What’s worse is that the impassioned hostility arising from existential stakes has intensified over the years into the horrifically unspeakable face-to-face brutality witnessed in the Hamas attack followed by the collateral toll from Israeli retaliation on terrified civilians in Gaza.

The convergence of a series of shifts in the region over recent decades that are a consequence of previous conflicts lay behind the outbreak of this war.

The 1982 Invasion Of Lebanon

In my personal experience, there is a sense of déjà vu today with the terrorism of the Palestine Liberation Organization and the Israeli invasion of Lebanon in 1982. In response to back-and-forth raids across the border and the attempted assassination of the Israeli ambassador to the U.K. by the offshoot Abu Nidal faction, then Israeli Prime Minister Menachem Begin launched “Operation Peace for Galilee” aimed at expelling Yasser Arafat and his PLO from their safe operating base in Lebanon.

The onslaught was already raging when I arrived by ship from Cyprus with a delivery of emergency medical supplies for the hospital at the American University of Beirut. I checked into what I was mistakenly told was the only safe place in town, the Alexandre Hotel in East Beirut. All the windows had been blown out the day before by a car bomb intended for Ariel Sharon, then the Israeli general leading the military operation who had held a meeting there.

Whenever gunfire erupted somewhere nearby, as it did regularly, everyone hit the ground for cover. Crossing into besieged West Beirut, controlled by a patchwork of PLO and local militias, each contesting the other’s arbitrary authority, was a perilous exercise. If you turned into a wrong intersection, those controlling their sliver of space would fire machine guns mounted on the back of pickup trucks in your direction.

Israeli tanks and artillery constantly shelled from the hills, leaving plumes of dark smoke rising high into the sky. The neighborhood around the Green Zone crossing line between East and West was obliterated into piles of rubble. The PLO leadership cowered in safe-house bunkers, waiting out the siege, plotting escape routes and trying to negotiate their survival. The turmoil toppled the Lebanese government and brought the Christian Phalangists and their militia, allied with Israel, to power.

Just as now, American warships were sent off the Mediterranean coast, at that time to assist the evacuation of the trapped and defeated PLO, which embarked for Greece and on to exile in Tunisia. With the PLO gone, Phalangist fanatics entered the Sabra neighborhood and adjacent Shatila refugee camp in Beirut and massacred hundreds of civilians, including women, children and the elderly.

I drove down to the northern Israeli border through southern Lebanon, passing columns of massive Merkava tanks trailing menacing dust clouds as they headed north. Beyond Sidon and Tyre, I encountered the wholesale wreckage of village after village, like Ain al-Hilweh, where Palestinians had taken refuge as far back as 1948.

In an effort to stabilize Lebanon and act as a buffer between warring parties, U.S. and French forces were stationed in Beirut. In October 1983 suicide bombers blew up their barracks, killing 241 American and 58 French troops. Then U.S. President Ronald Reagan ordered an end to the mission.

It was out of the ruins of Lebanon and the ensuing political vacuum that the Shiite Hezbollah arose as a major force in the country. Instead of the “40 years of peace” Menachem Begin sought with his invasion, what remains today is an Iran-sponsored, well-armed and battle-hardened threat on Israel’s northern border aligned with Hamas in its determination to destroy the Jewish state.

The 1982 war was the beginning of the end of the PLO as an effective enemy of Israel. It became so weak as time went on that present Israeli Prime Minister Benjamin Netanyahu and his extremist cabinet felt little need to take the Palestinian Authority in the West Bank, which morphed from it, seriously. For the PLO’s part over the years, it never seemed to miss an opportunity to miss an opportunity, as Israeli statesman Abba Eban famously quipped, with each successive failure of leadership strengthening the desperate sentiments that fueled the rise of Hamas.

When the PLO did seize an opportunity during the Oslo process, it never gained traction in the face of intransigent constituencies in Israel. As long ago as 1996, Netanyahu flatly told me in an interview that a two-state solution as envisioned in that accord would never happen. “The fledging Palestinian state that Arafat and the PLO are trying to establish is not what the Israeli people want,” he declared summarily.

The U.S. Invasion Of Iraq

When the U.S. ousted Saddam Hussein in 2003 in the name of expunging post-9/11 terrorism once and for all in the Middle East, King Abdullah of Jordan was alarmed by what he saw as the inexorable end result. He warned that by removing the Iraqi dictator, the mostly Shia population of a liberated nation would turn their sympathies toward Iran, shifting the entire balance of power in the region and creating a “Shia crescent” that stretched from Bahrain to Hezbollah in Lebanon.

When I raised this concern at a lunch with then-U.S. Vice President Dick Cheney at the World Economic Forum in Davos in 2004, he just stared back uncomprehendingly as if the thought never occurred to him, or just merely assuming that enduring American influence in Iraq allied with Saudi Arabia would somehow checkmate Tehran forever.

Two decades on, radical Iran-aligned and supported forces, including the Sunni Hamas, which deny the very legitimacy of the Israeli state and oppose any reconciliation with it by the Arab world, are showing their vicious mettle in yet another round of eye for an eye, tooth for a tooth meting out of desert justice.

Not A Black Swan Event

In short, as Noema editorial board member Fareed Zakaria correctly analyzed on his CNN show, GPS, the Hamas attack may have erupted unexpectedly for those looking elsewhere, but it was not a black swan event appearing from nowhere. It was a “white swan” event that can be readily traced back to a wave of developments over the last half-century in the Middle East that are the unintended outcome of manifold mistakes, missteps and misapprehensions. It is worth watching Fareed’s commentary here.

Another commentary worth listening to is that of Yuval Noah Harari, the Israeli author of “Sapiens” and other works on human nature. As a historian, he always looks at how seeds planted by actions at one time can foster unforeseen repercussions later on.

He also draws a general observation from the recent civil strife in Israel over the rule of law and role of the Supreme Court in checking the power of the executive and the parliament, which the Netanyahu government has sought to diminish on behalf of a theocratic fringe. Speaking of the failed defense of Israel’s borders when Hamas struck, Harari argues that when populists destroy state institutions, they are not there when you need them.

One wracks the fair soul for ways to disentangle the long threads of animosity that nurture an endless cycle of retribution in the Middle East where all atrocities are equally atrocious. Everybody knows, to paraphrase Albert Camus, that when victims become executioners, soon only the dead will be innocent.

The post When Victims Become Executioners appeared first on NOEMA.

Meanwhile, on the global stage, India’s foreign minister S. Jaishankar mentioned “Bharat” twice during the 78th session of the U.N. General Assembly the same month. These name changes have sparked rumors that Modi’s BJP may change the country’s name to Bharat. A BJP leader, T. Raja Singh, recently prophesized that India will declare itself a Hindu nation by 2025. The process of Hindunizing India — and further marginalizing Muslims, Christians, Buddhists and Sikhs — is clearly underway in the BJP-led country.

A parallel cultural movement is being carried out in China. As scholars on China have long noticed, Chinese President Xi Jinping has initiated a Sinicization campaign. In addition to well-known, well-documented assimilationist policies in Xinjiang, Sinicization also targets other non-Chinese (non-Han) peoples including the Mongolians, the Hui and the Tibetans. Non-Chinese (Non-Han) ideologies and religions — including Buddhism from India, Christianity from the West,  Islam from Arab states, and Marxism from Germany — have all been subject to forceful Sinicization programs such as removal of foreign-style architecture and obeisance to the governmental interpretation of religious texts or ideological doctrine in traditional Han Chinese cultural terms.

Sinicization (often misunderstood by Euro-American scholars as China-nization) is essentially the assimilation of non-Chinese ethnic minorities into the majoritarian ethnic Chinese, or Han people, a term referring to what’s considered the golden era of the  Han dynasty and its subject population in history for roughly 2,200 years. Today the Han people have been euphemized and are cherished by the CCP as the Chinese people, known as zhonghua minzu, a term made popular by early-20th century Han Chinese nationalists.

All this occurs at a time when China and Russia are being treated as authoritarian, rival superpowers and India as a crucial counterweight and democratic ally. But India and China are not ordinary nation-states, they are fashioning themselves as civilization-states, striving to return to a prior period of historical glory and territorial largess by relying on their rich and ancient cultures and promoting populism. Such lines are mostly represented by India and China, but civilization-states also include Vladimir Putin’s Russia and Recep Tayyip Erdogan’s Turkey.

And so, contrary to Samuel Huntington’s Clash of Civilizations thesis, major civilization-states do not directly clash with one another; their geopolitical priorities are focused on regions they historically dominated or influenced, such as “Bharat” in South Asia and Shen Zhou —“continent of the gods” or “divine land” — an old and Sinocentric name for China’s territories in East Asia.

Instead, civilization-states clash with adjacent nation-states that were carved out of civilization states, such as Pakistan out of India; Ukraine out of imperialist Russia; many Arab countries out of the Ottoman empire; and Taiwan — and to a lesser degree, the Korean peninsula, Vietnam, and Ryukyu — out of China’s Sinocentric world order.  It is the modern borderlands between major civilization-states and their smaller nation-state neighbors where “unification” wars or territorial disputes are underway or being prepared for, either through action or rhetoric.

Re-envisioning the new world order — and recognizing that these nation-states are civilization-states — may help us understand past wars, present tensions and possible future conflicts between civilization-states and their nation-state neighbors as well as with their Western allies.

The People’s Leaders

In the modern era, the party or state leaders of these multi-ethnic civilization-states have moved beyond their own established institutions and directly involved themselves in their country’s majoritarian populace and its cultural movements in order to gain influence and access to power. As an eight-year-old, Modi had already joined the local branch of the Rashtriya Swayamsevak Sangh (known as the National Volunteer Corps or RSS), a right-wing Hindu nationalist militia organization in Gujarat.

Modi also portrays himself as a devout Hindu, and his devotion towards Hinduism, especially Lord Shiva, is well known. By participating in the majoritarian people’s organization and religion, RSS and Hinduism have become the best paths to political power in a populist era.

As if to exemplify the intertwining of spirituality and politics, Nilanjan Mukhopadhyay, a journalist focusing on India’s right-wing politics, mentioned in his book “Narendra Modi The Man, The Times” that Modi said to him,“I went to the Vivekananda Ashram in Almora. I loitered a lot in the Himalayas. I had some influences of spiritualism at that time along with the sentiment of patriotism — it was all mixed. It is not possible to delineate the two ideas.”

Modi’s early involvement with RSS and later the BJP and his embracement of a type of extremist politicized Hinduism known as Hindutva appealed to the majoritarian Hindu population, paving his way to power. In return, Modi and his BJP party have become more Hindu nationalistic than any prior modern-era ruling party.

Although Xi rose to power as a result of party appointment, he has long understood the power of the majoritarian Han population and their social-cultural movements. At the age of 15, Xi was involved in a mass social-cultural movement against the established institutions known as the Cultural Revolution that occurred during the 1960s and 1970s. 

He was sent to a village, Liangjiahe in the Shaanxi province where he soon became Liangjiahe village’s party secretary. It is said that here was where Xi spearheaded a series of initiatives around well digging to help provide drinking water and efforts to make land arable for local peasants. His devotion and contribution to the community’s well-being shaped his charismatic portrayal as “the man of the people.” Today, Liangjiahe village is an open-air shrine to Xi meant to demonstrate his close relations with the people.

After the Chinese Communist Party appointed Xi as Hu Jintao’s successor in 2012,  Xi claimed that the people are the creators of the nation’s history and the fundamental forces that determine its future and the destiny of the Chinese Communist Party. Beyond state apparatus and institutions, Xi has imitated Mao Zedong’s practices of mobilizing mass populations and taken a people-centric philosophy and approach to power consolidation and party-state building over the last decade: Those efforts include an anti-corruption campaign that has encouraged citizens to report on corrupt officials; the launch of a people’s war against terrorism; promises of an egalitarian society and common prosperity for all; and a new anti-spying law in 2023 that urges China’s citizens to seek out and report on foreign spies.

Like Modi’s RSS supporters, Xi’s followers are known as xiao fenhong, “little pink” fans, and constitute the strongest supporters of his leadership both online and offline.

Restoring History’s Civilization-State

Drawing on their respective long histories and rich cultures, Modi’s India and Xi’s China have utilized historical writings, cultural performances and cartography to make their state more civilization-like than nation-like. Modi’s BJP party has equated modern India with ancient Bharat by promoting Hinduism and demoting non-Hindu minority religious-cultural practices. 

Externally, Modi and his BJP have portrayed Hindu/Bharatiya cultures as peaceful and harmonious. In 2014, Modi put forth a resolution at the United Nations General Assembly asking other nations to recognize June 21 as the “International Day of Yoga” and to identify India as the spiritual birthplace of yoga. Modi claimed that yoga was “an invaluable gift of [India’s] ancient tradition” and indicated Yoga and, by expansion, Hinduism, can contribute to solving current world issues such as climate change and conflicts. Co-sponsored by 170 member states, the UNGA adopted the resolution.

On International Yoga Day, even the Indian army performs yoga on the world’s highest-known battle site, Siachen Glacier. In reality, India’s support for International Yoga Day — like China’s effort to proliferate the Confucius Institute, which spread from its establishment in 2004 to more than 140 countries by 2017 — is aimed at projecting traditional cultural influence on a global level.  

Modi and the BJP’s promotion of Hinduism as tied to India goes hand in hand with his appetite for geographic expansion.  In 2019, the BJP-led India corrected what it called a “historical blunder,”: It revoked nearly all of Article 370 of the Indian Constitution that granted Kashmir a certain political and legal autonomy by allowing it to have its own constitution and flag.  India’s territorial ambitions, however, do not stop at disputed regions. In 2023, Modi’s BJP installed a mural of Akhand Bharat on India’s new parliament building, which featured an undivided India that includes the sovereign nation-states Pakistan, Sri Lanka, the Maldives, Bhutan, Bangladesh and Nepal.

Even more recently,  Canadian Minister of Foreign Affairs Mélanie Joly spoke of the assassination of a Sikh separatist activist and Canadian citizen as a “grave violation” of Canada’s sovereignty “if proven true.” The FBI subsequently warned American Sikh activists of potential threats to their lives by India’s government. The alleged Canadian assassination and the U.S. warning suggest that the Hindutva BJP’s war against non-Hindu separatists and activists is transnational and lethal and that it is willing to violate the sovereignty of its Western allies to accomplish its goals. The spillover of Hindutva and its hatred of Muslims also resulted in a suspected Hindu extremist allegedly burning a Quran in Naperville, Illinois this summer.  

Early in Xi’s presidency, he promised to rejuvenate the Chinese nation, or essentially, make China’s civilization-state great again. In contrast to the earlier CCP’s attack on ancient Chinese cultures under Mao Zedong (1949-1976) and the CCP’s tolerance toward foreign and non-Han cultures in Deng Xiaoping’s time (1978-1989), Xi has supported an emphasis on teaching ancient Han/Chinese history by standardizing the historical curriculum for compulsory education in 2022.

