Natural intelligence Revisited: The Five-Fold Way, A Working Paper

New working paper. Title above, links, abstract, contents, and introduction below:

Academia.edu: https://www.academia.edu/165530520/Natural_intelligence_Revisited_The_Five_Fold_Way_A_Working_Paper
SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6529398
ResearchGate: https://www.researchgate.net/publication/403545810_Natural_intelligence_Revisited_The_Five-Fold_Way_A_Working_Paper

Abstract: In 1988 David Hays and I published an article entitled, “Principles and Development of Natural Intelligence.” The principles were computational: 1) modal, 2) diagonalization, 3) decision, 4) finitization, and 5) indexing. We made our argument in terms of the principles themselves along with behavioral, neuroanatomical, ontogenetic and phylogenetic evidence. The literature in all those fields has changed enormously in the four decades since we finished writing. To get a read on how our computational proposals have fared, I asked ChatGPT 5.2 to evaluate it against the current literature. Its verdict: the “empirical specifics have aged unevenly but [the] central agenda has held up surprisingly well.” This article presents the five principles, in brief, followed by ChatGPT’s full evaluation. Also, I have asked ChatGPT to evaluate a section on control structure, “Vehicularization,” that we cut from the original argument. Verdict: “vehicularization points toward a more complete account of natural intelligence—one in which cognition is understood as coordinated navigation across multiple, nested domains.”

CONTENTS

Introduction: Constraining Theories and Models 2
The Five Principles of Natural Intelligence 4
Revisiting The Principles and Development of Natural Intelligence (1988) 6
Vehicularization 11

Introduction: Constraining Theories and Models

Sometime in 1985 David Hays and I decided it was time to set forth our views on the nature of, well, of natural intelligence. First, however, we had to discover what those views were. We sat down to a table in my parents’ kitchen and made a list of the various things we wanted to include in this article, experimental findings, observations, models, mathematical ideas, and so forth, from psychology, neuroscience, linguistics, evolutionary biology, and computing. We just wrote them down in no particular order, probably on unlined paper. When we’d accumulated about 50 or so items we decided to gather them into a small number of groups of items that seemed to belong together. We arrived at five groups.

Just how we proceeded from that point I don’t recall. Perhaps we sat around discussing the various groups and came up with a principle for each group. Maybe we had to do some writing first. I don’t recall. But however we actually proceeded, we end with an article we called, “Principles and Development of Natural Intelligence.” We intended “natural” to contrast with “artificial” but didn’t say that anywhere in the article. When we’d finished a draft, days or weeks later, Hays said that it felt like fundamental work; he used the term “bedrock.” I agreed. It took three years to get it published, in a now defunct interdisciplinary journal, The Journal of Social and Biological Structures.

I’ve included the abstract of that article, along with a bit of the introduction, below, as the first part of this document: “Five Principles of Natural Intelligence.” That should give you an idea of the framework without all the expository elaboration, argumentation, and support.

ChatGPT reviews

That was four decades ago. I have continued to like what we did. But has any of it held up? How could it? By now the literature we referenced was 40 years out of date? And, yet, it wasn’t about that literature, it was about how we put it together. Is there anything left of that framework?

About a week ago I asked ChatGPT 5.2 to evaluate it. Here’s the prompt I gave it:

I want you to evaluate a paper that David Hays and I published back in 1988: The Principles and Development of Natural Intelligence. Give me a third-party assessment from the standpoint of what we now know, not a summary and not a defensive reconstruction. Be explicit about where it now looks prescient, where it looks historically bounded, and where it still poses unresolved challenges.

Here’s the first line of ChatGPT’s conclusion:

As of 2026, I would not describe the paper as a correct theory of mind. I would describe it as an ambitious synthetic manifesto whose empirical specifics have aged unevenly but whose central agenda has held up surprisingly well.

I’ll take it. Could I take issue with some of ChatGPT’s criticisms? Sure. But that assessment pinpoints the single most important facet of the essay, its synthetic nature. To push back on ChatGPT’s reservations would blunt that point.

