgākais, jo kopā ar to tiek veidotas vērtības, kas noteiks turpmāko rīcību. Tā ir, jādomā, ne tikai Homo sapiens īpašība, bet visu informācijas apstrādes mašīnu īpašība: kamēr nav daudz iespaidu, tikmēr nav ar ko salīdzināt. Tādēļ pirmais iespaids ir visspēcīgākais. No šī fakta izriet vēl viena cilvēku (un, jādomā, visu informācijas apstrādes mašīnu) problēma: mēs nespējam novērtēt, kamēr neesam zaudējuši. Un tā vien šķiet, ka šī zaudējuma sajūta izpaužas ļoti daudzās pat ikdienišķās situācijās, kuru pieredze tika veidota ‘pirmās laimes’ laikā.

Jaunības pirmajos gados, protams, mūsu spēja uztvert, izjust un izteikt mīlestību, ir mazāk izkopta, nekā vēlākos gados. Tādēļ, kad dzīvē gadās ierosināt zemapziņā izveidoto ‘sapņu tēlu’ (satikt ‘īsto’), kad vajadzības ir vairāk izkoptas, tad izjustās emocijas ir daudz dziļākas un plašākas. Piemēram, ja cilvēks mīlestības valodu mācījies kopā ar varenu mūziku vai kādu citu mākslas veidu, tad nākošais satiktais cilvēks ierosina mūsos veselas simfonijas: tās mūsos sāk skanēt.

Mēs visi maināmies. Var teikt, ka mēs esam kā kalnā kāpēji, kuri šobrīd satikušies un domā, ka visu atlikušo mūžu kāps kopā. Bet izrādās, ka tas tā nav: iekšējās pasaules un sevis veidošanas ceļš katram jāiet pašam. Un tā mēs arī darām. Tādēļ nav brīnums, ka pēc kāda laika izrādās, ka mēs esam attālinājušies viens no otra. Slēdziens ir vienkāršs: ilgāk kopā nodzīvot izdodas tikai tiem, kas daudz dara kopā. Kopā svin dzīvi. Kādu nepieciešamu, svarīgu daļu. Mums nevajag prasīt, lai operas solists nodarbotos ar eksakto zinātni. Bet, no otras puses, mēs zinām, ka operas solisti ar bokseriem parasti neprecas. Tomēr. Kaut kādai intelektu lauku kopībai jābūt.

Mēs pieredzam, ka daudzi laulātie pēc kāda laika: 1) pazaudē sākotnējo aizrautību (mēs jau zinām, ka tas ir dabisks process); 2) nav izveidojuši kādu kopēju atkarību; 3) atrod kādu dziļu aizrautību nākošo reizi.

Atkarībā no mantiskā stāvokļa un spējas sevi saprast viņi rada, izveido tādu pašu dzīvi, kā iepriekšējo, vai labāku, tādu, kura nav nolemta izjukšanai. Kas ir pamatā? Laikam jau tā lielā, abpusējā un naivā aizrautība, – tādā nozīmē, ka mēs rīkojamies, kaut arī apzināti, bet esam nolemti tā rīkoties, jo tas varbūt ir vienīgais (laimes) ceļš, kuru evolūcija mums iedevusi, kas ļauj visu sākt no jauna. Ar pilnīgu tīrības, piepildījuma, un, var pat teikt, svētuma sajūtu. Ar dziļu īstuma sajūtu, kas saka, ka šeit, kopā ar šo cilvēku, mēs varam būt īsti un patiesi. Ja abiem paveicies būt domājošiem (tādā nozīmē, ka viņi sevi redz, saprot un spēj veidot), tad var paveikties, un atlikušajā dzīvē viņiem nebūs jāmeklē ‘nākošo lielo laimi’.

Nozīmīga, svarīga mūsu ģenētiskā mantojuma daļa ir vajadzība pēc kaut kā lielāka par mūsu ikdienu, par mums pašiem. Vajadzība pēc jēgas, mērķa un uzdevuma. Un milzīgs, dziļš gandarījums par šo vajadzību apmierināšanu. Mīlestība nav izņēmums. Arī šeit vislielāko piepildījumu dod patiesīgums, saturs un jēga, īstums un svētums. Tādēļ visas izpriecas, izklaides un ‘atpūtas pēc darba’, ja tajās netiek ielikts augstāks nozīmīgums un jēga, ir surogāti, kuri dod pavisam nelielu daļu no tā piepildījuma, kādu mums sagatavojusi evolūcija. To pašu var teikt par visiem mākslas darbiem, bet tā nav šīs esejas tēma.

Vai vispār ir iespējams izvairīties no Helen Fisher aprakstītās ‘aizrautības laika’ izbeigšanās? Es domāju, ka ir. Jāizveido kopēja atkarība, lielāka vai mazāka, viena vai vairākas. Piezemētā variantā tā ir kopēja māja, dārzs vai veikali, citā variantā tie var būt TV seriāli, mūzika vai cita mākslas nozare. Tā var būt arī limbiskā tuvība, pieķeršanās un atkarība, kam maz kopēja ar TV redzamo. Tā var būt arī domāšana. Ar to es negribu apzīmēt sabiedrībā izplatīto paviršību. Ar to es domāju domāšanu par cilvēces izdzīvošanai svarīgām lietām, savas dzīves pakārtošanu tām, un gandarījuma un jēgas saņemšanu no tā.

Citādā skatījumā var teikt tā. Visi cilvēki dzīvo dažādās pasaulēs: ģimenē, darbā, skolā, sabiedriskās vietās mēs piedalāmies izklaides, kultūras un sporta pasākumos. Šajās pasaulēs ir daudzas mazākas telpas, piemēram, ģimenē ir mājas darbi (ēdienu gatavošana, darbs darbnīcā, garažā, dārzā, vai uz lauka, nodarbības ar bērniem). Galvenais divu cilvēku ilgstošas sadzīves un veiksmīgas sadarbības noteikums ir kopīgas telpas. Ja diviem cilvēkiem ir daudzas svarīgas un nozīmīgas kopīgas dzīvestelpas, atrašanās kurās sagādā gandarījumu un piepildījumu, tad var teikt, ka liela viņu kopdzīves daļa ir patīkama un abiem nepieciešama. Slēdziens un kritērijs ir vienkāršs: ja jums ir daudzas kopējas esības telpas, kurās jūs pavadāt daudz sava laika, un atrašanās tajās jums ir patīkama, svarīga un nepieciešama, tad jums ir paveicies. Viena no svarīgākajām laulāto dzīvestelpām ir seksuāla tuvība: par  tās vajadzību piepildīšanu evolūcija mums ir iedevusi milzīgu labsajūtu, gandarījumu un piepildījumu. Vēl vairāk: arī veselību. Slēdziens ir skaidrs: ja jums nav kopējas svarīgākās dzīves telpas, un jūs nevarat tās izveidot, tad cerību (dzīvot piepildītu dzīvi) nav. Visa laulāto dzīve ir balanss, līdzsvars starp to, kas abiem kopējs, un to, kas katram savs. Līdzsvaru veido labsajūta un prieks par kopā pavadīto laiku un, no otras puses, atziņa, ka dažas dzīves telpas nav un nebūs kopējas. To izturēt palīdz dažas domas: atbildības sajūta par kādreiz izdarīto izvēli. Un vispār: ir vērts vīrišķīgi pieņemt, ka mēs neesam un nevaram būt vienādi. Vienkārši – tas nemaz nav iespējams. Un vēl: mēs nepārtraukti maināmies. Šajā aspektā galvenais ir – kurā virzienā? Ja kopējās dzīvestelpas palielināšanas virzienā, tad viss ir OK. Ja kopējās dzīvestelpas iet mazumā, tad jāsāk domāt.