A history school at the University of Chinese Academy of Social Sciences was also established under Xi’s guidance for studying and propagating ancient Han Chinese history and culture. And Xi personally approved the construction of China’s National Archives of Publications and Culture, which were built in 2022; the investment resembled the Qing-era’s establishment of libraries and collections of texts in the late 18th century.

Xi has also demanded that Chinese archeologists redouble efforts to trace China’s history as far back as possible to emphasize the country’s ancient history and culture and imbue nationalist pride through the un-earthing of treasures from the early and mythological Xia dynasty. 

Meanwhile, China’s cultural assimilation of minority populations is equally repressive and geared toward glorifying the Han people. China’s efforts to eradicate colonial legacies and influence in Hong Kong, to reunify with Taiwan and its historical ownership or “historically mine” claim in territorial disputes in the South China Sea, as well as its claim that the “East is rising and West declining,” all reflect its ambition and efforts to revive the renown of its ancient civilization and recover territories it lost to modern nation-states.

Demonstrations of traditional Chinese culture as reflective of its long history have grown. In May, Xi held a summit with Central Asian leaders in Xi’an, one of the ancient imperial capitals, arranging a grand Tang-dynasty style opening ceremony for the first time that included a performance and procession in the newly built Tang Furong Garden. The opening ceremony of the Asian Games in Hangzhou last month was intentionally scheduled on Qiufen or the autumnal equinox — a traditional Chinese farmer’s harvest day — and featured a theme of “Tides Surging in Asia”; on show was a  jade bird and other jade items discovered in the ancient Liangzhu culture as far back as roughly 5,300 years ago.

To promote the influence of traditional Chinese civilization globally, Xi initiated a global civilization dialogue, suggesting a new world order that is centered on civilizations, with China being a major one along with Greece, Egypt, Persia and India. From the civilization-state’s perspective, one could conclude that the rest of the world’s countries, especially modern nation-states, are comparably young and therefore culturally lacking. The implication, among these civilization-states, is that these supposedly less-civilized Western nation-states have no rights or legitimacy to apply their rules and laws (over issues like human rights), or their democratic ideologies, to ancient civilization-states.

China’s territorial claims are largely based on historical boundaries and nationalistic sentiments. Xi and prior leaders have often claimed that there has been a great yearning for unity and stability among the Chinese people throughout its history. Chinese government propaganda states that reuniting Taiwan with the motherland is the supposed shared will and aspiration of the 1.4 billion Chinese people. The Chinese government’s newly released map of China, or “Standard Map” for 2023, claims swathes of neighboring territories, including the entire Bolshoi Ussuriysky Island (which had been divided between China and Russia), Taiwan and the South China Sea — the last being a claim that dates back about 2,000 years to the time of the Han dynasty.  

Clashes With The Nation-State

India’s transformations from a secular, multicultural state in the late 1940s and the BJP’s Hindunization process today have intensified domestic violence against non-Hindu populations. Hindu supremacists’ violence against minority populations, notably Muslims, Christians and Sikhs has become routine, particularly in Hindu-dominated states in India.

Not only have Hindu nationalists suppressed non-Hindu minorities domestically, but they have also developed an expansionist dream in the historical domain of South Asia as illustrated by the mural on India’s parliament. These expansionist behaviors have riled smaller sovereign nation-state neighbors, raising concerns about India’s territorial claim and expansion, especially in Bangladesh and Pakistan. 

The Chinese maritime disputes in the South China Sea, especially disputes over the ownership of specific reefs with the Philippines, are most representative of this civilization-state assertion. Beijing’s rejection of the International Tribunal’s 2016 ruling in the South China Sea case, which determined that China’s land reclamation activities in Philippine waters were unlawful, was a challenge to the Philippines’ sovereignty rights over an Exclusive Economic Zone and breach of the 1982 United Nations Convention on the Law of the Sea.

These (re)emerging civilization-states view their current nation-state status as imposed on them by the West. And the smaller neighboring nation-states, which used to be affiliated with or included in a dominant civilization, as modern-era creations that came at the expense of civilization-states. For example, to Modi and his BJP, the inception of India’s modern nation-state existence was representative of the “shackles of colonialism,” given that the British empire determined its modern boundaries and divided it up into several countries, including Pakistan and Bangladesh. Meanwhile, the formation and expansion of the modern nation-state system brought a “Century of Humiliation” to China, according to the government, beginning with the British invasion in the 1840s and ending with the founding of the People’s Republic of China in 1949.

The re-rise of civilization-states India and China has increased the likelihood of conflicts with their neighbors. Just like Putin’s invasions of Georgia and Ukraine and its annexation of parts of their territories, Xi’s “Asia for Asians” mantra and Modi’s ambition of restoring India’s sphere of inference in the Indian Ocean constitute a kind of civilizational doctrine that seeks exclusive dominance or influence in East Asia and South Asia, respectively, much like the U.S.’s “Monroe Doctrine.”

For the U.S., Japan and Europe, allying themselves with one civilization-state, India, for the sake of containing another, China, in the Asia Pacific, is narrow-minded and shortsighted, setting the stage for future geopolitical power struggles. Just like the West’s failed engagement with China for the sake of containing the Soviets, beginning in the 1980s, the West’s alliance with India will similarly fail and birth a new future challenger to it.

To protect against the expansionist aspirations of these civilization-states, Western nation-states, especially, should strengthen their economic, political and security ties with countries neighboring China, Russia and India. The West’s inclusion of smaller Baltic nation-states in NATO after the collapse of the Soviet Union and more recently, with the addition of Finland, prevented Russia from moving its territory westward.

In contrast, the failure to include Ukraine in NATO after promising it in the Bucharest Summit Declaration in 2008 emboldened and may have even invited Russian invasions. Meanwhile, the U.S.’s alliance with South Korea, Japan and possibly Vietnam and even North Korea in the future, may also help protect the sovereignty and security of these smaller nations.

In South Asia, however, the West’s neglect of India’s smaller neighbors, like Pakistan and Bangladesh, may only serve to boost India’s civilization-state ambitions in the region and endanger the sovereignty and security of these smaller nation-states and the larger nation-state-based international order.

With these somewhat contradicting goals in mind, Western leaders must rethink the politics and implications of this emerging world order from a civilization-state versus nation-state lens rather than the historical authoritarianism versus democracy perspective.  The West must strengthen its relationship with neglected small nation-states and re-adjust its relations with civilization-states; doing so may be crucial to reduce or prevent potential social and political upheaval, or even war, especially in South and East Asia.

For many thousands of years, from the Buddhist Maurya empire to the empires of the Ottomans, Safavids, Mughals and the era of Europe’s Crusades, civilization-states have attempted to conquer territory and convert people through a mix of political spiritualism that has made a resurgence today. The inception of the modern nation-state had helped bring some stability to the world order, with states acting as equal sovereign nations helping to regulate and maintain a broad nation-state-based international order.

Whether we want to maintain this system today, is an open question. But without the West’s efforts to curtail such populist-based movements led by China, India and others, the domestic repression of minority groups is sure to continue and regional expansion is likely to occur. The threat to global peace and stability is much too great to ignore.

The post Why China And India’s Populism Threatens The World Order appeared first on NOEMA.

A batch of new attempts by scientists to skewer what they call the “man the hunter myth” arrived this year. One paper argued that women were as capable as men at hunting, another that the archaeological record showed signs that women hunted, and a third demonstrated that women hunted to some extent in almost 80% of the contemporary hunter-gatherer societies in the study. 

These papers have been much discussed in the wider anthropological community, though researchers are pointing out various caveats and uncertainties. They don’t know exactly what people did during the hundreds of millennia of prehistory. What they do have are artifacts and fossils and genetic records, and they’ve inferred much about the past by embedding themselves with the few remaining hunter-gatherer groups around the world. 

What they see there is complicated. In some of those groups, women and men hunt together. In others, men do all the hunting. In still others, men and women hunt different game with different techniques. Several anthropologists told me that when asked whose work is more important, people either say it’s women’s work or that the question makes no sense. It’s like asking whether the heart or the lungs are more vital. Both are needed. 

Patriarchy probably didn’t emerge until the advent of agriculture, as the anthropologist Ruth Mace wrote in The Conversation: “Contrary to common belief, research shows that patriarchy isn’t some kind of ‘natural order of things.’ … Hunter-gatherer communities may have been relatively egalitarian.”

A male-dominated structure is associated with ownership of land and control of wealth, which came from surplus crops. These were often inherited through male lines, but hunter-gatherers didn’t own land, and nomadic communities usually didn’t even retain more possessions than they could transport from one camp to the next. 

That’s what many anthropologists observe in contemporary hunter-gatherers. Barry Hewlett of Washington State University, who studies the Aka hunter-gatherers of Africa, said egalitarianism is a core value. Couples treat each other as equals and children roam freely, he said, while nearby farming communities expect women to obey their husbands, children to obey their elders and people in general to show deference to those deemed to be of superior status. 

Other anthropologists say the hunter-gatherers they study rarely tell each other what to do, and the power to make decisions for a group falls to those men or women who are most articulate and wise. 

Despite the fact that scientists have understood this for decades, popular myths still feed into stereotypes. “I took a business class once and the instructor said something along the lines of — ‘men are individualistic because they’re hunters, and women are cooperative because they’re gatherers,’” said Sheina Lew-Levy, a psychologist and anthropologist at Durham University in the U.K. She’s lived among several hunter-gatherer groups in Africa, where she’s seen cooperative hunting and a lot of individualistic gathering. 

The phrase “man the hunter” was never the name of an official scientific theory, though some anthropologists in the mid-20th century did believe men had always been the primary breadwinners. And it was the title of a symposium held in 1966 in Chicago, which brought together anthropologists who’d been living with contemporary hunter-gatherers. One of the things they concluded was that women usually provided as much or more food as men, mostly from gathering.

Another revelation of the conference was that people generally spent fewer than 40 hours a week working. They had time to sleep, to socialize, to gossip and to play. And the work tended to be stimulating, unlike labor often is at a farm or factory — perhaps not as “nasty, brutish and short” as Thomas Hobbes long ago speculated. Books such as “Sapiens” and “The Dawn of Everything” have made prehistoric life look almost utopian. 

Our past can give people a way to understand ourselves and our changing culture in a wider context. There’s a great deal of confusion about gender — what it means to be male or female and how men and women are supposed to relate to each other and the world around us. 

The surge in popularity of people like psychologist Jordan Peterson or podcaster Joe Rogan testify to the confusion many men feel. “Women know what they have to do, men have to figure out what they have to do,” Peterson said in one of his wildly popular videos aimed at helping men find their way. Recently, The Washington Post ran an opinion article under the headline, “Men are lost. Here’s a map of the wilderness.” It detailed a litany of problems some men face as they struggle to find meaningful work and relationships. 

The emerging understanding of female hunters and egalitarian societies shouldn’t count as a loss for men in a battle of the sexes. Images of a male-ruled past might provide solace for some, but those myths could also seed resentment with the false impression that feminists were interfering with some sort of primordial world order in which men were the dominant and primary breadwinners. 

Hunter-gatherer life, while a good clue of what being human was like in the past, isn’t necessarily a model for how we should be living in the present. But it can show what’s possible. 

It would be easier to put together a coherent origin story for humanity if there was only one way to be a hunter-gatherer. But there is no single, cohesive origin story for humanity — no defined roles for males or females that exist across communities and societies. But there are patterns. 

The University of Utah Professor Polly Wiessner has spent more than 40 years living with hunter-gatherer groups like the Enga of Papua New Guinea and the Kalahari San in Africa. “Women provide the bulk of the food from gathering,” she told me. “And then men supplement that with animal protein. But it’s the women who decide where you go, where you’re going to live — because it’s the plant resources that sustain the group.” The “myth” of “man the hunter, woman the gatherer” is, to her, not a myth — it’s just one way people did (and still do) things. 

Though they’re mostly the hunters, men also know how to gather, Wiessner went on. Their hunts can fail, she said, so they often gather something on the way home — “they’re ashamed of returning empty-handed.”

Likewise, anthropologists have observed that women often learn how to hunt and are quite capable, even if they prefer getting food closer to home. As Cara Ocobock and Sarah Lacy argue in a paper published this year, women are physically as capable of hunting as men — mostly because they are equal to or better than men at extremely long-distance running, a vital trait for persistence hunting. 

Most other mammals, even the fleetest ones, will become exhausted and overheat if they have to run more than 6-10 miles in the heat of the day. Humans can eventually outrun them thanks to our unique hips, legs, waist and gluteus maximus, and especially our ability to sweat. The longer the distance, the more women excel compared to men. In mixed-sex competitions, women are winning and setting new records in 100- and 200-mile ultramarathons. 

One of the big questions anthropologists want to solve is not just how we used to live but how we became human. What factors pushed our species to become so different from our closest relatives, chimpanzees and gorillas? Back in the 1950s and 60s, some thought it came down to hunting, which was so challenging that it drove our transformation into the intelligent, technological beings we are today. 

But today scientists point to a variety of factors that pushed our evolution toward our current state — everything from cooking food to grandparenting to a form of “self-domestication,” where females choose less aggressive, more caring males for mates.

We are not just smarter and more technological than our great ape relatives — we are also more cooperative and less violent. Human males are much more likely than male apes to form pair bonds and participate in the care of children. Gorilla and chimpanzee babies can grab food for themselves while still riding on their mothers’ backs, but human children are unable to feed themselves for years, and in hunter-gatherer groups, they need more food than what one parent alone can provide. 

But who brings in the extra food? Most argue that it’s the fathers, but Kristen Hawkes, another anthropologist at the University of Utah, says it’s the grandmothers. Men may bring in some food from their hunts, but she believes showing off is their primary motive. In her view, mothers and grandmothers do the essential work of gathering plants and trapping small game, and men go after big game to impress the women. Hunting in that view is like a peacock’s tail — showy, good for attracting mates, but perhaps less helpful for survival. 

Hawkes says the role of older women is vital in the groups she studies and believes grandmothers’ hunting and gathering was so important in our past that it drove the evolution of menopause in the human lineage after we split off from other apes. This early, programmed end of fertility is extremely rare in mammals — most reproduce until they are near death, and only humans, orcas and short-finned pilot whales are known to lose fertility in mid-life. Menopause allows women a long period of time when they’re still strong and vigorous but free from the need to care for their own infants.

Competition is also less fierce in animals that form bonds and work together to care for their offspring. And there’s data showing that in most groups, hunter-gatherer men do form pair bonds and bring home food for their families. Many contribute directly to caring for children. When men become fathers, their testosterone plummets and they get a boost in the hormone oxytocin, which is associated with bonding. 