After making various comments on an ad hoc basis, ChatGPT offered to write a “more formal review-essay.” I’ve included that as the second part of this document: “Revisiting Principles and Development of Natural Intelligence (1988).” There’s more.

The article we had submitted was long. The editors asked us to cut what we could, but made no particular suggestions. Our single largest cut was a section on vehicularization – that’s what we called it. It was about control. While it was about the same general line of thinking, it didn’t seem to fit. The bulk of the article was about the five principles and how the developed, both phylogenetically and ontogenetically (in humans). Vehicularization was about how they operated in concert. I have included that as a third section followed by comments by ChatGPT as the fourth and final section.

The Five-Fold Way

Let’s return to ChatGPT’s characterization of the original article as a “synthetic manifesto.” From its conclusion:

It is best understood as an architectural proposal about the structure of intelligence. Many of its mechanistic claims have aged poorly, particularly its neuroanatomical simplifications and evolutionary staging. Yet several of its central insights—heterogeneous cognitive regimes, the integration of regulation and cognition, the interaction between holistic and symbolic processing, and the role of language in cognitive control—remain highly relevant.

Though we didn’t use such phrases when we wrote the article, that’s certainly what Hays and I thought we were doing.

The diagram to the left indicates the range of material we brought to bear in our thinking about natural intelligence. The labels on the vertices of the pentangle are from my 1978 Ph. D. thesis in the English Department at SUNY Buffalo, “Cognitive Science and Literary Theory.” There I somewhat idiosyncratically defined cognitive science as investigating a five-way correspondence between behavior, computation, computational geometry (neuroanatomy), phylogeny, and ontogeny. That dissertation was mostly about behavior, in the form of literary texts, and computation, in the form of cognitive networks semantics, though touched on the others here and there. But “Principles and Development of Natural Intelligence” covered all five. The principles themselves were computational in nature and we made our primary arguments in terms of their ability to account for behavior, but we also suggested which brain regions supported them and related them to the phylogeny of animal behavior and the ontogeny of human development.

By the usual standards of the academy, that range was wide, crazy wide. We certainly weren’t expert across that range; no one could be. However, when I look back in retrospect, it is clear that we weren’t attempting some grand synthesis over that range. We were doing something quite different, something that was and remains fundamentally conservative. We had some high-level ideas about the computational structure of the mind and we wanted to place constraints on those ideas by expanding the range of evidence that could be brought to bear on them. While it is necessary that those ideas account for observed behavior, that alone is not sufficient. The model implied by those ideas must be implemented somewhere in the brain and must be consistent with developmental evidence both from phylogeny, our evolutionary history, and ontogeny, child development. THAT was the central agenda that, in ChatGPT’s estimation, has held up well.

This is what happens when an open-ended research project is mis-perceived as commercial R&D

Nadella paid $650 million to acquihire Mustafa Suleyman and 70 Inflection employees in March 2024. The job: make Copilot the AI product that justifies Microsoft’s infrastructure bet. Two years later, Suleyman no longer runs Copilot.

The corporate framing is generous. “Freed up… https://t.co/nGo4DTa2Tl pic.twitter.com/W3I5PxgfFp

— Aakash Gupta (@aakashgupta) March 19, 2026

Sociogenomnics, is it just another spin of the nature/nurture wheel, or will it (be allowed to) evolve into something genuinely new?

Dalton Conley, A New Scientific Field Is Recasting Who We Are and How We Got That Way, NYTimes, 13 March 2025.

Since Sir Francis Galton coined the phrase “nature versus nurture” 150 years ago, the debate about what makes us who we are has dominated the human sciences.

Do genes determine our destiny, as the hereditarians would say? Or do we enter the world as blank slates, formed only by what we encounter in our homes and beyond? What started as an intellectual debate quickly expanded to whatever anyone wanted it to mean, invoked in arguments about everything from free will to race to inequality to whether public policy can, or should, level the playing field.