Un vēl viens būtisks aspekts: ja mēs gribam dzīvot īsti, tad (daudzām, galvenajām, svarīgākajām) vērtībām jābūt kopīgām. Jo tās nosaka mūsu rīcību un gandarījumu visās dzīvestelpās.


Kas ir dzīves kvalitāte un kā to mērīt?

Aptauju materiāli:

Ingenious: Helen Fisher. Talking sex, brains, and commitment with the best-selling scientist of love.

Vēl vairāk:

Pēdējā raksta virsraksts ir maldinošs, galvenā autores doma ir:  Our brain is soft-wired to attach slowly to a partner. Protams, visur ir izņēmumi.

Vēl par vienu svarīgu mūsu apziņas nozari, vai, pareizāk, novirzi. Par pornogrāfiju un citām novirzēm, piemēram, homoseksuālismu, mūsu sabiedrībā ir pieticīgi priekšstati.  Klods Barass (KDi, 16.02.2017) par pornogrāfiju:

“Bērni uzzina par seksualitāti caur pornogrāfiskiem materiāliem, kuri varētu būt viņu vecākiem vai kurus viņi paši atrod. Bērni sagrābsta daudz informācijas, taču viņiem neviens neko nepaskaidro. Ja bērniem ir piekļuve pornogrāfijai, ko viņi ieraudzīs? Vardarbīgas izpausmes un spēles ar dominēšanu. Tāpēc ir svarīgi runāt par to ar bērniem.”

Pornogrāfija ir patoloģiska novirze, cilvēka vērtīgāko vajadzību izveidošana un izkopšana līdz atkarībai, kas daudzkārt samazina pārējo vajadzību apmierināšanu, t.i., notiek slimīga interešu sašaurināšana un pārējo vajadzību ignorēšana. Galvenais pornogrāfijas kaitējums ir nevis ‘vardarbīgas izpausmes’ un ‘spēles’, bet vienkāršs fakts, ka pornogrāfija, kaut arī, kā visas atkarības, dod maksimālu un slimīgu piepildījumu, tā dod, sakāpinātu, bet sašaurinātu pieredzi, kas ir aptuveni desmitā daļa no tā piepildījuma, kuru dod plašāka seksuālo vajadzību apmierināšana, kas saistīta ar darbu, mākslu, mūziku, izglītību, domāšanu, un, visbeidzot, ar cilvēka esības nozīmīguma apzināšanos. Citiem vārdiem, notiek indivīda apziņas, iekšējās pasaules un vērtību degradācija, kas robežojas ar debilitāti. To var redzēt un dzirdēt, ielūkojoties darbojošos personu sejās un ieklausoties viņu sarunās.

No malas vieglāk redzama pornogrāfijas izpausme ir atkarība, kuras izpausmes ir spiesti pieredzēt apkārtējie cilvēki. Ar atkarību saslimušie pamazām visu dzīvi pakārto savai novirzei. Tā nav viegli ārstējama slimība. Kā tā rodas? Nezinoši, sevi nesaprotoši, nepietiekoši emocionāli izglītoti cilvēki savas iekšējās pasaules izaugsmes un mīlestības problēmas risināt nespēj un aiziet pa vieglāko, peļņas tīkotāju piedāvāto ceļu: samaksā un iegrimst izdabājošā, bet patīkamā nevarībā. Šajā atkarībā nevarības apziņu katrs atkarīgais cenšas noslāpēt ar aizrautīgu pakļaušanos, kas uz laiku ļauj aizmirst savu apkaunojošo atkarību.  Kas šeit vainīgs? Sabiedrība, kura nezin pati un nevēlas un bieži arī nespēj izglītot (pasargāt no novirzēm) savus bērnus. Mūsu instinktus, līdzīgi kā visu progresa atribūtus, nevainosim, tie mums ir tādi, kādi ir.

Homoseksualitātes jomā stāvoklis ir līdzīgs. Tas ir liels kauns un sabiedrības pagrimuma rādītājs, ka novirze tiek pacelta normas līmenī (Vācijā pieņemts likums, kas legalizē geju un lezbiešu laulības), un sabiedrības locekļu vairākums to neapzinās. Vai arī ir tik flegmātiski un apātiski, ka pieņem notiekošo klusējot. Homoseksualitāte ir patoloģiskas iedzimto tendenču izkopšanas izpausme. Zināms, ka iedzimtās tendences arī apraksta ‘zvanveida’ (normālā sadalījuma) līkne, bet, tiklīdz evolūcija mums ir pateikusi, ka nākotnei šādi novirzīti indivīdi nav vajadzīgi, mums der to redzēt un saprast.

Homoseksualitātes un pornogrāfijas propaganda izveido patoloģiskas vajadzības un novirzes, kas nodara lielu kaitējumu dalībniekiem un sabiedrībai. For instance, 20 years ago, I took up a sexual harassment lawsuit on behalf of a young woman—a state employee—who claimed that her boss, a politically powerful man, had arranged for her to meet him in a hotel room, where he then allegedly dropped his pants, propositioned her and invited her to perform oral sex on him.

Despite the fact that this man had a well-known reputation for womanizing and this woman was merely one in a long line of women who had accused the man of groping, propositioning, and pressuring them for sexual favors in the workplace, she was denounced as white trash and subjected to a massive smear campaign by the man’s wife, friends and colleagues (including the leading women’s rights organizations of the day), while he was given lucrative book deals and paid lavish sums for speaking engagements.

William Jefferson Clinton eventually agreed to settle the case and pay Paula Jones $850,000.