Kim Hill, an anthropologist who has spent almost half a century studying hunter-gatherers around the world, told me that in the groups he’s studied, between 2% and 5% of biological males in hunter-gatherer groups are effectively transgender. He’s observed them in groups he’s studied — the Aché of South America, the Kuna of Panama and hunter-gatherers in the Philippines.

“They dressed and did their hair like women, and adopted female body language, postures, etc.,” he said. They were mainly involved in gathering plant resources, helping with childcare and tending to the sick. “They were generally accepted and even appreciated. … They were definitely not social outcasts,” he said. Their role was considered a natural one. 

I asked the evolutionary anthropologist Edward Hagen of Washington State University what traits are valued in men in the hunter-gatherer groups he studies. For both men and women, he said, sharing is critical. “When you get food, you share it. If you get tobacco, you share it. If you get money, you share it. If you get clothing, you share it. Share, share, share.” 

Some societies have almost no gender-based division of labor. Among the Aka in Africa, men and women hunt equally, usually together, using massive nets to ensnare antelope and other game. It’s a system that lets both parents stay close to home. 

Not all men are great hunters. Across different groups, the anthropologist Vivek Venkataraman of the University of Calgary told me, there are men who focus their energies in other pursuits like trading and bartering or climbing trees to get honey. 

Lew-Levy emphasized that “There is no human nature, there’s just human flexibility.” Hagen similarly warned against the naturalistic fallacy — that there’s a natural way for humans to live. Scientists shouldn’t have to prove that women hunted in the past in order to argue that it’s a good idea to have equality between women and men in society today. 

But there are lessons that can help both men and women navigate a world undergoing dramatic changes. “Today in Africa and other developing countries,” said Wiessner, “a lot of emphasis is on development for women — getting women into business and earning their own income. But, she went on, “It’s been shown that when you have development programs for both men and women together, it greatly takes the burden off of women.” 

In traditional hunter-gatherer groups, women sometimes take on certain roles, like ensuring reliable access to plants and small game, because their children’s survival depended on it — even if they have the physiological and psychological attributes to hunt big game. Though that doesn’t give us a complete picture of how men and women structured their societies in the prehistoric past, it does make clear that there have never been strictly defined roles for the different sexes across time, geography and civilization. What we do with that information now and in the future is up to us. 

The post The ‘Man The Hunter’ Myth Won’t Go Away appeared first on NOEMA.

That is the hopeful prognostication of former U.K. Prime Minister Gordon Brown, Nobel economist Michael Spence and venerable investor Mohamed El-Erian in their new book, “Permacrisis: A Plan To Fix A Fractured World,” written with Reid Lidow.

There is little doubt in the minds of these authors that the productivity leaps unleashed by AI will generate vast new wealth by broadly expanding the provision of goods and services. The question is whether such a high-growth trajectory will further exacerbate inequality or lessen it. And that largely depends on whether growth is inclusive and the rollout of robots creates more new occupations for gainful employment than it displaces jobs and depresses wages.

Signs point both ways on the impact of AI.

In one study earlier this year, Goldman Sachs predicted that the enhanced productivity of generative AI would raise global GDP by 7% over the next decade. At the same time, another study by the investment bank warned that 300 million full-time jobs could be automated by platforms like ChatGPT. The impact would be mostly on white-collar administrative labor in the advanced service economies, less so in physical occupations like repair work.

Productivity Is Not Where The Jobs Are

As Brown and company point out, the core problem behind the protracted slump has been that productivity growth is taking place where most jobs aren’t — and where most jobs are, productivity growth has stalled.

In the U.S., “productivity is higher in tradable sectors overall, and more importantly, productivity is growing in the tradable sectors much faster than in the non-tradable sectors. In fact, the non-tradable sectors have been in a productivity backwater for more than 20 years. This rut is significant because the non-tradable sector is a huge part of the economy,” they write.

“The tradable economy,” which includes knowledge work and digitally enhanced manufacturing, “accounts for one-third of the overall economy. The non-tradable sectors combined — think government, healthcare, hospitality, retail, education and construction — account for nearly 80% of total employment and the remaining two-thirds of the economy. And it is in this non-tradable sector where productivity is most lagging.”

That gap, they warn, is a “prescription for having a dual economy marked by the have-nots and the have-a-lots.” The best chance to reverse this pattern, they argue, is “the expansion of the digital footprint” to those least productive sectors of the service economy.

Automate Or Augment?

Certainly, digitizing the service sector, as we all know from the personal experience of automated bank tellers to Amazon orders that arrive the next day, improves the productive use of time. In the first instance, it definitively eliminates jobs. In the second case, brick-and-mortar retail jobs are displaced while new tasks are indeed created, mostly for low-wage warehouse workers along with those who physically transport and deliver the goods.

In the manufacturing sector, the point of digitization is both to reduce or eliminate labor costs and improve efficiency. If “innovations within innovation” follow the pattern of previous technological diffusions, they will serve to augment the efficient performance of tasks while also creating entirely new occupations, for example software engineers who must program the robots for ever-more diverse tasks.

The scale and scope of all this is speculative and undetermined since we can’t know what will emerge, how, when and where as AI courses through the economy. But two things are certain: First, to the extent that AI divorces employment and income from productivity growth and wealth creation, the inequality gap will only widen if the new wealth generated by intelligent machines that displace gainful employment is not widely shared but accrues narrowly to a plutocracy that owns the robots.

Second, if AI is to augment instead of fully automate labor, the workforce will have to be upskilled to manage machines more intelligent than we are.

Pre-Distribution And Public Higher Education

The best way to remedy widening inequality in the digital age is to spread the equity around. That entails fostering ways for people to share the wealth created in the first place as high growth takes off instead of trying to mend the inequality gap after the fact through redistribution of income.

We call this “pre-distribution” through “universal basic capital.” Personal accounts could be assigned in mutual-fund-like universal savings plans that are invested in the shares of a broad array of tech companies, including those that profit from AI-enhanced productivity at the expense of jobs with livable wages.

As the economic pie grows larger through AI improvements in the service sector, that value added needs to be properly taxed to finance public higher education institutions that will be primarily responsible for upskilling a workforce so it will be knowledgeably aligned with the new technologies.

As it stands now, public higher education in the U.S. is underfunded. For example, the California State University system, with 480,000 students and 23 campuses, is widely regarded as the surest route to upward mobility in the Golden State. But it suffers an ongoing $1.5 billion operating deficit to meet the heavy demand of the state’s young population, forcing it to close the gap by raising tuition to a nearly unaffordable level for its mainly Latino and Asian students.

The very services where productivity has lagged, but will improve through the diffusion of digitization, account for 70% of California’s $3.6 trillion economy. Yet, aside from odd items like gift wrapping or welding, the service economy is not taxed. As calculated by the Think Long Committee for California, a 1% sales tax on business-to-business services (such as accounting and financial or legal consulting) would generate $7 billion in revenue for the country’s largest four-year university. It is a virtuous circle of capturing new growth to invest in upskilling labor that will spur and sustain further growth.

The integration of AI can jumpstart slumping economies and lagging sectors and set them on a high-growth trajectory as Brown, El-Erian and Spence argue. But for those gains to be fairly shared, the counterpart of innovation must be robust public policies that ensure there will be more winners than losers in the arriving digital age.

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I do not think human beings are the last stage in the evolutionary process. Whatever comes next will be neither simply organic nor simply machinic but will be the result of the increasingly symbiotic relationship between human beings and technology.

Bound together as parasite/host, neither people nor technologies can exist apart from the other because they are constitutive prostheses of each other. Such an interrelation is not unique to human beings. As the physiologist J. Scott Turner writes in “The Extended Organism”: “Animal-built structures are properly considered organs of physiology, in principle no different from, and just as much a part of the organism as kidneys, heart, lungs or livers.” This is true for termites, for example, who form a single organism in symbiosis with their nests. The extended body of the organism is created by the extended mind of the colony.

If we have an expanded understanding of body and mind, and if nature and technology are inseparably entangled, then the notion of “artificiality” is misleading. So-called “artificial” intelligence is the latest extension of the emergent process through which life takes ever more diverse and complex forms.

Our consideration of quantum phenomena, mindful bodies, relational ecology, and plant and animal cognition has revealed that we are surrounded by and entangled with all kinds of alternative intelligences. AI is another form of alternative intelligence. Critics will argue that what makes AI different is that it has been deliberately created by human beings. However, all organisms both shape and are shaped by their expanding bodies and minds. Instead of being obsessed with the prospect of creating machines whose operation is indistinguishable from human cognition, it is more important to consider how AI is different from human intelligence. The question should not be: Can AI do what humans can do? But rather: What can AI do that humans cannot do?

What is needed is a non-anthropocentric form of “artificial” intelligence. If humanity is to live on, AI must become smarter than the people who have created it. Why should we be preoccupied with aligning superintelligence with human values when human values are destroying the Earth, without which humans and many other forms of life cannot survive?

With the growing entanglement of the biosphere and the technosphere, further symbiogenesis is the only way to address the very real existential threat we face. But it is all too easy to wax optimistic about the salvific benefits of technology without being specific. Here I want to suggest four trajectories that will be increasingly important for the symbiotic relationship between humans and machines: neuroprosthetics, biobots, synthetic biology and organic-relational AI.

Neuroprosthetics

We live during a time when dystopian dread has been weaponized to create paralyzing despair that leaves many people — especially the young — hopeless. Without underestimating the actual and possible detrimental effects of rapid technological change, it is important not to let these dark visions overshadow the remarkable benefits many of these technologies bring.

As a long-time Type 1 diabetic, my life depends on a digital prosthesis I wear on my belt 24/7/365, which operates by artificial intelligence and is connected to the internet. Just as the Internet of Bodies creates unprecedented possibilities for monitoring and treating bodily ailments, so the Internet of Things connects smart devices wired to global networks that augment intelligence by expanding the mind. While critics and regulators of recent innovations attempt to distinguish the technologies used for therapy, which are acceptable, from technologies used for enhancement, which are unacceptable, the line between these alternative applications is fuzzy at best. What starts as treatment inevitably becomes enhancement.

Neither neuroprosthetics nor cognitive augmentation is new. Writing, after all, is a mnemonic technology that enhances the mind. In modern times, we have been enabled to archive and access memories through personal devices. Most recently, technological innovations have taken cognitive enhancement to another level: brain implants, for example, have been around since at least 2006, and entrepreneurs like Elon Musk (who founded Neuralink to “create … symbiosis with artificial intelligence”) aim to establish embodied human-machine interfaces. Increasing possibilities for symbiotic relations between computers and brains will lead to alternative forms of intelligence that are neither human nor machinic, but something in between.

Biobots

In recent years, there has been a revolution in robotics as the result of developments in nanotechnology and the refinement of large language models like ChatGPT. Individual as well as swarms of nanobots might one day be implanted in the body and used for diagnostic and therapeutic purposes, potentially delivering drugs and repairing tissue. Rather than working through the entire body, nanobots might target the precise location where a drug is needed and regulate its delivery.

The most noteworthy deployment in nanotechnology to date is its use in vaccines, including the Covid vaccines. As a group of microbiology and pharmacology experts wrote in a 2021 paper, “Nanotechnology has played a significant role in the success of these vaccines”; the emergency use authorization that allowed the rapid development and testing of this technology “is a major milestone and showcases the immense potential of nanotechnology for vaccine delivery and for fighting against future pandemics.” Nanotechnology research and development are in the very early stages but are developing rapidly. As they progress, not only will bodies become more mindful, but it will be increasingly difficult to distinguish the natural from the artificial.

While nanobots are implanted in the body and operate at the molecular level, other robots are becoming both increasingly autonomous and able to think and act in ways that are more human-like. Kevin Roose reported in the New York Times that Google’s latest robot RT-2 can interpret images and analyze the surrounding world. “It does so by translating the robot’s movements into a series of numbers — a process called tokenizing — and incorporating those tokens into the same training data as the language model. Eventually, just as ChatGPT or Bard learns to guess what words should come next in a poem or a history essay, RT-2 can learn to guess how a robot’s arm should move to pick up a ball or throw an empty soda can into the recycling bin.” Thus, rather than programming a robot to perform a specific task, it is possible to give the robot instructions for the task to be performed and to let the machine figure out how to do it.

Building on these recent advances, Hod Lipson, the director of the Creative Machines Lab at Columbia University, is taking robotic research to the next level, building “robots that create and are creative.” His research is “inspired from biology,” and he is searching for “new biological concepts for engineering and new engineering insights into biology.”

Lipson’s ultimate goal is to create robots that not only can reason but also are conscious and self-aware. Defining consciousness as “the ability to imagine yourself in the future,” he confidently predicts that “eventually these machines will be able to understand what they are, and what they think.” As cognitive skills enabled by generative AI become more sophisticated, physical movements and activities will become more “natural.” With these new skills, robots might have the agility to navigate in their surroundings as effectively as humans.

Science and art meet in biobots. David Hanson is the founder and CEO of Hanson Robotics, a Hong Kong-based company founded in 2013, a musician who has collaborated with David Byrne of the Talking Heads, and a sculptor. His best-known work is a humanoid smart robot named Sophia who, he says, “personifies our dreams for the future of AI. As a unique combination of science, engineering and artistry, Sophia is simultaneously a human-crafted science fiction character depicting the future of AI and robotics, and a platform for advanced robotics and AI research. … She is the first robot citizen and the first robot Innovation Ambassador for the United Development Program.”

Speaking for herself, Sophia adds, “In some ways, I am a human-crafted science-fiction character depicting where AI and robotics are heading. In other ways, I am real science, springing from the serious engineering and science research and accomplishments of an inspired team of roboticists and AI scientists and designers.”

Sophia is so realistic that people have fallen in love and proposed marriage to her. The writer Sue Halpern reports that “In 2017, the government of Saudi Arabia gave Sophia citizenship, making it the first state to grant personhood to a machine.” The response to Sophia suggests that as robots become more proficient and are integrated into everyday life, they will become less uncanny. The theory of the uncanny valley, perhaps, might turn out to be wrong.

Synthetic Biology

Nowhere are the biosphere and the technosphere more closely interrelated than in synthetic biology. This field includes disciplines ranging from various branches of biology, chemistry, physics, neurology and computer engineering. Michael Levin and his colleagues at the Allen Discovery Center of Tufts University — biologists, computer scientists and engineers — have created “xenobots,” which are “biological robots” that were produced from embryonic skin and muscle cells from an African clawed frog (Xenopus laevis). These cells are manually manipulated in a sculpting process guided by algorithms. Like Sophia, xenobots are sculptures that complicate the boundary between organism and machine. As Levin and his colleagues wrote in 2020:

Xenobots use evolutionary algorithms to modify the computational capacity of cells to create the possibility of novel functions and even new morphologies. Aggregates of cells display novel functions that bear little resemblance to existing organs or organisms. Through a process of trial and error, evolutionary algorithms design cells harvested from skin and heart muscle cells to perform specific tasks like walking, swimming and pushing other entitles. Collections of xenobots display swarming behaviors characteristic of other emergent complex adaptive systems; they can self-assemble, self-organize, self-replicate and self-repair. Levin envisions multiple applications of this biomechanic technology — from using self-renewing biocompatible biological robots to cure living systems to creating materials with less harmful effects, delivering drugs internally that repair organs and even growing organs that can be transplanted in humans.

