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Posts Tagged ‘artificial intelligence

“The intelligence of the universe is social”*…

From the series Neural Zoo by Sofia Crespo

Recently, (Roughly) Daily looked at AI and our (that’s to say, humans’) possible relationships to it. In a consideration of Jame Bridle‘s new book, Ways of Being, Doug Bierend widens the iris, considering our relationship not only to intelligences we might create but also to those with which we already co-habit…

It’s lonely at the top, but it doesn’t have to be. We humans tend to see ourselves as the anointed objects of evolution, our intelligence representing the leading edge of unlikely order cultivated amid an entropic universe. While there is no way to determine any purpose or intention behind the processes that produced us, let alone where they will or should lead, that hasn’t stopped some from making assertions. 

For example, consider the school of thought called longtermism, explored by Phil Torres in this essay for Aeon. Longtermism — a worldview held, as Torres notes, by some highly influential people including Elon Musk, Peter Thiel, tech entrepreneur Jaan Tallinn, and Jason Matheny, President Biden’s deputy assistant for technology and national security — essentially sees the prime directive of Homo sapiens as one of maximizing the “potential” of our species. That potential — often defined along such utilitarian lines as maximizing the population, distribution, longevity, and comfort that future humans could achieve over the coming millennia — is what longtermers say should drive the decisions we make today. Its most extreme version represents a kind of interstellar manifest destiny, human exceptionalism on the vastest possible scale. The stars are mere substrate for the extension and preservation of our species’ putatively unique gifts. Some fondly imagine our distant descendants cast throughout the universe in womb-like symbiosis with machines, ensconced in virtual environments enjoying perpetual states of bliss —The Matrix as utopia. 

Longtermist philosophy also overlaps with the “transhumanist” line of thought, articulated by figures such as philosopher Nick Bostrom, who describes human nature as incomplete, “a half-baked beginning that we can learn to remold in desirable ways.” Here, humanity as currently or historically constituted isn’t an end so much as a means of realizing some far greater fate. Transhumanism espouses the possibility of slipping the surly bonds of our limited brains and bodies to become “more than human,” in a sense reminiscent of fictional android builder Eldon Tyrell in Blade Runner: “Commerce is our goal,” Tyrell boasts. “‘More human than human’ is our motto.” Rather than celebrating and deepening our role within the world that produced us, these outlooks seek to exaggerate and consummate a centuries-long process of separation historically enabled by the paired forces of technology and capital. 

But this is not the only possible conception of the more than human. In their excellent new book Ways of Being, James Bridle also invokes the “more than human,” not as an effort to exceed our own limitations through various forms of enhancement but as a mega-category that collects within it essentially everything, from microbes and plants to water and stone, even machines. It is a grouping so vast and diverse as to be indefinable, which is part of Bridle’s point: The category disappears, and the interactions within it are what matters. More-than-human, in this usage, dismisses human exceptionalism in favor of recognizing the ecological nature of our existence, the co-construction of our lives, futures, and minds with the world itself. 

From this point of view, human intelligence is just one form of a more universal phenomenon, an emergent “flowering” found all throughout the evolutionary tree. It is among the tangled bramble of all life that our intelligence becomes intelligible, a gestalt rather than a particular trait. As Bridle writes, “intelligence is not something which exists, but something one does. It is active, interpersonal and generative, and it manifests when we think and act.” In Bridle’s telling, mind and meaning alike exist by way of relationship with everything else in the world, living or not. Accepting this, it makes little sense to elevate human agency and priorities above all others. If our minds are exceptional, it is still only in terms of their relationship to everything else that acts within the world. That is, our minds, like our bodies, aren’t just ours; they are contingent on everything else, which would suggest that the path forward should involve moving with the wider world rather than attempting to escape or surpass it.

This way of thinking borrows heavily from Indigenous concepts and cosmologies. It decenters human perspective and priorities, instead setting them within an infinite concatenation of agents engaged in the collective project of existence. No one viewpoint is more favored than another, not even of the biological over the mineral or mechanical. It is an invitation to engage with the “more-than-human” world not as though it consisted of objects but rather fellow subjects. This would cut against the impulse to enclose and conquer nature, which has been reified by our very study of it….

Technology often presupposes human domination, but it could instead reflect our ecological dependence: “Entangled Intelligence,” from @DougBierend in @_reallifemag (via @inevernu and @sentiers). Eminently worth reading in full.