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What Christians believe about evolution and the supposed naivety of atheists

It is understandable that Christian commentators want to denigrate atheists. A common tactic is to claim that atheists think that most Christians are Biblical literalists and thus only criticise fundamentalist and literalist religion. The atheist is thus painted as naive, not very thoughtful and a bit ignorant. The tactic also implies that atheists have not managed to produce significant critiques of liberal religious theology.

This is mostly wrong; atheists are well aware of liberal theology, and nowadays most New Atheistic critiques address liberal theology (literalist theology is simply not a worthwhile target any more; I can’t think of anyone bothering since Tom Paine’s Age of Reason, as long ago as 1807).

But, Christians like to think otherwise, as exemplified by an article this Sunday in The Observer by “leading Catholic commentator” Catherine Pepinster.

The article is summarised by her Tweet:

The article itself states that:

According to the research, nearly two-thirds of Britons — as well as nearly three-quarters of atheists — think Christians have to accept the assertion in Genesis that God created the world in six days and rested on the seventh.

Continue reading

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Noam Chomsky August 14, 2017 – Surviving the 21st Century

… future generations will not forgive us for our silence …

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Мем о доброй старой Англии

Noteikti, daļa īstenības tur ir. Mēs lasām neplānotu atzīšanos, stāstu par sevi, kurā autors cenšas pastāstīt par valsti un sabiedrību, kurā dzīvojis. Bet galvenais šajā stāstījumā – autoram pašam nav tā, kam viņš iedomājas pāri stāvam. Kultūras un vērtību. I.V. 

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A Thorium-Salt Reactor Has Fired Up for the First Time in Four Decades

The road to cleaner, meltdown-proof nuclear power has taken a big step forward. Researchers at NRG, a Dutch nuclear materials firm, have begun the first tests of nuclear fission using thorium salts since experiments ended at Oak Ridge National Laboratory in the early 1970s.

Thorium has several advantages over uranium, the fuel that powers most nuclear reactors in service today. First, it’s much harder to weaponize. Second, as we pointed out last year in a long read on thorium-salt reactors, designs that call for using it in a liquid form are, essentially, self-regulating and fail-safe.

The team at NRG is testing several reactor designs on a small scale at first. The first experiment is on a setup called a molten-salt fast reactor, which burns thorium salt and in theory should also be able to consume spent nuclear fuel from typical uranium fission reactions.

The tests come amid renewed global interest in thorium. While updated models of uranium-fueled power plants are struggling mightily to get off the ground in the U.S., several startup companies are exploring molten-salt reactors. China, meanwhile, is charging ahead with big plans for its nuclear industry, including a heavy bet on thorium-based reactors. The country plans to have the first such power plants hooked up to the grid inside 15 years. If they pull it off, it might just help usher in a safer future for nuclear power.



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Should You Worry About the Global Pursuit for AI Domination?

One thing is for certain: the race to achieve AI supremacy is certainly on. Russian state news organization RT reports that Vladimir Putin believes “artificial intelligence is the future, not only for Russia, but for all humankind.” In fact, he went a step further, adding that it comes “with colossal opportunities, but also threats that are difficult to predict. Whoever becomes the leader in this sphere will become the ruler of the world.”

The state news agency also reports that Putin wouldn’t abuse that kind of power. “If we become leaders in this area, we will share this know-how with entire world,” he’s reported to have said, “the same way we share our nuclear technologies today.” You can probably take that part with a pinch of salt.


Is the AI really so dangerous? Nick Bostrom has defined Superintelligence as ‘an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom and social skills.’ If we accept this definition, then it follows that AI will not wipe us out. On the opposite: AI will use all human accomplishments and create much much better humanity. I.V.

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Why Oil Prices Can’t Bounce Very High; Expect Deflation Instead

Why Oil Prices Can’t Bounce Very High; Expect Deflation Instead

Reasonable, seems to be very close to reality. I.V.

To, ka krīze tuvojas, redz daudzi. Tā būs neizbēgami. Vairākums ir nolemti turpināt izklaidēties, bet dažas domas tiem, kuri grib mēģināt izdzīvot. 

Galvenā vērtība būs nevis nauda vai pat zelts, bet – enerģija, pārtika un pajumte. Ko katrs var darīt? Ko krāt? Vai konservus, kā padomju laikā? Un atompatvertnes būvēt? Katrs var tikai atbilstoši savām iespējām. Ja  krāt, tad, piemēram, degvielu un nevis naudu. Ieročus, ar ko savas izdzīvošanas apstākļus aizstāvēt? Zināms, ka tas arī tiek un tiks darīts.

Ko atstāt, ko iedot nākotnei, bērniem plašākā skatījumā? Spēju izdzīvot ilglaicīgi. Kas pie tā pieder, mēs zinām: vieta, mājas attālākā vietā, kur naturāla saimniecība nodrošina pašpietiekamību. Un bērni, kas spēj šādā vidē strādāt un izdzīvot. Domāju, ka tas ir galvenais ieguldījums, kuru šodien ir jēga un iespēja veidot. I.V. 

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Knowing More and Understanding Less in the Age of Big Data

We used to say “seeing is believing”; now googling is believing. With 24/7 access to nearly all of the world’s information at our fingertips, we no longer trek to the library or the encyclopedia shelf in search of answers. We just open our browsers, type in a few keywords and wait for the information to come to us. Indeed, the Internet has revolutionized the way we learn and know, as well as how we interact with each other. And yet this explosion of technological innovation has also produced a curious paradox: even as we know more, we seem to understand less.

While a wealth of literature has been devoted to life with the Internet, the deep philosophical implications of this seismic shift have not been properly explored until now. Demonstrating that knowledge based on reason plays an essential role in society and that there is much more to “knowing” than just acquiring information, leading philosopher Michael Patrick Lynch shows how our digital way of life makes us overvalue some ways of processing information over others, and thus risks distorting what it means to be human.

With far-reaching implications, Lynch’s argument charts a path from Plato’s cave to Shannon’s mathematical theory of information to Google Glass, illustrating that technology itself isn’t the problem, nor is it the solution. Instead, it will be the way in which we adapt our minds to these new tools that will ultimately decide whether or not the “Internet of Things”―all those gadgets on our wrists, in our pockets and on our laps―will be a net gain for humanity. Along the way, Lynch uses a philosopher’s lens to examine some of the most urgent issues facing digital life today, including how social media is revolutionizing the way we think about privacy; why a greater reliance on Wikipedia and Google doesn’t necessarily make knowledge “more democratic”; and the perils of using “big data” alone to predict cultural trends.

To, ka mūsu smadzenes nav piemērotas mūsdienu sabiedrībām, mēs jau zinām. Ir interesanti palūkoties uz dažām izpausmēm. 