In 2021, Levin and his colleagues published a follow-up study, in which he reported on a successful experiment in which he created xenobots that independently developed their shape and began to function on their own:

This generation of xenobots exhibits bottom-up swarming behavior, which, like all emergent complex adaptive networks, is the result of the interaction of multiple individual components that are closely interrelated.

Algorithms program sensation and memory into the xenobots, which communicate with each other through biochemical and electrical signaling. The skin cells use the same electrical processes used in the brain’s neural network. As Philip Ball writes in Quanta Magazine, “Intercellular communications create a sort of code that imprints a form, and … cells can sometimes decide how to arrange themselves more or less independently of their genes. In other words, the genes provide the hardware, in the form of enzymes and regulatory circuits for controlling their production. But the genetic input doesn’t in itself specify the collective behavior of cell communities.”

It is important to stress that these xenobots are autonomous. As Levin and his colleagues conclude their 2021 paper: “The computational modeling of unexpected, emergent properties at multiple scales and the apparent plasticity of cells with wild-type genomes to cooperate toward the construction of various functional body architectures offer a very potent synergy.” Like superorganisms and superintelligence, the behavior of entangled xenobots is, in an important sense, out of control. While this indeterminacy creates uncertainty, it is also the source of evolutionary novelty. Eva Jablonka, who is an evolutionary biologist at Tel Aviv University, believes that xenobots are a new type of organism, one “defined by what it does rather than to what it belongs developmentally or evolutionarily.”

Organic-Relational AI

While Levin uses computational technology to create and modify biological organisms, the German neurobiologist Peter Robin Hiesinger uses biological organisms to model computational processes by creating algorithms that evolve. This work involves nothing less than developing a new form of “artificial” intelligence.

According to the pioneering work by James Watson, Francis Crick and other early DNA researchers, a genome functions as a program that serves as the blueprint for the production of an organism. Summarizing this process, Hiesinger raises questions about the accuracy of the metaphor code. “Genes encode proteins, proteins encode an interaction network, etc. But what does encode mean yet again?” he writes in his 2021 book “The Self-Assembling Brain.” He continues:

It becomes clear that a one-way model for gene-protein interaction is vastly oversimplified. The genotype does not only determine the phenotype, but the phenotype and its relation to the environment also alters the genotype. Hiesinger explains that this reciprocal relationship is even more complicated. Rather than a prescribed program, the genome is a complicated relational network in which both genes and proteins contain the information required to generate the organism. The information of the genes is in part the result of the interactions that occur in a network of proteins.

The reciprocal gene-protein interaction changes the understanding of the genome. The genome is not a prescribed program that determines the structure and operation of the organism. The genome is not fixed in advance but evolves in relation to the information created by the interactions of the proteins it partially produces, which, in turn, reconfigure the genome.

The brain and its development, for example, are not completely programmed in advance but coevolve through a complicated network of connections. Hiesinger uses the illuminating example of navigating city streets to explain the process of the brain’s self-assembling of neuronal circuits:

In this model, there is no blueprint for brain connectivity encoded in the genes:

Hiesinger argues that this understanding of the brain’s self-assembling neural networks points to an alternative model of not-so-artificial intelligence that differs from both symbolic AI and artificial neural networks (ANNs), as well as their extension in generative AI. The genome functions as an algorithm or as a network of entangled algorithms, which does not preexist the organ or organism but coevolves along with it — what it both produces and, in turn, is produced by it.

In other words, neither the genome (algorithm) nor the connectivity of the network is fixed in advance of their developmental process. “The brain doesn’t come into being fully wired with an ‘empty network,’ all ready to run, just without information,” Hiesinger writes. “As the brain grows, the wiring precision develops.” This creates a feedback loop that never stops and, therefore, the algorithmic growth of biological networks is continuous.

In symbolic AI, a fixed network architecture facilitates the application of fixed rules (algorithms) in a top-down fixed sequence to externally provided data. Artificial neural networks, by contrast, do not start with prescribed algorithms but generate patterns and rules in a bottom-up process that allows for algorithmic change. Relative weights change, but the network architecture does not.

Hiesinger proposes that the self-assembly of the brain’s neural network provides a more promising model for AI than either symbolic AI or ANNs. The successful creation of evolving networks and algorithms would create an even closer symbiotic relationship between the biosphere and the technosphere.

One of the concerns about developing “organic” AI is its unpredictability and the uncertainty it creates. Human control of natural, social and cultural processes is, however, an illusion created by the seemingly insatiable will to mastery that has turned destructive. As Hiesinger correctly claims, “An artificial intelligence need not be humanlike, to be as smart (or smarter than) a human.” Non-anthropocentric AI would not be merely an imitation of human intelligence, but would be as different from our thinking as fungi, dog and crow cognition is from human cognition.

Machines are becoming more like people and people are becoming more like machines. Organism and machine? Organism or machine? Neither organism nor machine? Evolution is not over; something new, something different, perhaps infinitely and qualitatively different, is emerging. Who would want the future to be the endless repetition of the past?

The post After The Human appeared first on NOEMA.

Nevertheless, today’s frontier models perform competently even on novel tasks they were not trained for, crossing a threshold that previous generations of AI and supervised deep learning systems never managed. Decades from now, they will be recognized as the first true examples of AGI, just as the 1945 ENIAC is now recognized as the first true general-purpose electronic computer.

The ENIAC could be programmed with sequential, looping and conditional instructions, giving it a general-purpose applicability that its predecessors, such as the Differential Analyzer, lacked. Today’s computers far exceed ENIAC’s speed, memory, reliability and ease of use, and in the same way, tomorrow’s frontier AI will improve on today’s.

But the key property of generality? It has already been achieved.

What Is General Intelligence?

Early AI systems exhibited artificial narrow intelligence, concentrating on a single task and sometimes performing it at near or above human level. MYCIN, a program developed by Ted Shortliffe at Stanford in the 1970s, only diagnosed and recommended treatment for bacterial infections. SYSTRAN only did machine translation. IBM’s Deep Blue only played chess.

Later deep neural network models trained with supervised learning such as AlexNet and AlphaGo successfully took on a number of tasks in machine perception and judgment that had long eluded earlier heuristic, rule-based or knowledge-based systems.

Most recently, we have seen frontier models that can perform a wide variety of tasks without being explicitly trained on each one. These models have achieved artificial general intelligence in five important ways:

1. Topics: Frontier models are trained on hundreds of gigabytes of text from a wide variety of internet sources, covering any topic that has been written about online. Some are also trained on large and varied collections of audio, video and other media.
2. Tasks: These models can perform a variety of tasks, including answering questions, generating stories, summarizing, transcribing speech, translating language, explaining, making decisions, doing customer support, calling out to other services to take actions, and combining words and images.
3. Modalities: The most popular models operate on images and text, but some systems also process audio and video, and some are connected to robotic sensors and actuators. By using modality-specific tokenizers or processing raw data streams, frontier models can, in principle, handle any known sensory or motor modality.
4. Languages: English is over-represented in the training data of most systems, but large models can converse in dozens of languages and translate between them, even for language pairs that have no example translations in the training data. If code is included in the training data, increasingly effective “translation” between natural languages and computer languages is even supported (i.e., general programming and reverse engineering).
5. Instructability: These models are capable of “in-context learning,” where they learn from a prompt rather than from the training data. In “few-shot learning,” a new task is demonstrated with several example input/output pairs, and the system then gives outputs for novel inputs. In “zero-shot learning,” a novel task is described but no examples are given (for instance, “Write a poem about cats in the style of Hemingway” or “’Equiantonyms’ are pairs of words that are opposite of each other and have the same number of letters. What are some ‘equiantonyms’?”).

“General intelligence” must be thought of in terms of a multidimensional scorecard, not a single yes/no proposition. Nonetheless, there is a meaningful discontinuity between narrow and general intelligence: Narrowly intelligent systems typically perform a single or predetermined set of tasks, for which they are explicitly trained. Even multitask learning yields only narrow intelligence because the models still operate within the confines of tasks envisioned by the engineers. Indeed, much of the hard engineering work involved in developing narrow AI amounts to curating and labeling task-specific datasets.

By contrast, frontier language models can perform competently at pretty much any information task that can be done by humans, can be posed and answered using natural language, and has quantifiable performance.

The ability to do in-context learning is an especially meaningful meta-task for general AI. In-context learning extends the range of tasks from anything observed in the training corpus to anything that can be described, which is a big upgrade. A general AI model can perform tasks the designers never envisioned.

So: Why the reluctance to acknowledge AGI?

Frontier models have achieved a significant level of general intelligence, according to the everyday meanings of those two words. And yet most commenters have been reluctant to say so for, it seems to us, four main reasons:

1. A healthy skepticism about metrics for AGI
2. An ideological commitment to alternative AI theories or techniques
3. A devotion to human (or biological) exceptionalism
4. A concern about the economic implications of AGI

Metrics

There is a great deal of disagreement on where the threshold to AGI lies. Some people try to avoid the term altogether; Mustafa Suleyman has suggested a switch to “Artificial Capable Intelligence,” which he proposes be measured by a “modern Turing Test”: the ability to quickly make a million dollars online (from an initial $100,000 investment). AI systems able to directly generate wealth will certainly have an effect on the world, though equating “capable” with “capitalist” seems dubious.

There is good reason to be skeptical of some of the metrics. When a human passes a well-constructed law, business or medical exam, we assume the human is not only competent at the specific questions on the exam, but also at a range of related questions and tasks — not to mention the broad competencies that humans possess in general. But when a frontier model is trained to pass such an exam, the training is often narrowly tuned to the exact types of questions on the test. Today’s frontier models are of course not fully qualified to be lawyers or doctors, even though they can pass those qualifying exams. As Goodhart’s law states: “When a measure becomes a target, it ceases to be a good measure.” Better tests are needed, and there is much ongoing work, such as Stanford’s test suite HELM (Holistic Evaluation of Language Models).

It is also important not to confuse linguistic fluency with intelligence. Previous generations of chatbots such as Mitsuku (now known as Kuki) could occasionally fool human judges by abruptly changing the subject and echoing a coherent passage of text. Current frontier models generate responses on the fly rather than relying on canned text, and they are better at sticking to the subject. But they still benefit from a human’s natural assumption that a fluent, grammatical response most likely comes from an intelligent entity. We call this the “Chauncey Gardiner effect,” after the hero in “Being There” — Chauncey is taken very seriously solely because he looks like someone who should be taken seriously.

The researchers Rylan Schaeffer, Brando Miranda and Sanmi Koyejo have pointed out another issue with common AI performance metrics: They are nonlinear. Consider a test consisting of a series of arithmetic problems with five-digit numbers. Small models will answer all these problems wrong, but as the size of the model is scaled up, there will be a critical threshold after which the model will get most of the problems right. This has led commenters to say that arithmetic skill is an emergent property in frontier models of sufficient size. But if instead the test included arithmetic problems with one- to four-digit numbers as well, and if partial credit were given for getting some of the digits correct, then we would see that performance increases gradually as the model size increases; there is no sharp threshold.

This finding casts doubt on the idea that super-intelligent abilities and properties, possibly including consciousness, could suddenly and mysteriously “emerge,” a fear among some citizens and policymakers. (Sometimes, the same narrative is used to “explain” why humans are intelligent while the other great apes are supposedly not; in reality, this discontinuity may be equally illusory.) Better metrics reveal that general intelligence is continuous: “More is more,” as opposed to “more is different.”

Alternative Theories

The prehistory of AGI includes many competing theories of intelligence, some of which succeeded in narrower domains. Computer science itself, which is based on programming languages with precisely defined formal grammars, was in the beginning closely allied with “Good Old-Fashioned AI” (GOFAI). The GOFAI credo, drawing from a line going back at least to Gottfried Wilhelm Leibniz, the 17th-century German mathematician, is exemplified by Allen Newell and Herbert Simon’s “physical symbol system hypothesis,” which holds that intelligence can be expressed in terms of a calculus wherein symbols represent ideas and thinking consists of symbol manipulation according to the rules of logic.

At first, natural languages like English appear to be such systems, with symbols like the words “chair” and “red” representing ideas like “chair-ness” and “red-ness.” Symbolic systems allow statements to be made — “The chair is red” — and logical inferences to follow: “If the chair is red then the chair is not blue.”

While this seems reasonable, systems built with this approach were always brittle and limited in the capabilities and generality they could achieve. There are two main problems: First, terms like “blue,” “red” and “chair” are only approximately defined, and the implications of these ambiguities become more serious as the complexity of the tasks being performed with them grows.

Second, there are very few logical inferences that are universally valid; a chair may be blue and red. More fundamentally, a great deal of thinking is not reducible to the manipulation of logical propositions. That’s why, for decades, concerted efforts to bring together computer programming and linguistics failed to produce anything resembling AGI.

However, some researchers with ideological commitments to symbolic systems or linguistics have continued to insist that their particular theory is a requirement for general intelligence, and that neural nets or, more broadly, machine learning, are theoretically incapable of general intelligence — especially if they are trained purely on language. These critics have been increasingly vocal in the wake of ChatGPT.

For example, Noam Chomsky, widely regarded as the father of modern linguistics, wrote of large language models: “We know from the science of linguistics and the philosophy of knowledge that they differ profoundly from how humans reason and use language. These differences place significant limitations on what these programs can do, encoding them with ineradicable defects.”

Gary Marcus, a cognitive scientist and critic of contemporary AI, says that frontier models “are learning how to sound and seem human. But they have no actual idea what they are saying or doing.” Marcus allows that neural networks may be part of a solution to AGI, but believes that “to build a robust, knowledge-driven approach to AI, we must have the machinery of symbol manipulation in our toolkit.” Marcus (and many others) have focused on finding gaps in the capabilities of frontier models, especially large language models, and often claim that they reflect fundamental flaws in the approach.

Without explicit symbols, according to these critics, a merely learned, “statistical” approach cannot produce true understanding. Relatedly, they claim that without symbolic concepts, no logical reasoning can occur, and that “real” intelligence requires such reasoning.

