by Bill Murray

We left last month’s column worried about getting tickets on a train across a swath of Africa’s midsection, from Dar es Salaam, Tanzania to Lusaka, Zambia. There’s a funny system for getting on that train. You can reserve tickets over the phone but you can’t buy them online.

You must come to the train station in person, Tanzanian Shillings in hand, and buy your tickets with cash. When we turned up the day before departure, the whole, massive, foreboding station was deserted except for a sprinkle of porters loitering outside for lack of business, and one man behind the ticket window.

We offered our $188 in cash in shillings. He offered a big smile, the fact that he had a son in Missouri, and four tickets, so that the two of us, my wife Mirja and I, claimed an entire four person compartment for our own.

There is a cliché about Africa, about the need to build in extra time for everything. It’s a cutesy, knowing, slightly smug expression of superiority among tourists when they learn it and use it for the first time; it is, in fairness, also true.

Welcome to the Tazara (TA for Tanzania, ZA for Zambia and RA for railroad) railroad. Its timetable led us to expect a forty two hour ride, but we stayed on that train for fifty seven hours and forty minutes, busting through a scheduled Sunday morning arrival time and instead arriving after midnight the next day.

Not that you’d have thought so at the start. Remarkably, even a touch triumphantly, the Tazara pulled out of Dar es Salaam station three minutes late at 3:53 on Friday afternoon. It didn’t take long for its true character to emerge, though; the Tazara was three hours late by its second stop. Read more »

Graduations

I have before me a list of extensions
without names. But it seems not to go on forever,
because of horizon which, with
the slickness of a blade, a knife of
limitation, slashes time in two

I’ve ticked-off the list through many graduations,
sometimes with honors, sometimes
smeared against a wall of dreams since I’m
a creature of their reckless persistence,
their humiliations

But that irresistible incision far off, though closer now,
still draws me regardless of my self-shaped limitations,
my turnings from what is true

Jim Culleny, 4/16/23

by Jonathan Kujawa

In the movies the mathematician is always a lone genius, possibly mad, and uninterested in socializing with other people. Or they are Jeff Goldblum — a category of its own. While it is true that doing mathematics involves a certain amount of thinking alone, I’ve frequently argued here at 3QD that math is a fundamentally social endeavor.

This weekend I was reminded again of this fundamental fact. Now that we are emerging from covid, in-person math conferences have returned in abundance. I am currently in Cincinnati attending one of the American Mathematical Society’s regional math conferences. It has been wonderful to hear many great talks about cutting edge research. The real treat, though, is the chance to see old friends and meet new people, especially the grad students and young researchers who’ve come into the field in the last few years.

In chats between talks, you learn about the problems people are pondering; their private shortcuts to how to think about certain topics; how their universities handle teaching, budgets, and post-covid life; and, of course, the latest professional gossip. It is nice to be reminded that you are part of a community of like-minded folks.

One of the tentpole events of the conference was the Einstein Public Lecture. They are held annually at one of the AMS meetings and were started to celebrate the one-hundredth anniversary of Albert Einstein’s annus mirabilis. In this case, the speaker was Nathaniel Whitaker, a University of Massachusetts, Amherst, professor. While the mathematical topic of his presentation was his work on finding approximate solutions and numerical estimates to the sorts of partial differential equations which arise in the study of fluid flows, the real story he wanted to tell was his journey from the segregated schools of 1950s Virginia to his role in the 2020s as a leader of a large research university [1]. Read more »

by Ethan Seavey

In the growing sector of the contemporary art world which focuses on environmental issues, participants in the art (artists, critics, and the general audience) disagree on the intention of each work of art: does it merit only aesthetic praise, or is it a successful work of climate activism? In my brief internship at Art of Change 21, a French nonprofit association at the intersection of contemporary art and the environment, I frequently encountered this dichotomy. At Art Paris 2022, the association hosted an exhibition centered around artists who deal with environmental themes. My goal is to contextualize some of the artworks present at this exhibition, based on critical theory as well as my own experiences.

When an artist depicts an environmental issue, they want to bring attention to it, and for many in the art world, this attention is enough to be considered powerful activism. In a study for the Norwegian University of Science and Technology, Laura Kim Sommer and Christian Andreas Klöckner collected qualitative date based on surveys and cognitive recognition information and determined that art engaging with environmental issues had strong emotional effects upon its audience. This study was conducted at the 2015 UN Climate Conference, for an exhibition of art pertaining to climate issues. (Art of Change 21 was born at this Climate Conference, and had no role in the display of these artworks; the association was present elsewhere in the conference, though, with similar projects.) Read more »

Zaneb Beams. Untitled, 2022.