And yet this explosion of technological innovation has also produced a curious paradox: even as we know more, we seem to understand less.

Problēma ir plašāka. Visas modernās sabiedrības ir pazaudējušas pamatvērtības. Kaut arī tās visbiežāk ir visai tālu no realitātes, tās vismaz bija un tika lietotas domāšanā un sevis un ārējās pasaules modeļu veidošanā. Pamatu nepieciešamība ir zināma jau gadu tūkstošiem, mēs daudzās kristiešu bībeles vietās lasām senu jūdu gudrību, kas saka, ka nedrīkst celt ēku uz smiltīm, bez pamatiem. Bez pamatvērtībām mēs nevaram izveidot vērtību skalu (nav atskaites punktu), realitātei atbilstošus sevis un apkārtējās pasaules modeļus, un dzīves mērķi jeb jēgu. Pamatvērtību vietā mūsdienu postmodernisms ir atnesis relatīvismu (viss ir relatīvs) un tā dabiskas sekas – paviršību. 

Saprast nozīmē spēt prognozēt jeb spēt paredzēt apkārtējās vides un cilvēku reakcijas uz mūsu rīcību. Ja šīs reakcijas sakrīt ar mūsu prognozi, mēs sakām, ka mēs saprotam sevi un citus, savu sabiedrību un pasauli. Ja nespējam izveidot pareizus, adekvātus ārējās pasaules modeļus, tas nozīmē, ka mēs sevī un ārpus mums notiekošo nesaprotam. To masveidā novērojam mūsu dzīvē: 90 % dažādu speciālistu, kuri ieņem atbilstošus amatus, nav speciālisti. Viņiem ir nosaukums, alga un štata vieta, bet nav kompetences. Raimonds Pauls saka: diletantisms. Piemēram, mākslā. Aktieri, mākslinieki un režisori, tā vietā lai iedotu skatītājiem vērtības, paziņo, ka ‘dzīvei nav jēgas’ (Kroders) vai arī, ka dzīves jēga ir bērnu dzimšana (Hermanis). Piemēram, politikā un valsts pārvaldē notiek savstarpēja sacensība par sevis apliecināšanu (un nevis patiesības meklēšana) un, vēl  vienkāršāk, sagrābt iespējami vairāk materiālo labumu un palikt nesodītam. 

reason plays an essential role in society and that there is much more to “knowing” than just acquiring information, leading philosopher Michael Patrick Lynch shows how our digital way of life makes us overvalue some ways of processing information over others, and thus risks distorting what it means to be human.

Nenoliedzami, ka saprātam ir liela nozīme visās sabiedrībās, bet mēs nedrīkstam aizmirst, ka galvenokārt mēs esam ’emociju mašīnas’ (Marwin Minsky), ka emocijas par 90% nosaka mūsu izvēli un rīcību. To mēs novērojam visā pasaulē, tās t.s. militārajos konfliktos, ‘globālajās problēmās’ un katra indivīda dzīvē (laulības dzīves notikumi un konflikti). Mums jāredz, ka tikmēr, kamēr mēs dzīvojam ar evolūcijas iedoto apbalvojumu un sodu sistēmu, mums savas sabiedrības dzīvi jāpakārto šīm milzīgajām evolūcijas veidotajām vajadzībām: izdzīvošana pāri visam, gandrīz neierobežota vajadzība pēc materiālo labumu un iespēju iegūšanas, vajadzība pēc limbiskās pieķeršanās un mīlestības, un, visbeidzot, vajadzība pēc kaut kā lielāka par mūsu ikdienu un mums pašiem, pēc kaut kā svēta un visam pāri stāvoša. 

Līdzīgas atziņas lasām arī citā grāmatā: 

Yehezkel Dror: For Rulers: Priming Political Leaders for Saving Humanity from Itself

In this striking book, Yehezkel Dror bravely goes where few authors dare, offering a big-picture view of the fateful choices facing the human species. He urges humankind to adopt unconventional survival and thriving strategies, including elevating the future of humanity above state interests, limiting the production and spread of dangerous knowledge and tools, and strengthening humanity’s collective deliberative capacity. The author confronts the evolutionary trap of science and technology ensnaring unprepared humankind by providing it with awesome future-shaping power, which contemporary values and institutions are unable to handle. Dror warns that tribal and nationalist values, the inability to learn from history, and mediocre leadership will catastrophically endanger the future of human life, making radical, even painful, innovations essential. According to Dror, the prevailing form of politics is obsolete. Instead, he argues urgently for a new type of political leader – “Homo Sapiens Governors” – willing and able to fulfill the daunting mission to save humanity from itself. Recognizing that the tyrannical status quo will try to prevent essential transformations, Dror predicts new crises making what is still unthinkable clearly compelling – and that humankind will have to choose: learn rapidly to survive and thrive, or perish. YEHEZKEL DROR is professor emeritus at the Hebrew University of Jerusalem. Recognized as a founder of modern policy studies, he integrates multi-disciplinary scholarship with extensive personal experience as a global advisor into a novel paradigm on alternative evolutionary futures of humanity – as shaped by fateful choices humanity has never before faced.

Pašreizējā izglītības sistēma ir nepiemērota ne tikai izpratnes veidošanai, bet arī cilvēces izdzīvošanai tālākā nākotnē: 

Posted in Human Evolution, Understand and Manage Ourselves, Values and Sense of Life | Leave a comment

How Will Capitalism End?

After years of ill health, capitalism is now in a critical condition. Growth has given way to stagnation; inequality is leading to instability; and confidence in the money economy has all but evaporated.

In How Will Capitalism End?, the acclaimed analyst of contemporary politics and economics Wolfgang Streeck argues that the world is about to change. The marriage between democracy and capitalism, ill-suited partners brought together in the shadow of World War Two, is coming to an end. The regulatory institutions that once restrained the financial sector’s excesses have collapsed and, after the final victory of capitalism at the end of the Cold War, there is no political agency capable of rolling back the liberalization of the markets.

Ours has become a world defined by declining growth, oligarchic rule, a shrinking public sphere, institutional corruption and international anarchy, and no cure to these ills is at hand.

As always in evolution, people will change only when their survival is threatened. There is a cure at hand: human nature, as E.O.Wilson has it described. There is the only way: a system, compatible with human nature and based on it. This means private property, but restricted, possibility to confirm, to witness oneself, but restricted, to have attachment and love, sense and sanctity, but restricted, to have longer life, but restricted. And, at least, to have a possibility to receive forgiveness, but restricted. 

Democracy in its simplest form (voting for people or decisions) is non-viable, impossible. For long-term survival of humanity only one step of democracy is necessary: voting for survival. The following steps and decisions are to be made by the AI program, specially designed for this purpose. A program, an intelligence, that is far above current average human intelligence,  that can avoid the current shortcomings of human nature. 