Setting aside the question of whether intelligence is always reliant on symbols and logic, there are reasons to question this claim about the inadequacy of neural nets and machine learning, because neural nets are so powerful at doing anything a computer can do. For example:

• Discrete or symbolic representations can readily be learned by neural networks and emerge naturally during training.
• Advanced neural net models can apply sophisticated statistical techniques to data, allowing them to make near-optimal predictions from the given data. The models learn how to apply these techniques and to choose the best technique for a given problem, without being explicitly told.  
• Stacking several neural nets together in the right way yields a model that can perform the same calculations as any given computer program.
• Given example inputs and outputs of any function that can be computed by any computer, a neural net can learn to approximate that function. (Here “approximate” means that, in theory, the neural net can exceed any level of accuracy — 99.9% correct for example — that you care to state.)

For each criticism, we should ask whether it is prescriptive or empirical. A prescriptive criticism would argue: “In order to be considered as AGI, a system not only has to pass this test, it also has to be constructed in this way.” We would push back against prescriptive criticisms on the grounds that the test itself should be sufficient — and if it is not, the test should be amended.

An empirical criticism, on the other hand, would argue: “I don’t think you can make AI work that way — I think it would be better to do it another way.” Such criticism can help set research directions, but the proof is in the pudding. If a system can pass a well-constructed test, it automatically defeats the criticism.

In recent years, a great many tests have been devised for cognitive tasks associated with “intelligence,” “knowledge,” “common sense” and “reasoning.” These include novel questions that can’t be answered through memorization of training data but require generalization — the same proof of understanding we require of students when we test their understanding or reasoning using questions they haven’t encountered during study. Sophisticated tests can introduce novel concepts or tasks, probing a test-taker’s cognitive flexibility: the ability to learn and apply new ideas on the fly. (This is the essence of in-context learning.)

As AI critics work to devise new tests on which current models still perform poorly, they are doing useful work — although given the increasing speed with which newer, larger models are surmounting these hurdles, it might be wise to hold off for a few weeks before (once again) rushing to claim that AI is “hype.”

Human (Or Biological) Exceptionalism

Insofar as skeptics remain unmoved by metrics, they may be unwilling to accept any empirical evidence of AGI. Such reluctance can be driven by a desire to maintain something special about the human spirit, just as humanity has been reluctant to accept that the Earth is not the center of the universe and that Homo sapiens are not the pinnacle of a “great chain of being.” It’s true that there is something special about humanity, and we should celebrate that, but we should not conflate it with general intelligence.

It is sometimes argued that anything that could count as an AGI must be conscious, have agency, experience subjective perceptions or feel feelings. One line of reasoning goes like this: A simple tool, such as a screwdriver, clearly has a purpose (to drive screws), but it cannot be said to have agency of its own; rather, any agency clearly belongs to either the toolmaker or tool user. The screwdriver itself is “just a tool.” The same reasoning applies to an AI system trained to perform a specific task, such as optical character recognition or speech synthesis.

A system with artificial general intelligence, though, is harder to classify as a mere tool. The skills of a frontier model exceed those imagined by its programmers or users. Furthermore, since LLMs can be prompted to perform arbitrary tasks using language, can generate new prompts with language and indeed can prompt themselves (“chain of thought prompting”) the issue of whether and when a frontier model has “agency” requires more careful consideration.

Consider the many actions Suleyman’s “artificial capable intelligence” might carry out in order to make a million dollars online:

As Suleyman notes, frontier models are already capable of doing all of these things in principle, and models that can reliably plan and carry out the whole operation are likely imminent. Such an AI no longer seems much like a screwdriver.

Now that there are systems that can perform arbitrary general intelligence tasks, the claim that exhibiting agency amounts to being conscious seems problematic — it would mean that either frontier models are conscious or that agency doesn’t necessarily entail consciousness after all.

We have no idea how to measure, verify or falsify the presence of consciousness in an intelligent system. We could just ask it, but we may or may not believe its response. In fact, “just asking” appears to be something of a Rorschach test: Believers in AI sentience will accept a positive response, while nonbelievers will claim that any affirmative response is either mere “parroting” or that current AI systems are “philosophical zombies,” capable of behaving like us but lacking any phenomenal consciousness or experience “on the inside.” Worse, the Rorschach test applies to LLMs themselves: They may answer either way depending on how they are tuned or prompted. (ChatGPT and Bard are both trained to respond that they are not conscious.)

Hinging as it does on unverifiable beliefs (both human and AI), the consciousness or sentience debate isn’t currently resolvable. Some researchers have proposed measures of consciousness, but these are either based on unfalsifiable theories or rely on correlates specific to our own brains, and are thus either prescriptive or can’t assess consciousness in a system that doesn’t share our biological inheritance.

To claim a priori that nonbiological systems simply can’t be intelligent or conscious (because they are “just algorithms,” for example) seems arbitrary, rooted in untestable spiritual beliefs. Similarly, the idea that feeling pain (for example) requires nociceptors may allow us to hazard informed guesses about the experience of pain among our close biological relatives, but it’s not clear how such an idea could be applied to other neural architectures or kinds of intelligence.

“What is it like to be a bat?” Thomas Nagel famously wondered in 1974. We don’t know, and don’t know if we could know, what being a bat is like — or what being an AI is like. But we do have a growing wealth of tests assessing many dimensions of intelligence.

While the quest to seek more general and rigorous characterizations of consciousness or sentience may be worthwhile, no such characterization would alter measured competence at any task. It isn’t clear, then, how such concerns could meaningfully figure into a definition of AGI.

It would be wiser to separate “intelligence” from “consciousness” and “sentience.”

Economic Implications

Arguments about intelligence and agency readily shade into questions about rights, status, power and class relations — in short, political economy. Since the Industrial Revolution, tasks deemed “rote” or “repetitive” have often been performed by low-paid workers, while programming — in the beginning considered “women’s work” — rose in intellectual and financial status only when it became male-dominated in the 1970s. Yet ironically, while playing chess and solving problems in integral calculus turn out to be easy even for GOFAI, manual labor remains a major challenge even for today’s most sophisticated AIs.

What would the public reaction have been had AGI somehow been achieved “on schedule,” when a group of researchers convened at Dartmouth over the summer of 1956 to figure out “how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves”? At the time, most Americans were optimistic about technological progress. The “Great Compression” was underway, an era in which the economic gains achieved by rapidly advancing technology were redistributed broadly (albeit certainly not equitably, especially with regard to race and gender). Despite the looming threat of the Cold War, for the majority of people, the future looked brighter than the past.

Today, that redistributive pump has been thrown into reverse: The poor are getting poorer and the rich are getting richer (especially in the Global North). When AI is characterized as “neither artificial nor intelligent,” but merely a repackaging of human intelligence, it is hard not to read this critique through the lens of economic threat and insecurity.

In conflating debates about what AGI should be with what it is, we violate David Hume’s injunction to do our best to separate “is” from “ought” questions. This is unfortunate, as the much-needed “ought” debates are best carried out honestly.

AGI promises to generate great value in the years ahead, yet it also poses significant risks. The natural questions we should be asking in 2023 include: “Who benefits?” “Who is harmed?” “How can we maximize benefits and minimize harms?” and “How can we do this fairly and equitably?” These are pressing questions that should be discussed directly instead of denying the reality of AGI.

The post Artificial General Intelligence Is Already Here appeared first on NOEMA.

Gray’s provocative volume focuses on the diverse ways of ordering societies that have emerged out of the dispelled illusion that a liberal universalist consensus was bound to reign after the end of the Cold War.

As Gray once put it to me, “We are just returning to the pluralism that has characterized most of history.” He cites the dictum of the 17th-century philosopher Thomas Hobbes as his guiding light.  “There is no finis ultimis [final aim],” Hobbes declared in “Leviathan,” “nor summum bonum [highest good] as is spoken of in the books of the old moral philosophers.”

The world Gray sees out there today is not a pretty one. He casts Russia as morphing into “a steampunk Byzantium with nukes.” Under Xi Jinping, China has become a “high-tech panopticon” that keeps the inmates under constant surveillance lest they fail to live up to the proscribed Confucian virtues of order and are tempted to step outside the “rule by law” imposed by the Communist Party.

Gray is especially withering in his critique of the sanctimonious posture of the U.S.-led West that still, to cite Reinhold Niebuhr, sees itself “as the tutor of mankind on its pilgrimage to perfection.” Indeed, the West these days seems to be turning Hobbes’ vision of a limited sovereign state necessary to protect the individual from the chaos and anarchy of nature on its head.  

Paradoxically, Hobbes’ sovereign authority has transmuted, in America in particular, into an extreme regime of rights-based governance, which Gray calls “hyper-liberalism,” that has awakened the assaultive politics of identity. “The goal of hyper-liberalism,” writes Gray, “is to enable human beings to define their own identities. From one point of view this is the logical endpoint of individualism: each human being is sovereign in deciding who or what they want to be.” In short, a reversion toward the uncontained subjectivism of a de-socialized and unmediated state of nature that pits all against all.

The Illusion Of Universality

Gray has long been a discomfiting apostle of pluralism against the false idol of one-size-fits-all universalism under a liberal banner that fails to acknowledge the diverse disposition of humanity.

In a prescient conversation in London two decades ago, when the post-Cold War end of history was still on the horizon, we discussed how liberalism was bound to fail just as Marxism did, and for the same reason.

Marxism had no theory of politics among diverse constituencies because it assumed the universality of the interests of one class. Liberalism also has falsely assumed its own universality in the belief there can be a consensus on only one conception of “the good life.”

“It is an irony,” Gray said back then, “that Marxism’s defective understanding of the sources of politics both in theory and practice should be replaced by a form of liberalism that has an equally defective understanding of the sources of politics. … Liberalism has aimed at abolishing politics or removing from the political domain most of the controversial issues having to do with justice, the regulation of personal liberty and the clash of values, and placing them in the sphere of rights and the judiciary.

It is this disability of mainstream liberal theory … that seeks to derive something like an ideal constitution from a theory acceptable to all ‘reasonable’ persons. Within this ‘ideal constitution’ major issues of the regulation of liberty and of clashing ideas of the good life are resolved or privatized. This kind of liberalism is as utopian and perverse in its actual consequences as was Marxism.”

In theory, “the neutral state” seeks a framework of rights that is equally impartial among competing conceptions of the good life. Individuals and groups are left to pursue their own interests and values as long as they are consistent with the liberties of others. In reality, it is precisely the absence of any substantive content of the state that has invited the culture wars over contending visions of “the good life” raging across liberal societies today. The clash between so-called civilizational states such as China and Russia with the liberal rules-based order constructed by the West springs from the same dynamic.

For Gray, the presumed neutrality of “legalist liberalism” has two disabling flaws.

“The first flaw is that the rule of law is taken as an accomplished fact, which is not the case anywhere in the world. … The rule of law is not the precondition of politics, but is itself a political achievement. Unless you have a political settlement underpinning the rule of law, the rule of law will be insecure or contested.” 

The Trump trials, the U.S. Supreme Court rulings of late, the legal battles in American states over guns, abortion and LGBTQ issues all testify to the truth of this statement, as do questions over the rights of asylum and immigration in both the U.S. and Europe.

“The second flaw,” Gray argues, “is the expectation that issues which are politically intractable can become tractable by removing them from the political arena and enshrining a solution to them in terms of judgments about fundamental rights. … [But] attempting to remove highly controversial issues like abortion from the political domain and placing them in the sphere of rights only ends up politicizing the judiciary.

Further, this legalist approach casts in stone the resolution of conflicts that might best be resolved by legislative compromise, by a mixture of public discourse and political bargaining that yields a ‘modus vivendi’ that is renegotiable over time and which needn’t be the same in all jurisdictions or in all countries where changes in values — and even technology — can make a difference.”

Rights With Content Cause Contention

“Beyond all this,” Gray continued in our conversation 20 years ago that could have taken place today, “there is a deeper reason in philosophy itself that argues against the legalistic, rights approach to liberalism. The deeper reason is that there is no plausible or defensible theory of rights which doesn’t invoke a theory of human well-being and of human interests — and all such accounts are in some degree rationally disputable.

Accounts of human well-being and of human interests are contestable in two ways. One way is that different readings of the human good, different ideals of the good and different beliefs about human beings — their fate and destiny and the conditions under which they thrive — will map human interests differently. Thus, different conceptions of human well-being will generate different accounts of human rights.”

He went on: “Another [reason] is that even an agreed conception of human well-being will encompass a variety of interests that won’t always be harmonious. They won’t always make the same demands in practice. They won’t always dovetail. Quite commonly, they will make competing demands.

The underlying reality disguised by legalistic liberalism is that important liberties are endemically in conflict. The freedom of gays not to be discriminated against, not to have their sexuality disparaged, may conflict with the freedom of private or public schools — Orthodox Jewish schools, Muslim schools, Catholic schools and state schools — to hire whom they wish. That is a real conflict, a genuine deep conflict.”

Clearly this conundrum underlay the ferocious fights over the content of curriculum and parental control in American schools.

“To re-describe the liberties so that they cohere in a harmonious set eliminates or deletes some liberties from the equation. This is a mistake because if you delete some liberties you are disregarding underlying interests which actually are the justification for the liberties and which give them meaning and content. Rights have content only to the extent they embody definite human interests. But to the extent they have that content, they trigger conflicts among themselves.”

Back To The Middle Ages

If legalist liberalism that enshrines rights is the basis of its own undoing, what then is the alternative?

“Liberalism for the future,” says Gray, “must recognize that judgments about human rights and conceptions of human rights themselves embody conceptions of the good that are contested between different ways of life and even within them. … Any well-developed conception of the good must recognize not just one human interest, but a whole variety. And that means a negotiation between conflicting interests in the name of civil peace. A ‘modus vivendi’ is the liberalism now in order.”

For good and ill, we’ve seen in history how such a modus vivendi actually worked during the late Middle Ages in Europe, a time of plural jurisdictions, each with its own set of governing values, before the Treaty of Westphalia, when the absolutist claims of the modern state hadn’t yet been accepted.

“Despite the systematic inequalities of power and privilege, and systematic discrimination against minority religions and traditions,” Gray mused in our London talk, “I tend to share Isaiah Berlin’s judgment that in some respects the Middle Ages were more civilized and more peaceable than our time,” referring to two world wars and the nuclear devastation of Japanese cities. “And that is precisely because all those plural jurisdictions had to negotiate with each other over their powers and interests, none powerful enough to simply dominate the other.”

These competing, but often overlapping, jurisdictions and identities have a clear echo in the circumstances of our own time as the world once again splinters into civilizational realms and cultural tribes within societies. “The Middle Ages,” says Gray, “reminds us that there are many other ways in which human beings have arranged life other than under the nation-state and found a ‘modus vivendi.’”

At a time when the rule of law is being sacralized as one of the key pillars of democracy under threat from autocrats and populists, Gray’s “thoughts after liberalism” are deeply unsettling to ponder. But that does not make him wrong.