* Marcus Aurelius, The Meditations


As we welcome fellow travelers, we might recall that this date in 1752 was the final day of use of the Julian calendar in Great Britain, Ireland, and the British colonies, including those on the East coast of America. Eleven days were skipped to sync to the Gregorian calendar, which was designed to realign the calendar with equinoxes. Hence the following day was September 14. (Most of Europe had shifted, by Papal decree, to the Gregorian calendar in the 16th century; Russia and China made the move in the 20th century.)


Written by (Roughly) Daily

September 2, 2022 at 1:00 am

“It was orderly, like the universe. It had logic. It was dependable. Using it allowed a kind of moral uplift, as one’s own chaos was also brought under control.”*…

(Roughly) Daily has looked before at the history of the filing cabinet, rooted in the work of Craig Robertson (@craig2robertson). He has deepened his research and published a new book, The Filing Cabinet: A Vertical History of Information. An Xiao Mina offers an appreciation– and a consideration of one of the central questions it raises: can emergent knowledge coexist with an internet that privileges the kind “certainty” that’s implicit in the filing paradigm that was born with the filing cabinet and that informs our “knowledge systems” today…

… The 20th century saw an emergent information paradigm shaped by corporate capitalism, which emphasized maximizing profit and minimizing the time workers spent on tasks. Offices once kept their information in books—think Ebenezer Scrooge with his quill pen, updating his thick ledger on Christmas. The filing cabinet changed all that, encouraging what Robertson calls “granular certainty,” or “the drive to break more and more of life and its everyday routines into discrete, observable, and manageable parts.” This represented an important conceptualization: Information became a practical unit of knowledge that could be standardized, classified, and effortlessly stored and retrieved.

Take medical records, which require multiple layers of organization to support routine hospital business. “At the Bryn Mawr Hospital,” Robertson writes, “six different card files provided access to patient information: an alphabetical file of admission cards for discharged patients, an alphabetical file for the accident ward, a file to record all operations, a disease file, a diagnostic file, and a doctors’ file that recorded the number of patients each physician referred to the hospital.” The underlying logic of this system was that the storage of medical records didn’t just keep them safe; it made sure that those records could be accessed easily.

Robertson’s deep focus on the filing cabinet grounds the book in history and not historical analogy. He touches very little on Big Data and indexing and instead dives into the materiality of the filing cabinet and the principles of information management that guided its evolution. But students of technology and information studies will immediately see this history shaping our world today…

[And] if the filing cabinet, as a tool of business and capital, guides how we access digital information today, its legacy of certainty overshadows the messiness intrinsic to acquiring knowledge—the sort that requires reflection, contextualization, and good-faith debate. Ask the internet difficult questions with complex answers—questions of philosophy, political science, aesthetics, perception—and you’ll get responses using the same neat little index cards with summaries of findings. What makes for an ethical way of life? What is the best English-language translation of the poetry of Borges? What are the long-term effects of social inequalities, and how do we resolve them? Is it Yanny or Laurel?

Information collection and distribution today tends to follow the rigidity of cabinet logic to its natural extreme, but that bias leaves unattended more complex puzzles. The human condition inherently demands a degree of comfort with uncertainty and ambiguity, as we carefully balance incomplete and conflicting data points, competing value systems, and intricate frameworks to arrive at some form of knowing. In that sense, the filing cabinet, despite its deep roots in our contemporary information architecture, is just one step in our epistemological journey, not its end…

A captivating new history helps us see a humble appliance’s sweeping influence on modern life: “The Logic of the Filing Cabinet Is Everywhere.”

* Jeanette Winterson, Why Be Happy When You Could Be Normal?


As we store and retrieve, we might recall that it was on this date in 19955 that the term “artificial intelligence” was coined in a proposal for a “2 month, 10 man study of artificial intelligence” submitted by John McCarthy (Dartmouth College), Marvin Minsky (Harvard University), Nathaniel Rochester (IBM), and Claude Shannon (Bell Telephone Laboratories). The workshop, which took place at Dartmouth a year later, in July and August 1956, is generally recognized as the official birth date of the new field. 

Dartmouth Conference attendees: Marvin Minsky, Claude Shannon, Ray Solomonoff and other scientists at the Dartmouth Summer Research Project on Artificial Intelligence (Photo: Margaret Minsky)


“It takes something more than intelligence to act intelligently”*…

AI isn’t human, but that doesn’t mean, Nathan Gardels argues (citing three recent essays in Noema, the magazine that he edits), that it cannot be intelligent…

As the authors point out, “the dominant technique in contemporary AI is deep learning (DL) neural networks, massive self-learning algorithms which excel at discerning and utilizing patterns in data.”

Critics of this approach argue that its “insurmountable wall” is “symbolic reasoning, the capacity to manipulate symbols in the ways familiar from algebra or logic. As we learned as children, solving math problems involves a step-by-step manipulation of symbols according to strict rules (e.g., multiply the furthest right column, carry the extra value to the column to the left, etc.).”