Today, however, a new realm of science is poised to upend the debate — not by declaring victory for one side or the other, nor even by calling a tie, but rather by revealing they were never in opposition in the first place. Through this new vantage, nature and nurture are not even entirely distinguishable, because genes and environment don’t operate in isolation; they influence each other and to a very real degree even create each other.

The new field is called sociogenomics, a fusion of behavioral science and genetics that I have been closely involved with for over a decade. Though the field is still in its infancy, its philosophical implications are staggering. It has the potential to rewrite a great deal of what we think we know about who we are and how we got that way. For all the talk of someday engineering our chromosomes and the science-fiction fantasy of designer babies flooding our preschools, this is the real paradigm shift, and it’s already underway.

Genes, it turns out, don’t affect who we become just on their own, inside our bodies — they work, in part, by shaping the environments we seek out or engender.

Picture a kid who is born with two working copies of what’s known as the sprinter’s gene, ACTN3. By elementary school she might be winning every game of tag, every race, and be chosen first whenever sides are drawn up. You could see how parents and coaches might encourage a kid like that to join an organized sports team and how she would be likely to receive positive feedback for her performance on it, which in turn might motivate her to train harder. By high school she makes varsity track and soccer, and the more she excels, the more coaching and training is made available to her.

Of course, any number of factors might cause her to quit sports — an injury, say, or a toxic team environment. But if she keeps at it, her starting position on a big college team won’t be the result of just her genes or her hard work. It will also be the result of how her genes shaped her environment, influencing the people and opportunities she encountered, and how her environment shaped the way and the degree to which her genes expressed themselves.

It’s a continuous feedback loop, in which neither nature nor nurture is a fixed entity.

Later:

The part of this research that really blows me away is the realization that our environment is, in part, made up of the genes of the people around us. Our friends’, our partners’, even our peers’ genes all influence us. Preliminary research that I was involved in suggests that your spouse’s genes influence your likelihood of depression almost a third as much as your own genes do. Meanwhile, research I helped conduct shows that the presence of a few genetically predisposed smokers in a high school appears to cause smoking rates to spike for an entire grade — even among those students who didn’t personally know those nicotine-prone classmates — spreading like a genetically sparked wildfire through the social network.

There’s much more at the link.

But I guess I’m going to declare myself skeptical, mostly on general principle. What’s the principle? Mostly that the academy is organized on intellectual boundaries laid down in the 19th century and it has so far resisted changing them in any fundamental way. Oh, in the last half century we’ve seen interdisciplinary-this and intedisciplinary-that and all sort of conferences and centers, lots and lots of interdisciplinary. But those ancient boundaries remain, which is why interdisciplinarity keeps cropping up as presenting itself as new.

What do I think about nature/nurture? Think of chess. On the one hand we have the rules of the game, the size of the board, the different pieces and their moves, and a couple other rules. That’s nature, that’s biology. In order to play chess at all, you have to know and abide by those rules. But to play chess well, that’s something else. For that you need to know tactics and strategies that have been build over centuries. That’s nurture, that’s society and culture.

Now, as that’s a metaphor, and only a metaphor, of course it fits this “new” scientific program, this new paradigm, this “sociogenomics, a fusion of behavioral science and genetics.” But how will this program unfold, develop? That is very much dependent on the surrounding intellectual environment. That’s what gives me pause.

Bipedalism, Hominin Fetuses, and Musical and Linguistic Evolution

Matz Larsson and Dean Falk, Direct Effects of Bipedalism on Early Hominin Fetuses Stimulated Later Musical and Linguistic Evolution, Current Anthropology, Published online February 21, 2025.