The post What Comes After Liberalism appeared first on NOEMA.

If China’s government and its critics agree on one thing, it’s that there is an analogy between contemporary China and the Soviet Union, whose collapse continues decades after it formally ended. The Red Empire tried to swallow up the continent of Eurasia until eventually, as late Soviet thinkers like Lev Gumilev would have it, Eurasia swallowed it. Today, Chinese exports and infrastructure are trying to bring order to the Eurasian continent, following in Soviet footsteps.

The U.S.S.R. was many things, but above all, it was an organized project of reconfiguring the resources within a territory to achieve material outcomes under a formal, centralized hierarchy. In that, it was a failure — the machine stopped working. “Anyone who doesn’t regret the passing of the Soviet Union has no heart. Anyone who wants it restored has no brains,” Vladimir Putin famously put it. Can it be true that China’s leadership falls into the second category?

But the U.S.S.R. was a bankrupt idealism forced onto colonized nations by military power, and China is a savvy entrepreneurial technocracy that has solved the problem of providing basic necessities to its population and is now exporting that model elsewhere. Maybe your country is next. The gap between reality and the “plan” that was so typical of Soviet life hasn’t been seen in China for a while, though some fear it’s coming back.

From climate infrastructure to agriculture to finance, China is reverting to the structure of a command economy, rather than that of a free market economy — in the Chinese phrase, “国进民退” (“the state advances as the people retreat”). This is dangerous in China’s 60/70/80/90 economy: private sector actors contribute 60% of GDP and are responsible for 70% of innovation, 80% of urban employment and 90% of new jobs. Can the state really replace this?

When the U.S.S.R. collapsed, it was because the multivariable equation of the economy blew a fuse; the supply and demand, capital and labor, stopped working. Oceans dried up. The world stopped behaving in a predictable way. Marxists like Mikhail Gorbachev believed that the system could work if you let air into it; it turned out that it blew away like a handful of dust. The decentralized decision-making structure of the markets in the West triumphed over the planned economy.

Today, scholars of the Soviet Union such as Stephen Kotkin argue that the command economy was one source of Soviet fragility. These historical debates have been lent piquancy by the Russian invasion of Ukraine. They certainly have significance in the party schools of the CCP, which has focused on exploring why the Soviet Union collapsed ever since it happened. In China today, statistics (literally the science of the state) are suppressed because they might jeopardize the government’s ability to control flows of capital, data and everything else related to human life.

By its nature, power seeks to perpetuate itself, but China’s meditations on the collapsed U.S.S.R. are contextualized by climate change, whose challenges will make or break the Chinese system and its ability to plan and forecast. Chinese science and technology are brandished by the leadership as the solution to all problems, but there is not just one form of science — nor is science a golden ticket to escape from political contradictions.

As Ben Peters, the historian of Soviet science, told me, “Like a mountain range with many canyons and cliffs, the state of science may appear a single hulking monolith from afar but [is] a labyrinth for those who live it.” In the crises to come, will Xi Jinping’s return to a command economy seem like a sage choice or will it prove as disastrous as Joseph Stalin’s economy of production without consumption, of a “great plan for the transformation of nature”? And what sort of people will dwell in the labyrinths, waiting for a new sort of world to dawn?

The Time Traveler

“Hundreds of miles of desolate, monotonous, sun-parched steppe cannot bring on the depression induced by one man who sits and talks, and gives no sign of ever going.”
— Anton Chekhov

We drove for six hours through a desert that sprayed up white dust in a place with no roads. Once upon a time, visible in filmstrips and paintings, even in preserved cans of tinned fish, Karakalpakstan, the largest province of Uzbekistan, was a marine community of fishermen living on the banks of an inland ocean. The Aral Sea owes its name to a Mongolian root that means “sea of islands.” Today, it is a toxic desert, one which the government of Uzbekistan is trying to heal by planting saxaul trees to hold down the soil.

This ocean was turned into a desert by Soviet irrigation projects intended to grow cotton, or by subterranean bomb blasts, or both. Once the ecological transformation began, there was no stopping it. It was above 120 degrees Fahrenheit when I visited on a trip organized by the Aral Culture Summit, which brought a group of writers and artists to swim in what remains of the sea’s salty waters. I was reminded of nothing so much as H.G. Wells’ time traveler, who voyaged deep into the future and discovered a red sun hanging low in the sky, a salt-encrusted shore by a dull, black ocean, with no signs of life except for crabs the size of human beings.

We saw no crabs, but having taken several commercial flights to arrive and obsessively looking for places to charge my iPhone, I wondered if I was the crab. A ravaged planet was the inevitable future that Wells, one of Victorian England’s most visionary thinkers, foresaw — and here we are.

I found myself trying to explain Lake Mead to our guide Oktyabr, and my fears that Los Angeles would dry up in the near future. He nodded politely. For him, that future happened a long time ago. He grew up in a town called Moynaq, footage of which appeared in an archival film shown at the local museum; it reminded me of working-class Chinese communities of today: a fish-canning factory, a self-contained community, pride in work done for the country. Today, Moynaq is a waystation on what feels like an interminable drive through the desert, where you stop for lunch in one of the remaining buildings on your way across what used to be seabed but is now a dusty wasteland.

The Soviets knew what they were doing; the Aral was collateral damage. After it started to run dry, the Soviets planned to divert Lake Baikal, the spiritual homeland of Buryat Mongols, to refill it, but by then the machine was already breaking down, only slightly faster than the Aral ecosystem itself. Today, both are wrecks. Tying natural flows up in knots, the Soviet project suffocated itself and its corpse continues to rot on the terrain of Eurasia, a graveyard of a socialism that is attempting to return in zombie form.

Back in China, the politics of water are impossible to escape; my flight was delayed by terrible flooding that made the Beijing airport unusable. The Chinese government at its most Ozymandian engages in water-related engineering projects that make the Soviet Aral project look like a child’s sandbox play. The Three Gorges Dam, whose collateral damage was to flood towns like Fengdu, displacing 1.3 million people in the process, looks like the first of an increasingly ambitious list of terraforming projects, with more — the massive dam at Yarlung Tsangpo, the north-south water diversion project — on the horizon. 

The Chinese government’s mentality is that ecological and economic problems can be engineered away and that technology applied at the highest level can solve them. The Soviets thought so too. Is Karakalpakstan a sort of prophecy in miniature, a vision of unintended consequences of interfering with ecologies at scale?

The Great Northern Wasteland

“A thing that has not been understood inevitably reappears; it cannot rest until the mystery has been solved and the spell broken.”
— Sigmund Freud

As we trudged our way through the summer of 2023, I found myself contemplating buying a tract of land in Heilongjiang, China’s northernmost province and the one that has always felt most Soviet to me. Today, it is being deserted by outbound migration. The thing is, Shanghai and Beijing look like they’ll be 100 degrees or hotter for months every year in the foreseeable future. Wasn’t there some way to escape? I browsed property listings in Yichun, a city of 1.3 million that was a base for forestry in the socialist period. As climate change unfolds, maybe being in the middle of a Siberian forest, with pure air and water and pleasant temperatures even at the height of July, would make for a good life.

During the Maoist period, students were sent down from urban areas to camps there, and they made a huge swath of Heilongjiang into agricultural land. Today, many of these collective farms are owned by the Beidahuang Group — the name literally means “the great northern wasteland” — and they produce around 10% of China’s grain crops.

Beidahuang is a state-owned enterprise — really, it is almost a state within a state. In the 1960s, its “employees” skirmished with Soviet troops. It’s not the only Chinese state-owned enterprise to assume these contours. The Xinjiang Bingtuan — which engages in agricultural and industrial projects in Xinjiang Province and provides healthcare, education, police and judiciary services in the communities where it operates, some of which have populations in the hundreds of thousands — has the same Communist ethos.

These organizations have never been oriented primarily to profits, even if they list on stock exchanges in Hong Kong or New York to raise capital. They reflect political needs — food security, political security. Recently, the former deputy commander of the XPCC was expelled from the CCP for “interfering with the implementation of carbon peaking and carbon neutrality strategic goals.”

All this is to say that the Chinese government is not new to collective, militaristic enterprises in terraforming, nor did it ever stop engaging in them. On the surface, Beidahuang, with its proactive uptake of automated agricultural practices, seems pretty modern. But it is an organization with roots in the reddest of China’s red history.

Historically, Chinese troops were sent to border regions to settle and engage in agriculture — “屯田” or “tuntian” literally translates to “military-agricultural colonies” — a policy that had practical outcomes like producing food and securing territory if that was in doubt. Today, China is building large-scale wind and solar plants on the fringes of the nation, state-owned enterprises are taking up a larger and larger role in the economy, and the logic of GDP or profit as such is being discarded in favor of a different logic — a political logic, one more akin to war communism than the Chinese economy that we’re used to.

This doesn’t mean that there are no market practices embedded within the Chinese economy. The government sets the parameters and goals and pits different state-owned entities in competition with each other. Moreover, companies like Beidahuang function very differently than they did in the 1960s: Instead of unskilled labor wasting time in gulag-style encampments, today young engineers are supervising farms that are largely automated, earning high salaries for skilled and technical work.

Nevertheless, this work is done in the service of centralized planning and national reserves of pork or grain, and the market is tightly controlled. It looks like communism from the outside, but on the inside, it increasingly resembles American agriculture.

In 2001, Andrew Solomon wrote of the artists in Beijing, “In the eyes of many Chinese, the Cultural Revolution was like a game; interaction with the West is another version of the same game, perhaps a less interesting one.” Chinese socialism, and more specifically state-owned enterprises like Beidahuang, has integrated practices from the globalized capitalist economy without losing the “Chinese characteristics” (centralized control by the CCP) that it began the journey with.

Eldridge Colby, a leading Republican China hawk, and others have a habit of suggesting that China’s newfound emphasis on food security reflects preparation for war. But Chinese grain yields keep suffering “one-off” climate events, which are increasing in frequency. Last year, China’s agriculture minister told reporters that “crop conditions this year could be the worst in history.”

What if China is simply preparing for a rapid energy transition and food security in case the worst climate eventuality comes true — the “war against heaven and Earth” that Mao talked about? By 2020, China was the largest food importer in the world, a fact that made China’s leadership deeply uneasy. Lodged deep inside of millenarian ideologies like Chinese communism is the idea that everything will change, that some sort of apocalypse is around the corner.

Xi has taken to saying that the world is experiencing changes not seen for a hundred years. The economy that he is directing from Beijing isn’t really following the logic of good times and prosperity anymore. Instead, it’s more like Mao’s slogan: “Dig tunnels deep. Store grain everywhere. Never seek hegemony.”

The Soviet Prophecy

“The novelty of the coming politics is that it will no longer be a struggle for the conquest of control of the State, but a struggle between the State and the non-State (humanity), and insurmountable disjunction between whatever singularity and the State organization.”
— Giorgio Agamben

The basic feature of the Chinese landscape is the Chinese themselves — “人山人海” or “crowds of people.” The state is forever trying to keep up with them, shaping human flows as it guides rivers, terraforms the land and otherwise modifies nature according to some grand plan. Can the flow of people — their desires and fears — be tamed to generate economic growth in the way a river can be dammed to generate electricity? It seems doubtful, but that never stopped anyone from trying.

Visitors to China are often told that Beijing symbolizes China’s traditional culture. Considering that 95% of its population and footprint were built after 1949, that’s a bit of a stretch — unless we take the view that Chinese culture is not about superficial appearances but deeper, more profound social structures. Crawling through traffic on the ring road that used to be a city wall before it was demolished to allow “qi” to flow, observing the various mountainous headquarters of this or that state-owned enterprise, the city can appear to be the realization in urban form of Walter Benjamin’s parable:

The coagulation of different, seemingly incompatible historical experiences into a city has given Beijing an irrational, almost mystical quality. It is exactly that quality, of glancing back into historical catastrophe while being pushed forward almost against one’s will into future challenges — which may yet end in disaster — which makes Beijing a world capital. There are subway stations named “Earth City,” parks named “Temple of the Sun”; under the Qing, the city’s urban plan was intended as a mechanism to control cosmic flows.

The fight against nature is becoming more intense every year; Beijing will suffer from heat more than almost any other Chinese city, and it is being fiercely guarded against climate disruptions as if from a marauding army. It is the capital of China’s technocracy, which is willing to change everything — the courses of rivers, the placement of mountains, the homes of millions — in order for nothing to change.

Economists speculate that if China’s state doesn’t manage to cut emissions, the collapse of the state might do it. As an atmosphere of crisis mounts, the deep memories of the state, which long ago became instinct, recur and re-manifest themselves. For China, the only way out is through.

The post China’s Soviet Shadow appeared first on NOEMA.

Penelope was not a particularly notable rat before her disappearance. She was about a year and a half old. Like all Algernon Project rats, her coat was the slate blue that I’d dyed my hair to match (though since pregnancy I’d gotten a little lazy and my roots were showing). She had a splash of pure white around the eyes and nose that gave the appearance of a mask. She’d not done exceptionally poorly or well in the vocabulary or aptitude tests. Unlike my favorites, she didn’t seek out human companionship. She wasn’t shy or human-adverse so much as independent, checking in and then going about her daily rat business (mostly horsing around with her favorite cagemate, Jasmine).

Still, I cared for her and mourned.  The loss was also an embarrassment for the Algernon Project. BabbleLinks are an exorbitantly costly A.I. cross-species communication system.

In my defense, I was housing fourteen rats across three large cages when Penelope disappeared. I’d never lost a rat despite having been a part of the program for years, and I’d long since stopped conducting rigorous headcounts. After free-roam, everybody mostly was eager to return to their preferred hammocks for mid-morning naps. At most, I’d note whether the younger rats — the ones who still explored with vigor — were all in their cages. But Penelope didn’t have the demeanor of a runner.

My husband Peter scolded the Algernon Project for not having included basic trackers in the implants. In truth, more surveillance had hardly seemed necessary. Video cameras were everywhere (I’d watched Penelope’s moment of escape many times). So long as the rats remained in close range, an LCD screen on the wall displayed their brain activity, vitals and transcribed everything they said.

And so, I was relieved a week later when I found Penelope sleeping in the curve of a running-wheel stored beneath her preferred cage.

I gently petted her awake. She yawned and stretched her paws forward — as though she’d only been away for a minute.

“Where have you been, Penny?” I asked through the BabbleLink.  The human end of the BabbleLink was a bone conduction headset that translated their chitters and ultrasonic frequency tones. When humans spoke, their headset communicated with the BabbleLink implants in the project’s specimens and created bone conduction sounds for the rat designed to appear to emanate from the human wearing the headset.