Digital photograph.

With permission.

by Chris Horner

The illusion of rational autonomy

The world is full of people who think that they think for themselves. Free thinkers and sceptics, they imagine themselves as emancipated from imprisoning beliefs. Yet most of what they, and you, know comes not from direct experience or through figuring it out for oneself, but from unknown others. Take science, for instance. What do you think you actually know? That the moon affects the tides? Something about space-time continuum or the exciting stuff about quantum mechanics? Or maybe the research on viruses and vaccines? Chances are whatever you know you have taken on trust – even, or particularly, if you are a reader of popular science books. This also applies to most scientists, since they usually only know what is going on in their own field of research. The range of things we call ‘science’ is simply too vast for anyone to have knowledge in any other way.

We are confronted by a series of fields of research, experimentation and application:  complex and specialised fields that requires years of study and training to fully understand. As individuals, we cannot be experts in all scientific domains, which is why we typically rely on the knowledge and expertise of the scientific community,  composed of experts from various fields who have the necessary background knowledge, experience, and expertise to evaluate scientific theories and data accurately. Read more »

by Tim Sommers

One thing that Elon Musk and Bill Gates have in common, besides being two of the five richest people in the world, is that they both believe that there is a very serious risk that an AI more intelligent than them – and, so, more intelligent than you and I, obviously – will one day take over, or destroy, the world. This makes sense because in our society how smart you are is well-known to be the best predictor of how successful and powerful you will become. But, you may have noticed, it’s not only the richest people in the world that worry about an AI apocalypse. One of the “Godfathers of AI,” Geoff Hinton recently said “It’s not inconceivable” that AI will wipe out humanity. In a response linked to by 3 Quarks Daily, Gary Marcus, a neuroscientist and founder of a machine learning company, asked whether the advantages of AI were sufficient for us to accept a 1% chance of extinction. This question struck me as eerily familiar.

Do you remember who offered this advice? “Even if there’s a 1% chance of the unimaginable coming due, act as it is a certainty.”

That would be Dick Cheney as quoted by Ron Suskin in “The One Percent Doctrine.” Many regard this as the line of thinking that led to the Iraq invasion. If anything, that’s an insufficiently cynical interpretation of the motives behind an invasion that killed between three hundred thousand and a million people and found no weapons of mass destruction. But there is a lesson there. Besides the fact that “inconceivable” need not mean 1% – but might mean a one following a googolplex of zeroes [.0….01%] – trying to react to every one-percent probable threat may not be a good idea. Therapists have a word for this. It’s called “catastrophizing.” I know, I know, even if you are catastrophizing, we still might be on the brink of catastrophe. “The decline and fall of everything is our daily dread,” Saul Bellow said. So, let’s look at the basic story that AI doomsayers tell. Read more »

by Brooks Riley

by Robyn Repko Waller

AI has a proclivity for exaggeration. This hallucination is integral to its success and its danger.

Much digital ink has been spilled and computational resources consumed as of late in the too rapidly advancing capacities of AI.

Large language models like GPT-4 heralded as a welcome shortcut for email, writing, and coding. Worried discussion for the implications for pedagogical assessment — how to codify and detect AI plagiarism. Open-AI image generation to rival celebrated artists and photographers. And what of the convincing deep fakes?

The convenience of using AI to innovate and make efficient our social world and health, from Tiktok to medical diagnosis and treatment. Continued calls, though, for algorithmic fairness in the use of algorithmic decision-making in finance, government, health, security, and hiring.

Newfound friends, therapists, lovers, and enemies of an artificial nature. Both triumphant and terrified exclamations and warnings of sentient, genuinely intelligent AI. Serious widespread calls for a pause in development of these AI systems. And, in reply, reports that such exclamations and calls are overblown: Doesn’t intelligence require experience? Embodiment?

These are fascinating and important matters. Still, I don’t intend to add to the much-warranted shouting. Instead, I want to draw attention to a curious, yet serious, corollary of the use of such AI systems, the emergence of artificial or machine hallucinations. By such hallucinations, folks mean the phenomenon by which AI systems, especially those driven by machine learning, generate factual inaccuracies or create new misleading or irrelevant content. I will focus on one kind of hallucination, the inherent propensity of AI to exaggerate and skew. Read more »

by Brooks Riley

‘Wenn möglich, bitte wenden.’