Abstract

We hypothesize that auditory and motor entrainment evolved in early hominin fetuses in direct response to their mothers’ bipedal footsteps and, later, contributed to the evolution of music and language via two related processes. First, selection for bipedalism transformed feet from grasping into weight-bearing organs, which negatively affected infants’ ability to cling to their mothers, provoking the emergence of novel affective vocal exchanges between mothers and infants that became building blocks for the emergence of motherese. Second, the derived ability to entrain movements to sound was incorporated during the prehistoric emergence of wide-ranging rhythmic behaviors such as synchronized chanting of nonlexical vocables and coordinated rhythmic clapping and stomping, which became instrumental during the more recent evolution of music. Like the derived ability to keep beat with rhythmic sounds, nascent motherese entailed entrainment of motor behavior (the physical production of pitch, timing, and vocalization rate) with external sources of sound (conversational utterances). If motherese was a precursor for language evolution, as many believe, music and language share phylogenetically derived substrates for auditory and motor entrainment that stemmed directly from bipedalism. If so, bipedalism was more important for serendipitously sculpting advanced cognition in our prehistoric ancestors than previously believed.

Nous émettons l’hypothèse que l’entraînement auditif/moteur a évolué chez les fœtus des premiers hominines en réponse directe aux pas bipèdes de leurs mères, et qu’il a ensuite contribué à l’évolution de la musique et du langage via deux processus connexes. Premièrement, la sélection en faveur de la bipédie a transformé les pieds en organes de soutien plutôt que des organes de préhension, ce qui a eu un impact négatif sur la capacité des nourrissons à s’accrocher à leurs mères, provoquant ainsi l’émergence d’échanges vocaux affectifs novateurs entre les mères et les nourrissons, qui sont devenus des éléments constitutifs de l’émergence du mamanais (motherese, en anglais). Deuxièmement, la capacité dérivée à synchroniser les mouvements avec le son a été intégrée lors de l’émergence préhistorique de comportements rythmiques variés, tels que le chant synchronisé de vocables non lexicaux et le battement de mains et de pieds coordonné, qui sont devenus des éléments essentiels durant l’évolution plus récente de la musique. Tout comme la capacité dérivée à suivre le rythme des sons rythmiques, le mamanais naissant impliquait l’entraînement du comportement moteur (la production physique de la hauteur, du timing et du taux de vocalisation) avec des sources sonores externes (les énonciations conversationnelles). Si le mamanais était un précurseur de l’évolution du langage, comme le pensent de nombreux chercheurs, la musique et le langage partagent alors des substrats phylogénétiquement dérivés pour l’entraînement auditif/moteur qui découle directement de la bipédie. Si tel est le cas, la bipédie aurait été plus importante pour sculpter de manière fortuite la cognition avancée de nos ancêtres préhistoriques que l’on croyait auparavant.

Wir gehen davon aus, dass sich die auditorische/motorische Synchronisation (Entrainment) bei frühen homininen Föten als direkte Reaktion auf den zweibeinigen Gang ihrer Mütter entwickelte und später über zwei verwandte Prozesse zur Entwicklung von Musik und Sprache beitrug. Erstens verwandelte die Selektion für die Zweibeinigkeit die Füße von Greiforganen in tragende Organe, was sich negativ auf die Fähigkeit der Säuglinge auswirkte, sich an ihre Mütter zu klammern und was zur Entstehung neuartiger affektiver Stimmaustausche zwischen Müttern und Säuglingen führte, die zu Bausteinen für die Entstehung der Motherese (Mutter-Baby-Dialog) wurden. Zweitens wurde die entwickelte Fähigkeit Bewegungen mit dem Klang zu synchronisieren, während der prähistorischen Entstehung weitreichender rhythmischer Verhaltensweisen, integriert, etwa beim synchronisierten Singen nicht-lexikalischer Vokabeln und beim koordinierten rhythmischen Klatschen und Stampfen, die in der neueren Entwicklung der Musik instrumental wurden. Ebenso wie die daraus entwickelte Fähigkeit, den Takt rhythmischer Klänge zu halten, erforderte die entstehende Motherese die Einbindung motorischen Verhaltens (der physischen Produktion von Tonhöhe, Timing und Vokalisierungsrate) in Verbindung mit externen Klangquellen (Gesprächsäußerungen). Wenn Motherese ein Vorläufer der Sprachentwicklung war, wie viele glauben, teilen Musik und Sprache phylogenetisch entstandene Substrate für die auditive/motorische Synchronisation, die direkt aus der Zweibeinigkeit stammen. Wenn dem so ist, war die Zweibeinigkeit für die zufällige Bildung fortgeschrittener Kognitionen bei unseren prähistorischen Vorfahren wichtiger als bisher angenommen.