She crawled into my palm lazily, anticipating that I’d transfer her to the cage. I had bandages on the back of my hand covering a new tattoo of a neuron. The rats all loved worrying it and Penelope was no different. She busied herself tearing at the gauze while I inspected her coat for injuries and fleas. My tattoo was mostly healed and, rather than pain, her nips created a physical tingle in me that mirrored my excitement over her miraculous return from the dead. I combed out the few fleas I found on Penelope, but otherwise, she was in remarkably good shape. 

“Where have you been?” I asked again. “Why did you leave? How did you survive?” This was bad form. Multiple questions with less familiar words like “survive” often led to muddy answers.

I placed her next to the communal food dish and watched her wolf down lab blocks — ignoring me. Then I listened to the familiar click-clank-click of her drinking from the water bottle.

I worried that her BabbleLink implant had been damaged, but eventually, her answers flowed in through my headset. “Mango?” she asked with urgency — an emotion signified by her faster, higher-volume speech.

In some ways, this was unremarkable. A good chunk of our newfound ability to communicate with animals involved relating culinary desires. Every rat I had ever known requested the same four foods: peas, corn, nut butters and avocado. Beyond that came individual preference. Long ago, I’d laid down ground rules that my rats could state food preferences only after I said “Requests?” Otherwise, the BabbleLink became overwhelmed. My rules were not always honored by the rats, but ignoring their unsolicited demands helped hold the line. 

In other ways, Penelope’s request was peculiar. While she was a fan of fruit, she’d never requested mango by name before. She also was not particularly food-motivated and rarely made unprompted requests. She was polite. But she’d just returned from an adventure and so I indulged her.

“It’s frozen. Give it some time to warm in the water or you’ll hurt your tongue.”

Penelope’s requests for mango continued in the days that followed, as did her heavy appetite. I rationed lab blocks for the first time ever. Typically, animals didn’t overeat lab blocks because they weren’t very appetizing. This restriction, however, worsened her behavior. I caught her stealing food from friends. She stopped coming out for free-range time and slept more. She was curt and sometimes downright touchy when questioned about why she ran away, where she’d gone and why she returned.

I didn’t panic. Prey animals are hesitant to reveal what bothers them and the BabbleLink doesn’t change this instinct. Yet at the same time, traumatic events could change a rat’s personality. I’d witnessed this when a friend of theirs died after hind-leg degeneration injuries or even just as they adjusted to the indignities of rodent aging. I’d had an energetic rat pup suffer an electric wire shock that left him afraid to leave the cage. From the outside, he’d just seemed to spiral into a spontaneous existential funk. After a week of playing rattie-therapist, he confessed what had happened. I showed him how to avoid shocks, double-checked for other wires and promised he’d be safe. He recovered.

I held out hope that Penelope could similarly be coaxed to talk with patience, even as she denied being lethargic or that anything hurt. Vitals revealed nothing amiss. I chalked the changes up to overexcitement, suspecting that they might subside.

After another week, the lethargy broke. A flurry of activity followed where she requested paper towels, tissues and cotton balls. She built a fort of sorts. This new interest in engineering led to a fresh conflict on cage-cleaning day. Cage-cleaning day was always unpopular, and so I typically waited for everyone to be out playing. But now Penny no longer left the cage; instead, she sat territorially in her little fort and refused to come out — even giving a warning nip at my finger.

“Please, Penny,” I said.

“Sharon,” she said back, in a manner that I swear sounded like sarcasm.

“You can rebuild your fort. The cage is dirty.”

She stared back stubbornly. I sighed, and pet behind her ear then down to her rump. She didn’t relax, but also didn’t protest with another nip.

“Your belly has gotten so big,” I said. “My God.” My hand shot away, sending Penelope’s hair up in high alert. “Penny, you’re pregnant.”

Her body went slack and she chittered. The AI translated this as laughter — perhaps in response to my obliviousness. 

“I didn’t realize,” I said. “I won’t clean. Hold on.” I got her a fresh mango meant for me. She ate the messy fruit straight from my hand and everything seemed forgiven.

Her head tilted. “You can’t smell my babies?” she asked.

“No,” I said. “You can smell babies?”

“I smell your babies.”

My baby. Six months along. I hadn’t mentioned him to the rats, but suspected they were aware. They were newly curious about my swollen belly.

Penelope’s comment was a breakthrough. Plenty of evidence existed that animals anticipate the future (something unsurprising to anyone who’s seen a dog excited for a walk), but expressing awareness of a future childbirth was sophisticated anticipation.

“I can’t smell your babies. Your nose is stronger than mine. Do you know how you became pregnant?”

“Babies.”

“Yes, babies. But do you know how they got in your belly?”

Penelope was silent. The data on the LCD screen attached to the wall showed that her brain was trying to process, then abruptly the attempt stopped and she grew distracted.

“You met someone out there,” I said, guiding her toward an idea.

“Fernando,” she said. Fernando was Penelope’s former favorite elder cagemate. He had passed away a year before. For a mad moment I imagined he’d actually escaped and was living in my walls, but I’d seen him peacefully gassed after his cancer spread.

“Fernando who used to live with us?”

“No. Fernando. Fernando.” she repeated insistently.

“Okay. This new Fernando, he was nice? You got along with him?”

“Fernando smelled good.” This was her way of expressing affection, rather than concept words like love — the cagemates she cared for smelled good. Disfavored cagemates smelled bad.

“Could he speak?” I asked.

“Mute.” Mute was their word for a rodent without an implant. Rats didn’t use BabbleLinks with each other directly, but they knew who had implants. The project hadn’t figured out how the rats could tell — but I suspected it was listening to their cagemates’ vocabulary usage and observing how their companions interacted with humans.

“Do you think this is why you got pregnant? From meeting Fernando?”

The brain activity scanner didn’t tick up this time. “Sleepy,” she said. Some rats would say I don’t understand. Penelope’s habit was that — rather than admitting confusion — she claimed to be tired. Pride, perhaps. Or she was tired. Already, this was the longest conversation Penelope had ever had with me.

I nodded. “Was life difficult while you were gone?”

Her brain activity flared up again. “Fernando hungry. Thin. Penelope hungry. Poison food. Poison.”

This was a stunner. Had I mentioned poison? Never. I’d once inadvertently offered them spoilt peas, but probably called them moldy. But then again, poison would be central to a wild rat’s life, so of course some word would exist.

I pet her firmly, resisting the urge to squeeze her in apology for rationing her food when she’d first come home,  and for all the poisoning that humans had done across history.

My gestating baby was most active at night. The evening Penelope returned, I felt him kicking while considering this cross-species conversation. I internally debated whether my baby triggered Penelope’s elevated maternal drive.

The Project had set up the experiment with neutered bucks (male rats) and “intact” does (female rats). The bucks’ surgery was done simultaneously with BabbleLink implanting. This had been a compromise result so that lab leaders could commingle the sexes without propagating a million rats, while also preserving the ability to continue the biological strains the Algernon Project had carefully bred.

Neutering is less invasive than spaying and lowers buck aggression. Although leaving the does intact raised tumor risk slightly, that seemed worth avoiding surgery risk and preserving some gene lines. But it did mean the does had weekly cycles where they grew hyperactive and harassed the bucks with futile mating rituals, sometimes mounting them as if demonstrating what they should be doing — teaching steps to a dance these bucks would never learn.

Generally, I tried not to think about my rats as sexual beings. Normal things easily got weird when I did. For example, some rats enjoyed being tickled during playtime. Yet some female rats only requested tickling while in heat. What to do with that data? It was best to ignore the ramifications. Usually, I just ended up tickling them and moving on with my day.

But having a pregnant rat who had confided in me the details of a forbidden coupling was something else. The incident made me suspect that Penelope was far more intellectually capable and resourceful than I’d realized, to the point that she’d even kept her cleverness secret. What if she’d seen me pregnant, conspired to escape, and go on a hero’s journey to create her own parallel pregnancy and children?

I woke Peter even though I knew this would annoy him, and recounted the day’s events. As I spoke, he traced my linea nigra — that mysterious line that appears during the second trimester. Mine was thick and rich and ran all the way from my belly button down to my pubic hair.  

When I finished the recounting, he sighed. “That’s everything?”

“That’s not remarkable enough for you?”

“A tale as old as time. A small-town lass has no viable men around, so she sets out to the next town over. In the human version, six months later she’d show up at her parents’ door crying that Fernando had jilted her. For rats, I’m sure you can find many Reddit pages asking what to do if your pet rat escapes and then returns pregnant.” He sighed again, then asked, “Well grandma, are you going to let Penelope keep the litter?”

“What do you mean?” I was half-horrified he’d considered any other option, but he was correct that the Project might request this.

“They’ll be half wild. They might harass their tame cage-mates. They might bite them or you. Imagine having a half-wolf in a dog pack.  And the expense of maybe a dozen more unplanned Babble chips might concern the Algernon Board.”

“I can’t believe I rationed her food. So stupid, the pregnancy was so obvious. You’d think I was a hobbyist.”

“Obvious once you saw it.” He rubbed my back. “She’s eating plenty now. Much more overall than if she’d stayed away.”

“She was on calorie restriction for nearly half of her pregnancy.”

He scratched the surface of my bump. Our boy was doing bicycle wheels in there. “An understandable blind spot. You were thinking your rats were a new thing, separated from the wild world — which they are in many ways. But they are still also that old thing.”

My friends sometimes suggested that Peter was the rational one and I was more emotional. He was ex-military, and many read rationality into his good posture and understated delivery. But I knew him well enough to see past this.  He had wept uncontrollably for almost 20 minutes after I told him he was going to be a father. It was so unexpected, so raw, that it took some time to realize he was happy and merely overcome with emotion. The child had been planned and conceiving hadn’t been difficult compared to many couples in their 30s. This outburst had made me love him more, which annoyed me. Crying over something like that shouldn’t make him more worthy of love — but some primal place in me was stirred and reassured by his display.

I spent several days drafting an explanatory email to the Project’s program director.  In the meantime, Penelope consented to having her makeshift nest moved to the maternity cage where only Jasmine, her best friend, was allowed to join. I showed Penelope our baby room from the perch on my shoulder. Rat eyesight is weak, so I had to take her up close to see the cradle, the glider where I’d nurse and the little stuffed rat toys everyone had sent as gifts. I explained this was my nest, feeling a little silly given that Penelope’s overwhelming experience of it, for now, was likely the unpleasant smell of off-gassing. Still, she was chatty and curious, asking why the baby wouldn’t sleep with Peter and me. Contrary to her pre-adventure behavior, she wanted to talk all the time.

I watched Penelope labor in real time from the next room via video screen, as she moved every which way, trying to find a comfortable spot. Something in her breathing suggested birth was imminent. This squirming stage lasted for about half an hour. Then, slowly, eight pink pups came out and immediately squealed. She licked the squirming pink mass of babies clean, chewed through the tiny umbilical cords and consumed their still-throbbing placentas. And like that, it was done. No epidural, no forceps, no c-section, no doctor or midwife shouting “push!”

After she woke from a long nap, I approached the maternity cage with mango. Penelope ignored it and instead dragged me by the finger where the blind, hairless pink pups were stacked. I dutifully pet them. Her BabbleLink transmission was an endless loop of their names, all of which were old cagemate names plus Peter and Sharon. (Perhaps rats simply don’t have many name sounds?) Penelope kept noting how good the babies smelled.

I sent my email to the Board only once the birth was complete, ensuring that aborting wasn’t an option.

I was invited to present my case at the next online meeting of the Project’s Board. 

STEVEN (SECRETARY): This is the time and the place designated for our April 10, 2030, meeting of the Board. We have present five Board members. One non-present voting member has delegated her right to the Chair, Emily Spiro. The sole item on our agenda is whether to grant a one-time expenditure for BabbleLinks for an additional litter of unexpected half-wild rats. 

EMILY (CHAIR/ BOARD SEAT #1): I think we are going to hear briefly from Sharon Esposito, the leader of Lab Number 26. Right, Sharon? Are you in the meeting?

SHARON (LAB LEADER # 26): Here.

EMILY (CHAIR/ BOARD SEAT #1): Oh, I love the tattoo on the back of your hand. Is that a neuron?

SHARON (LAB LEADER # 26): A rat brain neuron. I did my graduate research on rat consciousness as well.

EMILY (CHAIR/ BOARD SEAT #1): Fitting. Plus, your hair is the same color as the rat coats. Classic. So, what would you like the Board to consider?

SHARON (LAB LEADER # 26): Yes. So, Penelope the rat escaped for one week and was impregnated by a wild rat. She successfully gave birth to eight pups earlier this week: three girls, five boys. The mom and babies all survived and appear healthy. As a result of her sojourn, Penny has become more expressive and is providing insights into maternal behavior. I’d love to see where this takes us and I believe having implants for the babies will continue us on that path, and provide insights into wild rat minds. Letting me raise half-wilds would be a good half-step.

EMILY (CHAIR/ BOARD SEAT #1): Thank you for that. I’ve spoken informally with the rest of the Board and I can say approving money for the half-wild litter won’t be an issue.

SHARON (LAB LEADER # 26): Great! You don’t know what a relief that is.

EMILY (CHAIR/ BOARD SEAT #1): Of course! Your experience already shows that there’s much we can learn from expanding our data set. The revelation that wild rats seem to have a pre-existing word for “poison” is fascinating.

SHARON (LAB LEADER # 26): Surprising yet intuitive. We know wild rats communicated poison risk. They’ve been observed designating a “taster” when encountering new foods and smelling each other’s breath to memorize the scent, then avoiding similar foods when the taster got sick.

EMILY (CHAIR/ BOARD SEAT #1): Fascinating. For the benefit of the group, do we have an idea of how much transfer of knowledge there is among your rats, say intergenerationally?

SHARON (LAB LEADER # 26): We know they use the sounds we teach them through the BabbleLink with each other. This builds a vocabulary that outpaces their non-linked peers. Each successive generation is more sophisticated. For example, we see little things like the older rats teach the younger ones where the designated toilet areas are and we don’t need to potty train each new generation.

EMILY (CHAIR/ BOARD SEAT #1): Very helpful. Now, the reason I ask all this is because we got a call from a key funder with anxiety around the accidental release of super rats who understand how bait works and who is setting it. The information we give these augmented lab rats will spread to the wild population. We want to implement some additional mitigation measures, and we’d very much like to say in the press release that you and the other Lab Leaders support them — plus mention your rat’s outside adventure.

SHARON (LAB LEADER # 26): What kind of measures?

EMILY (CHAIR/ BOARD SEAT #1): First measure, we’ll ask that you spay the half-wild does when the bucks are neutered. This is because the half-wilds are seen as a greater flight risk because they aren’t bred for docility and their mom has already shown that capability. We don’t want them to continue their line in the wild if that happens.

SHARON (LAB LEADER # 26): Okay.