Contemporary societies are far away from such a system, it still waits its realization. This means deaf penalty is a must, like it is used not only by the evolution, but also by humans themselves (in their wars). The reality is camouflaged by slogans about human rights. And a system of ‘regulatory institutions’, using penalties in accordance with the trespassers damage to the society. Such a system will rise, will be gradually created on the ruins of our society. I.V.

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Garry Kasparov: Don’t fear intelligent machines. Work with them

Everything nice and correct, but the machines will dream! I.V.

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The Emotion Machine by Marwin Minsky

By  Shansay
This review is from: The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind
Marvin Minsky, along with a small group of scientists, coined the term, “artificial intelligence.” He also wrote Society of Mind, a tour de force that paved the way for thinking about getting machines to think. The Emotion Machine, his more recent work, presents ideas that shake up the field of psychology. His suggestions about the ways in which emotions “cascade” as a series of logical events in response to life circumstances offer a picture that is both physiologically and cognitively rational. Beyond suggesting what machines can accomplish, Minsky’s suggestions are highly innovative regarding the field of psychology. These topics, in addition to many others spanning varied fields, make the book amazing.
HALL OF FAMEon December 17, 2006

Progress in the design and creation of intelligent machines has been steady for the last four decades and at times has exhibited sharp peaks in both advances and applications. This progress has gone relatively unnoticed, or has been trivialized by the very individuals who have been responsible for it. The field of artificial intelligence has been peculiar in that regard: every advance is hailed as major at the time of its inception, but after a very short time it is delegated to the archives as being “trivial” or “not truly intelligent.” It is unknown why this pattern always occurs, but it might be due to the willingness of researchers to engage in philosophical debate on the nature of mind and the possibility, or impossibility, of thinking machines. By indulging in such debates, researchers waste precious time that is better used dealing with the actual building of these machines or the development of algorithms or reasoning patterns by which these machines can solve problems of both theoretical and practical interest. Also, philosophical musings on artificial intelligence, due to the huge conceptual spaces in which they wander aimlessly, are usually of no help in pointing to the right direction for researchers to follow. What researchers need is a “director” or “set of directors” that are familiar with the subject matter, have both applied and theoretical experience in the field of artificial intelligence, and that eschew philosophical armchair speculation in favor of realistic dialog about the nature and functioning of intelligent machines.

The author of this book has been one of these “directors” throughout his professional career, and even though some of his writings have a speculative air about them, many others have been very useful as guidance to those working in the trenches of artificial intelligence. One can point to the author’s writings as both inspiration and as a source of perspiration, the latter arising because of the difficulty in bringing some of his ideas to fruition. It would be incorrect to state that the author’s ideas have played a predominant role in the field of artificial intelligence, but his influence has been real, if sometimes even in the negative, such as his commentary on the role of perceptrons.

There are intelligent machines today, and they have wide application in business and finance, but their intelligence is restricted (but highly effective) to certain domains of applicability. There are machines for example that can play superb chess and backgammon, being competitive with the best human players in this regard, but these machines, and the reasoning patterns they use in chess and backgammon cannot without major modification indulge themselves in performing financial prediction or proving difficult theorems in mathematics. The building of intelligent machines that can think in multiple domains is at present one of the most difficult outstanding problems in artificial intelligence. Some progress is being made, but it has been stymied again by overindulgence in philosophical speculation and rancorous debates on the nature of mind and whether or not machines can have true emotions.

Humans can of course think in multiple domains. Indeed, a good human chess player can also be a good mathematician or a good chef. The ability to think in multiple domains has been christened as “commonsense” by many psychologists and professional educators, and those skeptical of the possibility of machine intelligence. It is thought by many that in order for a machine to be considered as truly intelligent, or even indeed to possess any intelligence at all, it must possess “commonsense”, in spite of the vague manner in which this concept is frequently presented in both the popular and scientific literature.

The nature of “commonsense” is explored in an atypical manner in this book, and in this regard the author again shows his ability to think outside of the box and phrase issues in a new light. This is not to say that advice on how to implement these ideas in real machines is included in the book, as it is not. But the ideas do seem plausible as well as practical, particularly the concept of a “panalogy”, which is the author’s contraction of the two words “parallel analogy”. A panalogy allows a machine (human or otherwise) to give multiple meanings to an object, event, or situation, and thus be able to discern whether a particular interpretation of an event is inappropriate. A machine good in the game of chess could possibly then give multiple interpretations to its moves, some of which may happen to be similar to the interpretations given to a musical composition for example. The machine could thus use its expertise in chess to write musical compositions, and therefore be able to think in multiple domains. On the other hand, the machine may realize that there are no such analogies between chess and musical composition, and thus refrain from attempting to gain expertise in the latter. Another role for pananalogies, which may be a fruitful one, is that they can be used to measure to what degree interpretations are “entangled” with each other. Intepretations, which are the results of thinking, algorithmic processing, or reasoning patterns as it were, could be entangled in the sense that they always refer to objects, events, or situations in multiple domains. A panalogy, being a collection of interpretations in one domain, could be entangled with another in a different domain. The machine could thus switch between these with great ease, and thus be effective in both domains. It remains of course to construct explicit examples of panalogies that can be implemented in a real machine. The author does not direct the reader on how to do this, unfortunately.

The author also discusses a few other topics that have been hotly debated in artificial intelligence, throughout its five-decade long history, namely the possibility of a conscious machine or one that displays (and feels!) genuine emotions. The nature of consciousness, even in the human case, is poorly understood, so any discussion of its implementation in machines must wait further clarification and elucidation. Contemporary research in neuroscience is giving assistance in this regard. The author though takes another view of consciousness, which departs from the “folk psychology” that this concept is typically embedded in. His view of consciousness is more process-oriented, in that consciousness is the result of more than twenty processes going on in the human brain. An entire chapter is spent elaborating on this view, which is highly interesting to read but of course needs to be connected with what is known in cognitive neuroscience.

“The nature of consciousness, even in the human case, is poorly understood..” Not so anymore. See definition in a previous article. I.V. 