Ipotizziamo che il trascinamento uditivo/motorio si sia evoluto nei primi feti di ominidi in risposta diretta ai passi bipedi delle loro madri e, in seguito, abbia contribuito all’evoluzione della musica e del linguaggio attraverso due processi correlati. In primo luogo, la selezione per il bipedismo ha trasformato i piedi da organi di presa in organi di carico, il che ha avuto un impatto negativo sulla capacità dei bambini di aggrapparsi alle madri, provocando l’emergere di nuovi scambi vocali, affettivi tra madri e bambini, che sono diventati elementi costitutivi per l’emergere del “maternese”. In secondo luogo, la capacità derivata di associare i movimenti al suono fu incorporata durante l’emergere preistorico di comportamenti ritmici ad ampio raggio, come il canto sincronizzato di vocaboli non lessicali e il battito delle mani e il calpestio ritmicamente coordinati, che divennero strumentali durante l’evoluzione più recente della musica. Come l’abilità derivata di seguire il ritmo dei suoni ritmici, il nascente “motherese” implicava il trascinamento del comportamento motorio (la produzione fisica dell’altezza, del ritmo e della velocità della vocalizzazione) con fonti sonore esterne (espressioni conversazionali). Se il maternese è stato un precursore dell’evoluzione del linguaggio, come molti credono, la musica e il linguaggio condividono substrati filogeneticamente derivati per il trascinamento uditivo/motorio che derivavano direttamente dal bipedismo. Se è così, il bipedismo è stato più importante di quanto si credesse in precedenza per scolpire in modo fortuito la cognizione avanzata nei nostri antenati preistorici.

‏راه رفتن انسانهای آغازین دلیل فرگشتی بوجود امدن و پیشرفت موسیقی و زبان انسان ها دارای این توانایی منحصر به فرد هستند که بدنشان را منطبق با امواج صوتی آهنگین به صورت ریتمیک و با زمانبدیه هماهنگ حرکت دهند( آنچه که entrainment خوانده می شود).فرضیه ما این است که این توانایی در جنین های هومینین اولیه به عنوان پاسخی مستقیم به راه رفتن دوپایی مادرانشان تحریک شد و همچنین این سبک راه رفتن (قدمهای دوپا) بعداً از طریق دو فرآیند مرتبط، به توسعه موسیقی و زبان کمک کرد. پاها که اساساً اندامی برای گرفتن بودند، حالا حمل کننده وزن هستند و این امر توانایی نوزادان را برای درکنار نگه داشتن مادر مختل میکند. فقدان تماس فیزیکی، نیاز و پیشرفت ارتباط صوتی عاطفی بین مادر و نوزاد را تحریک کرد، که به نوبه خود پایهای شد برای شیوهای خاص از اصوات جهت دار به سوی کودک که مادرانه نامیده می شود. توانایی پاسخ حرکتی ریتمیک به صدا همچنین می تواند رفتارهای ریتمیک مختلف، مانند دست زدن همزمان، کوبیدن پا و نجوای آهنگین بی کلام را در هم ادغام کرده باشد.این احتمال وجود دارد که چنین اشکالی از توانایی های ماقبل تاریخ به پایه ریزی علایق و توانایی های موسیقیایی انسان کمک کرده باشد.توانایی شکوفنده ی تعقیب متوازن صداهای موزون، و همچنین رشد زودهنگام کلام مادرانه، این فرض را برانگیخت که فرد دارای ظرفیت متوازن سازی عملکرد خود در ارتباط با منابع صوتی خارجی، برای مثال کلام دیگران (برای ایجاد زیر و بمی درست، زمانبندی مناسب و سرعت کلامی سازی) است. اگر همانطور که بسیاری معتقدند، کلام مادرانه پیش قراولی برای رشد زبان بوده است، پس موسیقی و زبان، بستر فیلوژنتیکی مشترکی برای اینتریمنت شنوایی/موتوری دارند. این بستر مشترک مستقیماً از رشد انسان در راه رفتن دوپا ناشی شده است. پس به این ترتیب راه رفتن بر دوپا، گامی مهمتر از آنچه قبلاً فکر میکردیم برای توسعه ی شناخت های ارتقا یافته ی اجداد بشر بوده است.‎