Such reasoning would enable logical inferences that can apply what has been learned to unprogrammed contingencies, thus “completing patterns” by connecting the dots. LeCun and Browning argue that, as with the evolution of the human mind itself, in time and with manifold experiences, this ability may emerge as well from the neural networks of intelligent machines.

“Contemporary large language models — such as GPT-3 and LaMDA — show the potential of this approach,” they contend. “They are capable of impressive abilities to manipulate symbols, displaying some level of common-sense reasoning, compositionality, multilingual competency, some logical and mathematical abilities, and even creepy capacities to mimic the dead. If you’re inclined to take symbolic reasoning as coming in degrees, this is incredibly exciting.”

The philosopher Charles Taylor associates the breakthroughs of consciousness in that era with the arrival of written language. In his view, access to the stored memories of this first cloud technology enabled the interiority of sustained reflection from which symbolic competencies evolved.

This “transcendence” beyond oral narrative myth narrowly grounded in one’s own immediate circumstance and experience gave rise to what the sociologist Robert Bellah called “theoretic culture” — a mental organization of the world at large into the abstraction of symbols. The universalization of abstraction, in turn and over a long period of time, enabled the emergence of systems of thought ranging from monotheistic religions to the scientific reasoning of the Enlightenment.

Not unlike the transition from oral to written culture, might AI be the midwife to the next step of evolution? As has been written in this column before, we have only become aware of climate change through planetary computation that abstractly models the Earthly organism beyond what any of us could conceive out of our own un-encompassing knowledge or direct experience.

For Bratton and Agüera y Arcas, it comes down in the end to language as the “cognitive infrastructure” that can comprehend patterns, referential context and the relationality among them when facing novel events.

“There are already many kinds of languages. There are internal languages that may be unrelated to external communication. There are bird songs, musical scores and mathematical notation, none of which have the same kinds of correspondences to real-world referents,” they observe.

As an “executable” translation of human language, code does not produce the same kind of intelligence that emerges from human consciousness, but is intelligence nonetheless. What is most likely to emerge in their view is not “artificial” intelligence when machines become more human, but “synthetic” intelligence, which fuses both.

As AI further develops through human prompt or a capacity to guide its own evolution by acquiring a sense of itself in the world, what is clear is that it is well on the way to taking its place alongside, perhaps conjoining and becoming synthesized with, other intelligences, from homo sapiens to insects to forests to the planetary organism itself…

AI takes its place among and may conjoin with other multiple intelligences: “Cognizant Machines: A What Is Not A Who.” Eminentl worth reading in full both the linked essay and the articles referenced in it.

* Dostoyevsky, Crime and Punishment


As we make room for company, we might recall that it was on this date in 1911 that a telegraph operator in the 7th floor of The New York Times headquarters in Times Square sent a message– “This message sent around the world”– that left at 7:00p, traveled over 28,000 miles, and was relayed by 16 different operators. It arrived back at the Times only 16.5 minutes later.

The “around the world telegraphy” record had been set in 1903, when President Roosevelt celebrated the completion of the Commercial Pacific Cable by sending the first round-the-world message in just 9 minutes. But that message had been given priority status; the Times wanted to see how long a regular message would take — and what route it would follow.

The building from which the message originated is now called One Times Square and is best known as the site of the New Year’s Eve ball drop.


Written by (Roughly) Daily

August 20, 2022 at 1:00 am

“O brave new world, that has such people in ‘t!”*…

The estimable Steven Johnson suggests that the creation of Disney’s masterpiece, Snow White, gives us a preview of what may be coming with AI algorithms sophisticated enough to pass for sentient beings…

… You can make the argument that the single most dramatic acceleration point in the history of illusion occurred between the years of 1928 and 1937, the years between the release of Steamboat Willie [here], Disney’s breakthrough sound cartoon introducing Mickey Mouse, and the completion of his masterpiece, Snow White, the first long-form animated film in history [here— actually the first full-length animated feature produced in the U.S; the first produced anywhere in color]. It is hard to think of another stretch where the formal possibilities of an artistic medium expanded in such a dramatic fashion, in such a short amount of time.

[There follows an fascinating history of the Disney Studios technical innovations that made Snow White possible, and an account of the film;’s remarkable premiere…]

In just nine years, Disney and his team had transformed a quaint illusion—the dancing mouse is whistling!—into an expressive form so vivid and realistic that it could bring people to tears. Disney and his team had created the ultimate illusion: fictional characters created by hand, etched onto celluloid, and projected at twenty-four frames per second, that were somehow so believably human that it was almost impossible not to feel empathy for them.