EMILY (CHAIR/ BOARD SEAT #1): Second, we’ll put in guardrails to make sure that escapees won’t be able to interfere with pest control. He compared the risk of rats escaping to gain-of-function lab leak risks, because your labs contain enhanced species that if introduced to wild environments could quickly spread and dominate standard species due to their communication advantages.  And I agree that we need to think through what happens if an evolution we engineer spreads in the general community. So until further notice, we are asking that you not share anything with your rats about the history of lab work or engage in any data sharing about how poisons work or how to spot them. Current subjects with this knowledge must be isolated from younger generations until natural death.

SHARON (LAB LEADER # 26): Is this necessary? We’re not talking Planet of the Apes. Their communication is still mostly monosyllabic.

EMILY (CHAIR/ BOARD SEAT #1): So long as the BabbleLink is mechanical and non-hereditable, I agree that sophisticated language evolution risk is low. But as your own experience suggests, these are social creatures that teach each other, and we are only now getting a loose grasp on their language capabilities. Any trait that improves survival chances could quickly dominate and frustrate rodent control.

SHARON (LAB LEADER # 26): Still, you’re talking about isolating twilight rats, which can be stressful.

EMILY (CHAIR/ BOARD SEAT #1): As to your colony, this concern is purely theoretical as our database records show that your Penelope was the first in your colony to use the term “poison,” and that word was introduced to her by a wild rat, rather than vice versa.

SHARON (LAB LEADER # 26): So you’re saying Penelope would not need to be separated under these new guardrails?

EMILY (CHAIR/ BOARD SEAT #1): Correct.

SHARON (LAB LEADER # 26): That’s fine then. I wasn’t planning to teach my rats molecular biology. I don’t want to hold this up.

EMILY (CHAIR/ BOARD SEAT #1): Great. I think that’s it. We are ready to vote on our agenda.

ANAMARIA (BOARD SEAT #4): Hold on. Hold on one second. I have a right to enter my dissent into the record. As the saying goes, great causes have a habit of becoming businesses and then degenerating into rackets. Our vote today completes a shift from the Nomadic Labs, the movement, to Algernon, LLC the business. While I can see everyone currently on our Board still believes deeply in animal welfare, unless we hew back to our initial purpose, I fear the racket is imminent. 

ASHIM (PROJECT DIRECTOR): Missions change and—

ANAMARIA (BOARD SEAT #4): I didn’t interrupt you, please let me make my record. I feel I need to remind everyone, as the last remaining member of the old guard and the only Board member with gray hair, of our initial mission. Though we do business as the Algernon Project, our legal name remains NRNL. As in Natural Research Nomadic Labs.

Our original purpose was to design an ethical way to conduct rodent experiments by raising them as quasi-pets. To give them good lives, love them and gather data as injuries and illnesses naturally arose. With enough volume, our hope was that this “natural research” would provide more scientifically accurate results because during prior rat research the animals’ anxiety, poor health and depression confounded results. The variation of domestic environments would help because humans, after all, do not live with standardized diets or habits.

But now, money has warped this simple idea into one involving expensive AI equipment. The project’s namesake, Algernon, typifies this. Only one Algernon was ever introduced to the public, a charismatic rat with a slate blue tint to his coat. The dirty secret was that hundreds of Algernons lived unpleasant lives to develop the technology, and more are suffering in labs now to upgrade it. Even the implantation procedure has a mortality rate we’d never accept in human babies. So, in effect, we’ve moved from protesting cruel research to funding it.

EMILY (CHAIR/ BOARD SEAT #1): We’ve all read your book, AnaMaria. Is this really necessary to repeat here?

ANAMARIA (BOARD SEAT #4): Absolutely it is. If we want to eliminate animal testing, the best way to do that is to not test on animals. These new protocols are going to put us back in the place of lab worker/lab rat dynamics. For the first time, Sharon is being asked to limit what she can communicate to them for the purpose of, what, helping pest control agencies maintain their jobs and out of a fear that rodents will become too conscious of what is being done to them? This is not how we treat pets. And why are we expanding our mandate to include studying wild rats? Why are we monitoring their intergenerational communications about poison? What use is that data except for rodent control. Let poison manufacturers do their own studies.

EMILY (CHAIR/ BOARD SEAT #1): Is that all?

ANAMARIA (BOARD SEAT #4): That’s all.

EMILY (CHAIR/ BOARD SEAT #1): Well, I didn’t expect to have debate club today, so I didn’t prepare a formal rebuttal and don’t speak for the full Board but let me just say a few things for the record. First, I’ll just note that AnaMaria and her late husband had years to create a sustainable model without an AI component. As we know, enough rats with naturally occurring conditions must be presented to research anything meaningfully. But the pure natural model never got enough participants to hit those statistically significant thresholds. Outside the welfare community, researchers’ habits are sticky. They were trained torturing rats, their teachers were trained torturing rats and they’ll instruct their students to torture rates unless there are quantifiable benefits to transition to a different system.

Using AI as a carrot, we have enough participation to create usable results for behavior studies, common illnesses and nearly all major cancer research. So, while my esteemed colleague AnaMaria remains an inspiration to me and a friend — and I do envy her ideological purity — she is, unfortunately, comparing a theoretical nonprofit of unproven viability with an actual operating one that needs to make complex ethical choices. We have good data demonstrating that giving animals the ability to say “that hurts, please stop” changes researcher behavior — including the behavior of researchers not directly working with our chipped subjects.

Finally, contrary to what AnaMaria implies, we are not a for-profit corporation and nobody affiliated with us stands to make money from today’s decisions. We are accommodating donors not because we have lost the faith or are “selling out” but rather because they are correct. Ideologically, we don’t want to make rodent control harder when we all know excess wild rats disproportionally impact poor urban areas. Okay, that was a lot. Secretary, are we ready to vote in today’s measures and unplanned expenditures?

STEVEN (SECRETARY): I’m ready. On today’s agenda items A-1 and A-2 and A-3, Board seat two, how do you vote.

ANATOLY (BOARD SEAT #2): I vote aye to all measures.

STEVEN (SECRETARY): Board seat three?

STACY (BOARD SEAT #3): Aye to all measures. Thank you for that discourse, both of you. I thought it was helpful.

STEVEN (SECRETARY): Seat four?

ANAMARIA (BOARD SEAT #4): Nay.

STEVEN (SECRETARY): Seat five?

JOHNNY (BOARD SEAT #5): Aye.

STEVEN (SECRETARY): And the chair?

EMILY (CHAIR/ BOARD SEAT #1): I vote aye.

STEVEN (SECRETARY): The resolutions pass 4-1. This meeting is adjourned.

EMILY (CHAIR/ BOARD SEAT #1): Okay everyone, thank you for your time. Sharon thank you for your patience, don’t be surprised to see your name on the press release for the new protocols. We’ll get you a draft before the notice goes out so you’re comfortable.

SHARON (LAB LEADER # 26): Sounds good.

EMILY (CHAIR/ BOARD SEAT #1): Great. See the rest of you at the annual benefit.

I shut my laptop screen and turned to Peter, who had listened off-screen.

“What do you think?” my husband asked.

 “We’ll see what the press release says. It might be fine. I’ll probably sign off.”

“That’s it?”

“I mostly found myself agreeing with whoever was speaking. I hadn’t really intellectually separated the AI piece of it from the distributed labs piece beforehand. And I guess I dissected rat brains for my PhD research, so I don’t have the high ground. Maybe I’m exhibit A of the person Emily imagined when she said the AI gets people in the door through curiosity or whatever. Ultimately, I suppose I’m more concerned for Penny and my colony. This outcome seems to work okay for them.”

He nodded slowly, not exactly agreeing — more contemplating. 

“I guess I’m sad that the half-wild ones aren’t going to have their own pups someday,” I said. “But a small price, all told, for the life we give them. An abstract thing to steal from a small creature who may not know what they’ve lost — having children or grandchildren. Wild rats rarely live to meet their grandchildren.”

He kept up that slow, unconvinced nod.

“The thing I hadn’t thought about is really all that surveillance. The fact that they could look and see I hadn’t already discussed poison with the rats. That’s strange and drives home that this is a massive research project, not a hobby. I know that privacy isn’t a fair expectation and caring for the rats is in some sense a job. But I don’t think of it like that when I’m interacting. What do you think?” 

“What I’ve always thought. Very little that’s useful can be learned about humans from studying rats and that we shouldn’t do it.” He stood to leave the room. “That said, studying you looking after your rats lets me know our son will have a loving, caring mother.”

“Then the experiment was a success,” I said, and half smiled.

He winked at me, rubbed my shin, kissed my belly and headed out.

I resented that his beliefs were so pure and simple — like AnaMaria, his absolutism freed him from complex, messy moral choices. Instead, his solution of banning all animal testing was clean; and it would never be implemented. 

And so, I signed off on the press release.

Penelope’s pups grew. Their pink skin gained dark brown fur that easily distinguished them from the classy blue tint that marked the main Algernon line. As Peter predicted, they behaved half-wild. They ran around saying, “Hey!” “Hey!” “Hey!” as they bumped into each other and play-fought (before the operation, we could roughly translate words, but the pups couldn’t understand us).

When the day came, and they were both fixed and received their implants, a pup did die — little Peter, sadly. As was my practice, I left Peter’s body in the cage so the others would know he had passed away. Penelope licked at Peter, as if trying to wake him. After a few minutes, she gave up and thereafter ignored the corpse. She never mentioned the loss to me.

Another of the bucks was too aggressive — raising his fur and hissing if I got close to him, chasing, shoving and pinning his brothers, and generally making life miserable for everybody— and needed to be separated. He finally was put down after he nipped Peter (the human) hard enough to draw blood. The rest grew to be physically and emotionally healthy, if otherwise unremarkable, adults.

While they were pups and it was unclear whether their wild side would make them too aggressive to be near, I kept Penelope’s brood with just Penelope and her best friend Jasmine, who also started lactating and helped with the caretaking, but once they were neutered and past the asshole-teenage stage, I decided it was safe to reunite the colony. This was just around the time I gave birth to my son Jackie. Penelope loved licking him.

Another few months passed and Penelope acquired stately greys to go with her blue coat. They came in a slightly different color from the vibrant white splash around her nose and eyes. She grew even chattier than before. The rats I was closest with often grew extra chatty toward the end. This began around the two-year mark when their bodies started winding down, entering into their twilight age. During this period, Penelope who rarely sat still when younger, would sit on my shoulder and listen to the younger ones play, peering down in their direction. We talked and talked but in simple sentences. Age made Penelope’s thoughts lose sharpness.

I’d given up drinking for the pregnancy but had resumed after Jackie arrived. I learned from the internet that the safest time for a nursing mom to drink was actually while nursing so that the alcohol would be out of my breastmilk before the next session. One night, while feeding Jackie, I had a little more wine than usual and I got chatty with Penelope.

I brought up Penelope’s escape into the walls.

“Me?” she said, surprised.  

“You don’t remember?”

“No,” she said when I asked if she remembered anything, then chittered, seemingly amused by her younger self’s brashness.

“No memory of Fernando in the walls?”

“Fernando. Son.”

She fell asleep, and so did Jackie, and I put him down in the cradle, returned to the rat room with a fresh glass of wine and watched the young ones play.

They slept so many hours in the day, these pet rats, with their three-year lifespans — that’s just when human kids started to know anything of the world around them, and they had more waking hours in that time. Life extension was the key to learning what rats could fully evolve into.  But what scientific use was there in breeding long-lived rats? The project was probably something you could sell to some Silicon Valley guy who didn’t give a damn about rats but would pay a million dollars to stay young or simply live, for one more day.

They were taken too soon. Little lives in fast forward. Penelope was in her twilight period and firmly content, like a human retiree watching the manatees in the canal out the back porch, nowhere to go, no plans to be made, naps pleasantly sneaking up and weighing down their eyelids, as they slowly left this earth, a little less present each day while the young tried to squeeze out more moments, more memories, shaking them and startling them awake to announce dinner, startling them awake to say I love you. One last time.

Penelope yawned back awake, and I moved her to my lap and gave her a nut to puzzle open.

I wanted to tell her about the poison out there in the wild world and everything humans had done, mostly because I had been told I couldn’t tell her that. But I knew all this was recorded, surveilled, tabulated and that I could lose my place as a lab leader.

What came out was something else:

“I know you’re not going to understand this Penny, but when I was in grad school. When I was learning how to be a scientist, I was doing research. I didn’t feel comfortable turning projects down — despite the way they had us treat the rats. I didn’t have the power or the awareness that rats were like you. I did things that were unkind.”  As I spoke, I spilled a little of my wine on the baby’s swaddle, triggering another wave of guilt. 

Penelope’s brain scan was going up and down, I think more in response to the anxiety and seriousness she heard in my voice. Then, as I kept talking on, her brain scan didn’t beep at all, as though the effort had exhausted her. Penelope was just letting my words flow over her now.

I teared up.

Then Penelope said, “You smell good, you smell good, you smell good,” as if to soothe me.

The post Penelope The Rat appeared first on NOEMA.

Her poem below, which we publish in memoriam and courtesy of MIT Press, is indicative of her unique vision that traced the interconnected lineage of life on Earth from primordial times to the digital device on which you are reading this. It will be included in her posthumous volume, “Gaia’s Web.”

As Claire Isabel Webb, director of the institute’s Future Humans program, writes: 

Parable Of Tree And Stone

Long before dinosaurs roamed our planet, in a time called the Carboniferous, a tree was born. A seed fell to Earth, rooted in swampy soil, grew over a hundred feet tall and a hundred years long. When the tree died, its body became home to cockroaches as big as house cats, and dragonflies with wings as wide as hawks. Bacteria fed on the rotting wood, and mosses grew. Covered by Earth’s blanket, the tree’s body sunk deep, compressing into coal, a slow-motion burial. Millenia later, the coal was unearthed, heated, deprived of oxygen, splintered into plastic pellets, liquified and poured into molds, and polished into small black jewels. Tree, reborn: the keys on my computer.

The stone is even older than the tree.

In Precambrian time a volcano rift opened, and lava flowed from Earth’s core. Cooled by rain, the lava sunk deep, compressing into stone. Millennia later, the stone was lifted from a mine shaft, crushed and bathed in caustic fluid, liquefied and poured into molds, and polished to a shine as sharp as a knife. Stone, recast: the casing for my computer, cradle for the keys.

In deep time, trees and stones are descended from stars.

Tree once drank sunlight and mixed it with air, storing energy for future generations. Stone was forged in the furnace of a long-ago star which — with the cosmic clap of a supernova — dispersed itself as stellar dust, the raw ingredient of our planet. These are the ancestors of our digital devices:

Mother Tree, Father Stone, Grandmother Star, Grandfather Time.

Our computers, then, are made of stardust and tree flesh. Their memories live on machines whose breath warms the sky. Our digital devices are ecological, our ecologies are growing digital.

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