It remains to be seen whether the ideas in this book can be implemented in real machines. If the author’s views on emotions, commonsense, and consciousness are correct, as detailed throughout the book, it seems more plausible that machines will arise in the next few years that have these characteristics. If not, then perhaps machine intelligence should be viewed as something that is completely different from the human case. The fact that hundreds of tasks are now being done by machines that used to be thought of as the sole province of humans says a lot about the degree to which machine intelligence has progressed. Whenever the first machines are constructed to operate and reason in many in different domains, it seems likely that they will have their own ideas about how to direct further progress. Their understanding of ideas and issues may perhaps be very different than what humans is, and they may in fact serve as directors for further human advancement in different fields and contexts, much like the author has done throughout a major portion of his life.


on November 5, 2006
Anyone working on cognitive systems will want this book in their library. In reviewing THE EMOTION MACHINE there are two lines of criticism that seem important. Firstly, with the behaviorists I would argue that introspection is both frequently inaccurate and unscientific. Secondly, and more significantly, most of Minsky’s theories have not been developed to the level of detail needed in order to formulate actual algorithms. (To be fair there is Riecken’s “M system” (in SOFTWARE AGENTS, J. M. Bradshaw, Ed., MIT Press, 1997) and Singh’s thesis (EM-ONE, PhD thesis, MIT, June 2005) which are at least a start in that direction.)
On the positive side I am in general agreement with Minsky that thought can be decomposed into subroutines like: 
remembering (search), generalization, comparison, explanation, deduction,
organization, induction, classification, concept formation, imagemanipulation, feature detection, analogy, compression, simulation, value assessment. 
My list appears in Asa H: A hierarchical architecture for software agents (Transactions of the Kansas Academy of Science, vol. 109, No. 3/4, 2006). Minsky calls these “ways to think” and a partial list appears on pages 226-228 of THE EMOTION MACHINE. My own Asa H software uses exactly these mechanisms but my architecture is not nearly as complex as what Minsky is looking for.

 Max Hodges10 years ago

All the bizarre reviews posted here are testimony to the kinds of bad assumptions, misconceptions and retarded psychology that Minsky is up against. Minsky’s book is full of deep, penetrating insight. But most of the reviews here seem to be full of the reviewer’s own (misguided) ideas and opinions and have little to do with the book Minsky wrote. Secondly, and more significantly, most of Minsky’s theories have not been developed to the level of detail needed in order to formulate actual algorithms.

Dennett: The research world is going to be impatient with Marvin because they are eager for computational models that really work. Marvin is saying, “Wait a minute, let’s work out some of the high-level architectural details in a way that’s still very loose, very impressionistic. It’s too early to build the big model.”
Minsky: Actually, I could quarrel with that. I think the architecture described in The Emotion Machine is programmable. If I could afford to get three or four first-rate systems programmers, we could do it. You can get millions of dollars to drive a car through a desert, but you can’t get money to try to do something that’s more human.

Marwin Minsky has written a book about emotions but has not written much about how the emotions influence the human decisions and behavior. But the emotions are very important: they change significantly the results of thinking and our decisions. Maintaining the subroutines Minsky has formulated we can define thinking a bit wider and more exactly (see previous article): 

Thinking is the activation of event streams from the past or imagined future, marking them by symbols, and applying the rules of logic and laws of nature (to the degree they are known to the system) to the EWM, without executing corresponding actions.

At least for 90 % we are emotion machines, this means that our decisions and external world models (EWM) they are using often do not correspond to reality, are false. Because the values used in EWM are oriented for positive emotions but not for reality. This is the source of conflict between the ’emotions and mind’, the commonly known issue.  This is the source of our so called ‘global problems’. If contemporary humans want to survive, they have to create the new balance between emotions and rational analysis: today our genetic heritage makes optimal balance hard to achieve.  I.V.

on June 9, 2007

I agree with the reviewer who noted how odd it was that a book titled “The Emotion Machine” does not discuss Joseph LeDoux, even if only to refute him. But I think that the problem is with the title, not the book. I found many of Minsky’s insights very helpful – it is a very good book about how machines think. And if you are not a dualist, then those insights apply to people too. The book is very well organized and clearly written, and helps you think about thinking. I especially enjoyed his discussion of qualia (although he does not use the term), and why he thinks it is not quite the problem that so many philosophers want to make it.

Minsky’s main take on emotions is that emotional states are not fundamentally different from other types of thinking, and that the entire dicotomy of rationality v. emotion is misleading. He prefers to view them all as different ways of thinking – of utilizing various mental resources at one’s disposal, some conscious and some not. He organizes his discussion of difficult material very well, but I wish there was more grounding in the underlying neural anatomy of human emotion.

Emotional states are fundamentally different from other types of thinking not only because they are created in a different region of brain (limbic brain), but because they use completely different EWM with values, oriented for positive emotions.  I.V. 


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AI, engineering approach


In this paper author formulates definitions of basic notions and proposes definitions and conditions necessary for achieving general artificial intelligence (AGI).

Author maintains that the last big hurdle in achieving AGI in robots is the fact that they don’t create external world models (EWM).


Artificial intelligence, Emergence, Consciousness, External world models, Thinking, Learning.


  1. Current state.

The common features (random search, memories, learning, thinking, and EWM) necessary for creation of AI are known [1], [2], but the conditions for emergence of these features are not considered: We believe consciousness will result as an emergent behavior if there is adequate sensor input, processing power, and learning. [3].

Human-like intelligence is referred to as strong AI. General intelligence or strong AI has not been achieved yet and is a long-term goal of AI research. In conferences and hundreds of papers there are complicated discussions about the consciousness and AI. But some essential notions are missing.

1.1. Intelligence and its constituents are emergent processes. In animals simplest features are inherited genetically (random search, memories, learning), and after the birth more complicated features are developed: learning, thinking, consciousness, and EWM. In artificial machines these processes and their emergence conditions must preprogrammed: it is impossible to train robots to achieve features, for which evolution has spent millions of years. The first is preprogramming the features, tendencies and rewards; the second is to support, to create the conditions for the emergence and development of more complicated features: thinking, consciousness, and EWM. This means to determine, to define the emergence conditions and implement them.

1.2. Thinking about one model is described in [4]: For the robot to learn how to stand and twist its body, for example, it first performs a series of simulations in order to train a high-level deep-learning network how to perform the task—something the researchers compare to an “imaginary process.” This provides overall guidance for the robot, while a second deep-learning network is trained to carry out the task while responding to the dynamics of the robot’s joints and the complexity of the real environment. 

It is impossible to preprogram thinking for all possible actions and processes: the structure of this one process has to be replicated and adapted for uncountable number of other processes.

1.3. Contemporary robots are preprogrammed machines with distinct behaviors. When confronted with new and unknown situations these robots don’t have adequate behavior. The main issue and problem is the emergence of EWM. Some AI emergence conditions are counted in [1], [2], [3]. Hopeful systems are with input sensors, actuators and body distinct from environment, where creation of unrestricted number of EWM can be induced [4].