That was the voice of the other woman in the car, ‘If possible, please turn around.’ She was nowhere to be seen in the BMW I was riding in sometime in the early aughts, but her voice was pleasant—neutral, polite, finely modulated and real.  She was the voice of the navigation system, a precursor of the chatbot—without the chat. You couldn’t talk back to her. All she knew about you was the destination you had typed into the system.

‘Wenn möglich, bitte wenden.’

She always said this when we missed a turn, or an exit. Since we hadn’t followed her suggestion the first time, she asked us again to turn around. There were reasons not to take her advice. If we were on the autobahn, turning around might be deadly. More often, we just wanted her to find a new route to our destination.

The silence after her second directive seemed excessive—long enough for us to get the impression that she, the ‘voice’, was sulking. In reality, the silence covered the period of time the navigation system needed to calculate a new route. But to ears that were attuned to silent treatments speaking volumes, it was as if Frau GPS was mightily miffed that we hadn’t turned around.

Recent encounters with the Bing chatbot have jogged my memory of that time of relative innocence, when a bot conveyed a message, nothing more. And yet, even that simple computational interaction generated a reflex anthropomorphic response, provoked by the use of language, or in the case of the pregnant silence, the prolonged absence of it. Read more »

My wife looking at the Dolomites from the Villanderer Alm in South Tyrol the day before yesterday.

by Eric Bies

Everyone is talking about artificial intelligence. This is understandable: AI in its current capacity, which we so little understand ourselves, alternately threatens dystopia and promises utopia. We are mostly asking questions. Crucially, we are not asking so much whether the risks outweigh the rewards. That is because the relationship between the first potential and the second is laughably skewed. Most of us are already striving to thrive; whether increasingly superintelligent AI can help us do that is questionable. Whether AI can kill all humans is not.

So laymen like me potter about and conceive, no longer of Kant’s end-in-itself, but of some increasingly possible end-to-it-all. No surprise, then, when notions of the parallel and the alternate grow more and more conspicuous in our cultural moment. We long for other science-fictional universes.

Happily, then, did the news of the FDA’s approval of one company’s proprietary blend of “cultured chicken cell material” greet my wonky eyes last month.

“Too much time and money has been poured into the research and development of plant-based meat,” I thought. “It’s time we focused our attention on meat-based meat.”

When I shared this milestone with my students—most of them high school freshmen—opinions were split. Like AI, lab-grown meat was quick to take on the Janus-faced contour of promise and threat. The regulatory thumbs-up to GOOD Meat’s synthetic chicken breast was, for some students, evidence of our steady march, aided by science, into a sustainable future. For other students, it was yet another chromium-plated creepy-crawly, an omen of more bad to come. Read more »

Trying to make Sense of Red
—A Tennessee Cleanup

Its janitors are sweeping up its sins—
senators are on the floor with whisks and
fine-toothed combs. They crawl and sift,
scooping, collecting photographs
of those they’ve lynched
they cram them into
rubbish bins

—before their kids get wind

they ban   their two-faced history,
they ban   before their children come to know,
they ban   before their jittering pot lid blows

—but

maybe    they skew and hack the rules
..  ………  to save kids from what history shows,
maybe    they obfuscate for mercy’s sake,
maybe.   before their children come to see and judge,
maybe.. .they’d rather have them shot in schools

Jim Culleny, 4/8/23

by Mindy Clegg

In their oft-cited classic examination of the modern mass media, Manufacturing Consent, Edward Herman and Noam Chomsky described modern American news media thusly: “The mass media serve as a system for communicating messages and symbols to the general populace. It is their function to amuse, entertain, and inform, and to inculcate individuals with the values, beliefs, and codes of behavior that will integrate them into the institutional structures of the larger society. In a world of concentrated wealth and major conflicts of class interest, to fulfill this role requires systematic propaganda.”¹ In other words, democratic states use privately-owned media as a means of social control. Private corporations own and operate media outlets and they work with the US government because the power of the state dovetailed with their own economic interests.