Those weeping spectators at the Snow White premiere signaled a fundamental change in the relationship between human beings and the illusions concocted to amuse them. Complexity theorists have a term for this kind of change in physical systems: phase transitions. Alter one property of a system—lowering the temperature of a cloud of steam, for instance—and for a while the changes are linear: the steam gets steadily cooler. But then, at a certain threshold point, a fundamental shift happens: below 212 degrees Fahrenheit, the gas becomes liquid water. That moment marks the phase transition: not just cooler steam, but something altogether different.

It is possible—maybe even likely—that a further twist awaits us. When Charles Babbage encountered an automaton of a ballerina as a child in the early 1800s, the “irresistible eyes” of the mechanism convinced him that there was something lifelike in the machine.  Those robotic facial expressions would seem laughable to a modern viewer, but animatronics has made a great deal of progress since then. There may well be a comparable threshold in simulated emotion—via robotics or digital animation, or even the text chat of an AI like LaMDA—that makes it near impossible for humans not to form emotional bonds with a simulated being. We knew the dwarfs in Snow White were not real, but we couldn’t keep ourselves from weeping for their lost princess in sympathy with them. Imagine a world populated by machines or digital simulations that fill our lives with comparable illusion, only this time the virtual beings are not following a storyboard sketched out in Disney’s studios, but instead responding to the twists and turns and unmet emotional needs of our own lives. (The brilliant Spike Jonze film Her imagined this scenario using only a voice.) There is likely to be the equivalent of a Turing Test for artificial emotional intelligence: a machine real enough to elicit an emotional attachment. It may well be that the first simulated intelligence to trigger that connection will be some kind of voice-only assistant, a descendant of software like Alexa or Siri—only these assistants will have such fluid conversational skills and growing knowledge of our own individual needs and habits that we will find ourselves compelled to think of them as more than machines, just as we were compelled to think of those first movie stars as more than just flickering lights on a fabric screen. Once we pass that threshold, a bizarre new world may open up, a world where our lives are accompanied by simulated friends…

Are we in for a phase-shift in our understanding of companionship? “Natural Magic,” from @stevenbjohnson, adapted from his book Wonderland: How Play Made The Modern World.

And for a different, but aposite perspective, from the ever-illuminating L. M. Sacasas (@LMSacasas), see “LaMDA, Lemoine, and the Allures of Digital Re-enchantment.”

* Shakespeare, The Tempest


As we rethink relationships, we might recall that it was on this date in 2007 that the original iPhone was introduced. Generally downplayed by traditional technology pundits after its announcement six months earlier, the iPhone was greeted by long lines of buyers around the country on that first day. Quickly becoming a phenomenon, one million iPhones were sold in only 74 days. Since those early days, the ensuing iPhone models have continued to set sales records and have radically changed not only the smartphone and technology industries, but the world in which they operate as well.

The original iPhone


“Artificial intelligence is growing up fast”*…

A simple prototype system sidesteps the computing bottleneck in tuning– teaching– artificial intelligence algorithms…

A simple electrical circuit [pictured above] has learned to recognize flowers based on their petal size. That may seem trivial compared with artificial intelligence (AI) systems that recognize faces in a crowd, transcribe spoken words into text, and perform other astounding feats. However, the tiny circuit outshines conventional machine learning systems in one key way: It teaches itself without any help from a computer—akin to a living brain. The result demonstrates one way to avoid the massive amount of computation typically required to tune an AI system, an issue that could become more of a roadblock as such programs grow increasingly complex.

“It’s a proof of principle,” says Samuel Dillavou, a physicist at the University of Pennsylvania who presented the work here this week at the annual March meeting of the American Physical Society. “We are learning something about learning.”…

More at “Simple electrical circuit learns on its own—with no help from a computer, from @ScienceMagazine.

* Diane Ackerman


As we brace ourselves (and lest we doubt the big things can grow from humble beginnings like these), we might recall that it was on this date in 1959 that Texas Instruments (TI) demonstrated the first working integrated circuit (IC), which had been invented by Jack Kilby. Kilby created the device to prove that resistors and capacitors could exist on the same piece of semiconductor material. His circuit consisted of a sliver of germanium with five components linked by wires. It was Fairchild’s Robert Noyce, however, who filed for a patent within months of Kilby and who made the IC a commercially-viable technology. Both men are credited as co-inventors of the IC. (Kilby won the Nobel Prize for his work in 2000; Noyce, who died in 1990, did not share.)

Kilby and his first IC (source)
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