1.4. Step in the direction of domain-independent reinforced learning (RL) is deep learning, corresponding results are achieved with PR2 [5]. US Berkeley researcher Levine says: For all our versatility, humans are not born with a repertoire that can be deployed like a Swiss army knife, and we don’t need to be programmed. Instead we learn new skill over the course of our life from experience and from other humans.

The reality is different: some minutes after the birth most animals start using genetically inherited movements (drinking mother’s milk, following the mother, running, swimming or flying). These movements are not learned just after the birth but sought out from huge genetically inherited library and induced by the reward system. These movements were learned and fine-tuned by previous generations of individuals, and after the birth they are recognized and used after some tries.

Robot builders have to copy this evolutionary experience: millions of movements by contemporary robots first have to be learned slowly and after that used – taken from library and optimized and fine-tuned for real conditions. Creation and replication of EWM and learning then follows. But it takes much more time [6].

1.5. Deep learning is close to the way evolution happens [9]: Instead of a programmer writing the commands to solve a problem, the program generates its own algorithm based on example data and a desired output.

1.6. The necessity of models and their improving via reinforcement learning is mentioned in [7]:

With model-free approach, these works could not leverage the knowledge about underlying system, which is essential and plentiful in software engineering, to enhance their learning. In this paper, we introduce the advantages of model-based RL. By utilizing engineering knowledge, system maintains a model of interaction with its environment and predicts the consequence of its action, to improve and guarantee system performance. We also discuss the engineering issues and propose a procedure to adopt model-based RL to build self-adaptive software and bring policy evolution closer to real-world applications.

1.7. The generalization in AI is still a problem: AI programs …were successful at specific tasks, but generalizing the learned behavior to other domains was not attempted. How can generalized intelligence ever be realized? This paper will examine the different aspects of generalization and whether it can be performed successfully by future computer programs or robots [8].

1.8. Jeff Hawkins has named three fundamental attributes of the neocortex necessary for the intelligence to emerge: learning by rewiring, sparse distributed representations, and sensorymotor integration [13]. These three attributes provide and support the intelligence emergence conditions 3.1-3.4.



  1. Definitions of basic notions.

It is impossible to create something not defined. Without definitions science is impossible. But all definitions are temporal.

Generation of information in living systems is accomplished via random search, which creates the entropy space, and selection, which eliminates the not appropriate, not useful states or processes.

2.1. Intelligence is information processing system’s (IPS) ability to achieve its goals by adapting its behavior to changing environment, using pre-programmed (genetically inherited or obtained from environment) information, and optimize its behavior by creating and using models of environment and predictions about the environment’s reactions.

2.2. Artificial intelligence is the simulation of intelligence in machines.

2.3. EWM-s are preprogrammed or learned collaboration algorithms between the IPS and the environment. Activation of EWM enables IPS to predict the EW events. When these predictions are correct, we say that IPS understands the EW.

2.4. General artificial intelligence (AGI) is human-like intelligence in which IPS achieves its goals by creating unrestricted number of EWM and predicts the EW events.

2.5. Simple learning is accomplished via random moves, sensory feedback and choosing the best moves. More complex learning is accomplished via activation of existing and creation of new EWM (and corresponding behaviors, skills, values, preferences).

2.6. Thinking is the activation of event streams from the past or imagined future, marking them by symbols, and applying the rules of logic and laws of nature (to the degree they are known to the system) to the EWM, without executing corresponding actions. This allows IPS to predict the EW reactions and to plan, to choose own behavior.

2.7. Consciousness is the model of self.




  1. Intelligence and EWM emergence conditions.

3.1. The features created by the structure and programming: ability and tendency to memorize EW event strings (The ability to recognize and predict temporal sequences of sensory inputs) [12], neuron colon level-like structure which provides the ability to filter out the principal, basic lines in all input patterns (generalization [1], [2], [8]), and huge number of connections between neurons which provides the possibility to activate similar patterns [10].

3.2. Sensor signal processing, actuator control (transition from multi-coordinate world of output actuator moves to 4 coordinate world of output actions), and own action evaluation and learning.

3.3. Random search, selection, generalization, reward and punishing system, copying or multiplying the existing EWM or creation of new EWM and movement libraries. For complicated EWM this is achieved by thinking.

3.4. The ability to create the model of self, which receives EW signals and executes internal program’s decisions. This is called consciousness. All sensory streams are integrated and the map of EW is created, where the receiving and acting subject plays the main role. Lyle N. Long names it Unity: All sensor modalities melded into one experience [1].

3.5. The hierarchical reward and punishing system, which creates values – the laws saying what is good and what has to be avoided.

3.6. For General AI the ability to learn, understand spoken and written language and the ability to speak is necessary. For understanding of language the words and symbols of language must be connected with the own sensory experience and EWM .




  1. Emergence.

All atoms and molecules of the physical world, all physical processes, chemical reactions, human made products, inventions and all living beings are emergent property systems. If we have good models of systems and processes, we explain and predict the emerged properties by properties of parts and known physical laws. I will not consider here the declarations about impossibility of generation or understanding emergence. Human intelligence, consciousness and thinking are complex emergent property processes, for which we can define and implement the emergence conditions.

Many emergence conditions in contemporary AI systems are embedded structurally, e.g., big number of connections between the neurons, which allows the activation of alike memories and processes, a layer-like structure of NN, which allows generalizing, creating basic lines and abstract notions for incoming pictures, reward and punishing system which directs behavior. In living entities these features are inherited genetically, in artificial systems they must be preprogrammed.

Consciousness emerges in complicated multi-level systems, therefore we can’t reduce them to the properties of neurons. There are many complexity levels between the basic elements (neurons) and final emerged properties: sensors, neurons, neuron colons, output activators, and processes: memory reading and writing, generalizing, thinking, reward systems, EWM generation and development. But we can formulate the emergence conditions and, when implemented, the consciousness will emerge. The first results are already obtained [4], [6], [9].

The teaching-programming of robot will be like raising human infant [1], [8]. Randomly generated actuator moves will create thousands of event streams (with sensory signals added to each action) recorded in robot’s memory. If after many trials and actuator moves robot stops hitting obstacles, starts grabbing and moving objects, and shows collaboration elements (definite reactions to external visual, audio or touch signals) with EW, or, as in [4], learns to stand vertically on its own feet, or imitates the learned sounds, this means that robot has created maps and models of the EW.

How to teach the robot to adapt to environment, to optimize the own body moves? In a way all animals and humans do: connect input sensor signals to the current situation and processes, remember them, and use them next time by like situations.

Strong AI will arrive only when we will manage our robots to create the models of external world by themselves.  In animals and humans everyday usage of EWM is partly unconscious. This means that the essential lines are maintained but concrete details are abandoned.  For example, all animals unconsciously know and use the Earth’s gravitational force, know that all objects of external world have hard surfaces, but some are soft or liquid, some are hot or cold, and adjust their behavior.