The groundwork for this state of affairs emerged out of intellectual discourse in the early days of mass media. In the wake of the first world war, prominent intellectuals like Walter Lippmann and Edward Bernays suggested a set of strategies for channeling democratic impulses expanding in the United States to better align with the wishes of the ruling classes.² Such analysis was and continues to be necessary, as many are unaware of the very real pitfalls of corporate media in democratic societie. These systems are now often globalized which shape our understanding of the past and present that we must understand in hopes of changing them. But we must also wonder if the singular focus on these systems of control lead to the feelings of hopelessness that many of us feel about our institutions these days. As much as describing what dominates us feels cathartic, focusing only on the systems of control and not on resistance makes the problem seem insurmountable. I argue that we need to look for the cracks as much as describe the problem posed by corporate medi. Understanding the democratic alternatives within and outside of the mainstream production of popular culture can help us to see these cracks. Read more »

Sughra Raza. NYC, April 2023.

Digital photograph.

by David J. Lobina

The hype surrounding Large Language Models remains unbearable when it comes to the study of human cognition, no matter what I write in this Column about the issue – doesn’t everyone read my posts? I certainly do sometimes.

Indeed, this is my fourth, successive post on the topic, having already made the points that Machine/Deep Learning approaches to Artificial Intelligence cannot be smart or sentient, that such approaches are not accounts of cognition anyway, and that when put to the test, LLMs don’t actually behave like human beings at all (where? In order: here, here, and here).[i]

But, again, no matter. Some of the overall coverage on LLMs can certainly be ludicrous (a covenant so that future, sentient computer programs have their rights protected?), and even delirious (let’s treat AI chatbots as we treat people, with radical love?), and this is without considering what some tech charlatans and politicians have said about these models. More to the point here, two recent articles from some cognitive scientists offer quite the bloated view regarding what LLMs can do and contribute to the study of language, and a discussion of where these scholars have gone wrong will, hopefully, make me sleep better at night.

One Pablo Contreras Kallens and two colleagues have it that LLMs constitute an existence proof (their choice of words) that the ability to produce grammatical language can be learned from exposure to data alone, without the need to postulate language-specific processes or even representations, with clear repercussions for cognitive science.[ii]

And one Steven Piantadosi, in a wide-ranging (and widely raging) book chapter, claims that LLMs refute Chomsky’s approach to language, and in toto no less, given that LLMs are bona fide (his choice of words) theories of language; these models have developed sui generis representations of key linguistic structures and dependencies, thereby capturing the basic dynamics of human language and constituting a clear victory for statistical learning in so doing (Contreras Kallens and co. get a tip of the hat here), and in any case Chomskyan accounts of language are not precise or formal enough, cannot be integrated with other fields of cognitive science, have not been empirically tested, and moreover…(oh, piantala).[iii] Read more »

by John Allen Paulos

Despite many people’s apocalyptic response to ChatGPT, a great deal of caution and skepticism is in order. Some of it is philosophical, some of it practical and social. Let me begin with the former.

Whatever its usefulness, we naturally wonder whether CharGPT and its near relatives understand language and, more generally, whether they demonstrate real intelligence. The Chinese Room thought experiment, a classic argument put forward by philosopher John Searle in 1980, somewhat controversially maintains that the answer is No. It is a refinement of arguments of this sort that go back to Leibniz.

In his presentation of the argument (very roughly sketched here), Searle first assumes that research in artificial intelligence has, contrary to fact, already managed to design a computer program that seems to understand Chinese. Specifically, the computer responds to inputs of Chinese characters by following the program’s humongous set of detailed instructions to generate outputs of other Chinese characters. It’s assumed that the program is so good at producing appropriate responses that even Chinese speakers find it to be indistinguishable from a human Chinese speaker. In other words, the computer program passes the so-called Turing test, but does even it really understand Chinese?

The next step in Searle’s argument asks us to imagine a man completely innocent of the Chinese language in a closed room, perhaps sitting behind a large desk in it. He is supplied with an English language version of the same elaborate set of rules and protocols the computer program itself uses for correctly manipulating Chinese characters to answer questions put to it. Moreover, the man is directed to use these rules and protocols to respond to questions written in Chinese that are submitted to him through a mail slot in in the wall of the room. Someone outside the room would likely be quite impressed with the man’s responses to the questions posed to him and what seems to be the man’s understanding of Chinese. Yet all the man is doing is blindly following the same rules that govern the way the sequences of symbols in the questions should be responded to in order to yield answers.  Clearly the man could process the Chinese questions and produce answers to them without any understanding any of the Chinese writing. Finally, Searle drops the mic by maintaining that both the man and the computer itself have no knowledge or understanding of Chinese. Read more »