  1. Discussion and Conclusions.

Emergent behavior is the main process of intelligent systems. EWM and consciousness emerge only in complex systems. This is a price we have to pay for AI and creation of consciousness. Complexity of the system can be measured by the number of parts and emerged properties.

It is not possible to pre-program EWM for all life situations. If future robots will not create EWM for all life situations by themselves, they will not have true intelligence:


Rule-based systems and cognitive architectures require humans to program the rules, and this process is not scalable to billions of rules. The machines will need to rely on hybrid systems, learning, and emergent behavior; and they will need to be carefully taught and trained by teams of engineers and scientists. Humans will not be capable of completely specifying and programming the entire system; learning and emergent behavior will be a stringent requirement for development of the system [11].


Living beings are genetically prepared for adapting to unknown and changing environment. The first environment all living beings are confronted with after the hatch or birth is own body. Movement is a fundamental characteristic of living systems [8]. In relatively short time and series of random moves they recognize and start using basic genetically inherited actions. Developing and improving these series of actions via learning and thinking leads to creation of EWM. Human body has about 500 muscles, an approximate robot can have about 50 actuators. Researchers have realized that it is impossible to solve the math equations in real time environment even for simple moves, because it takes “minutes or hours of computation for seconds of motion” [8]. This means that all moves are to be optimized via slow supervised learning and after that used automatically, taken from the library. Successful actions are stored and their algorithms are copied and used for the next models.

The intelligence and its constituents are gradual features [1], [11], which can be more or less outspoken, developed and recognizable. Conditions 3.(1-6) facilitate the emergence of thinking, creation of EWM and consciousness, but the degree of necessity of each feature is not known.

The approach with actuator movement library creation and transferring the library to new robots (see 1.3) will have some problems: actuator change is coupled with corresponding program change, in order to transfer the experience of previous machines, the corresponding transcoding of control commands will be necessary. In this sense the evolution of robots will be like the evolution of living beings: in order to transfer the experience from previous generations, new individuals must keep the organs and actuators that ‘understand’ the old commands (e.g., our triune brain).

There are no ‘easy’ or ‘hard’ problems of consciousness [1]. In all IPS notions, senses and emotions (e.g., feeling of some color or feeling of self) are connected with personal sensory experience, which is unique for every individual. In this view talking about “what it is like to be” is nonsensical. As long as we have not reached the direct transfer of information (copying neuron connections) between the individuals, it is impossible to know exactly their inner experience. It is an axiomatic truth of information transfer, and there is no mystics or something impossible.

The task of creating consciousness is challenging: Consciousness is an emergent property, and the first conscious robot will be a bit surprising: “It will be as astounding and frightening to humans as the discovery of life on other planets” [1].

The emergence conditions, tendencies, proclivities, rewards, values, and moves, learned by previous units, must be pre-programmed. The further development of these features and EWM is accomplished by the system.

After the IPS presents the simplest EWM for mechanical moves, it must be taught like human or animal infants [11], [12].





  1. Lyle N. Long, Review of Consciousness and the Possibility of Conscious Robots, JOURNAL OF AEROSPACE COMPUTING, INFORMATION, AND COMMUNICATION Vol. 7, February 2010,

  1. Lyle N. Long, and Troy D. Kelley, The Requirements and Possibilities of Creating Conscious Systems,
  2. Lyle N. Long, Troy D. Kelley, and Michael, J. Wenger, The Prospects for Creating Conscious Machines,
  3. Robot Toddler Learns to Stand by “Imagining” How to Do It.
  4. Sarah Yang, New ‘deep learning’ technique enables robot mastery of skills via trial and error
  5. Jean-Paul Laumond, Nicolas Mansard, Jean Bernard Lasserre, Optimization as Motion Selection Principle in Robot Action, Communications of the ACM, ACM, 2015, 58 (5), pp.64-74

  1. Han Nguyen Ho, Eunseok Lee, Model-based Reinforcement Learning Approach for Planning in Self-Adaptive Software System, Proceedings of the 9th International Conference on Ubiquitos Information Management and Communication, Article No. 103,

  1. Troy D. Kelleyand Lyle N. Long, Deep Blue Cannot Play Checkers: The Need for Generalized Intelligence for Mobile Robots,

  1. The Dark Secret at the Heart of AI, Intelligent Machines by Will Knight,

April 11, 2017,

  1. Jeff HawkinsSubutai Ahmad, Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex,
  2. Imants Vilks, When Will Consciousness Emerge? Bulletin of Electrical Engineering and Informatics, Vol 2, No 1: March 2013
  3. Yuwei Cui*, Chetan Surpur, Subutai Ahmad, and Jeff Hawkins, Continuous online sequence learning with an unsupervised neural network model,arXiv:1512.05463v1.
  4. Jeff Hawkins, What Intelligent Machines Need to Learn From the Neocortex,

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Scientific Naturalism: A Manifesto for Enlightenment Humanism

The success of the Scientific Revolution led to the development of
the worldview of scientific naturalism, or the belief that the world
is governed by natural laws and forces that can be understood,
and that all phenomena are part of nature and can be explained
by natural causes, including human cognitive, moral and social
phenomena. The application of scientific naturalism in the human
realm led to the widespread adoption of Enlightenment humanism,
a cosmopolitan worldview that places supreme value on science
and reason, eschews the supernatural entirely and relies
exclusively on nature and nature’s laws, including human nature.

From scientific naturalism to Enlightenment humanism
Scientific naturalism is the principle that the world is governed by natural laws and forces
that can be understood, and that all phenomena are part of nature and can be explained by
natural causes, including human cognitive, moral and social phenomena. According to a
Google Ngram Viewer search, the term “scientific naturalism” first came into use in the
1820s, picked up momentum from the 1860s through the 1920s, then hit three peaks in
the 1930s, 1950s and early 2000s, where it is now established as a core component of
modern science. It incorporates methodological naturalism, the principle that the
methods of science operate under the presumption that the world and everything in it
is the result of natural processes in a system of material causes and effects that does not
allow, or need, the introduction of supernatural forces. “Methodological naturalism”
spiked dramatically in use in the mid-1990s and continues climbing into the 2000s,7
most likely the result of the rise in popularity (and polarization) of “scientific creationism”
and Intelligent Design Theory, the proponents of which complained that methodological
naturalism unfairly excludes their belief in what I have called methodological supernaturalism,  or the principle that supernatural intervention in the natural world may be invoked to explain any allegedly unexplained phenomena, such as the Big Bang, the fine-tuned cosmos, consciousness, morality, the eye, DNA and, notoriously, bacterial flagella.



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