Människan har en enastående förmåga att utifrån ljudsignaler röra kroppen rytmiskt och i takt (s.k. entrainment). Vår hypotes är att denna förmåga stimulerades hos tidiga hominin-foster som ett direkt svar på deras mödrars tvåbenta gång samt att denna gångstil (bipedalism) senare, via två relaterade processer, bidrog till utvecklingen av musik och språk. Fötterna, som främst varit greppande organ blev nu viktbärande, vilket försämrade spädbarns förmåga att hålla fast vid sina mödrar. Utebliven fysisk kontakt, stimulerade behovet och utvecklingen av känslobaserad vokal kommunikation mellan mödrar och spädbarn, vilket i sin tur lade grunden till det specifika och barnriktade sätt att tala som kallas motherese. Förmågan att röra sig rytmiskt till ljud kunde dessutom inlemmas i diverse rytmiska beteenden, såsom synkroniserad handklappning, stampande fötter och (ordlös) sång. Det är sannolikt att sådana former av prehistorisk entrainment var med och lade grunden till människans musikaliska intresse och förmåga. Såväl den spirande förmågan att följa med i takt till rytmiska ljud, som den tidiga utvecklingen av motherese förutsatte att individen hade motorisk förmåga till entrainment i förhållande till externa ljudkällor, till exempel andras tal (för att skapa rätt tonhöjd, tajming, och vokaliseringshastighet). Om motherese, som många tror, var en föregångare till språkutveckling, så delar musik och språk fylogenetiska substrat för hörsel/motor entrainment som kan härledas direkt från människans utveckling av tvåfota gång. I så fall var bipedalism ett viktigare steg än vi tidigare trott vad gäller människosläktets utveckling av avancerad kognition.

私たちの提示する仮説は、聴覚運動の訓練は初期の人類の胎児において母親の二足歩行の足音への直接の反応として進化し、その後、二点の関連したプロセスにおいて、音楽と言語の進化に貢献したというものである。第一点に、二足歩行への選択は、足を掴む機能の器官から重力を支えるものへと変化させた。それは、赤子が母親にしがみつく能力には相応しくない結果となり、母親と幼児の間の斬新な感情的な声のやり取りの発生を促し、母親言葉の発生の構成要素となった。　第二点は、その声に由来する音への動きが、非語彙的な音に合わせた詠唱やリズミカルな手拍子や足拍子という広い範囲の先史時代のリズミカルな行動となった。それは、音楽の進化の手段となった。リズミカルな音の拍子を保つ能力が生まれたように、初期の母親言語は、外部的な音源（会話の発言）と運動行動訓練（ピッチやタイミングや発声の生産）が必然的に伴うのである。もし、多くが信じるように母親言語が言語進化の前駆であるなら、音楽と言語は、系統発生的に二足歩行から直接生じた聴覚運動の訓練の基板を共有する。もしそうであるのなら、二足歩行は、先史時代に偶然にも形成された高度な認知力にとって、以前に信じられていたよりもはるかに重要なのである。

The Marshmallow Test does not reliably predict adult functioning

Jessica F. Sperber, Deborah Lowe Vandell, Greg J. Duncan, Tyler W. Watts, Delay of gratification and adult outcomes: The Marshmallow Test does not reliably predict adult functioning. Child Development, 00, 1-15. 29 July 2024 https://doi.org/10.1111/cdev.14129

Abstract: This study extends the analytic approach conducted by Watts et al. (2018) to examine the long-term predictive validity of delay of gratification. Participants (n = 702; 83% White, 46% male) completed the Marshmallow Test at 54 months (1995–1996) and survey measures at age 26 (2017–2018). Using a preregistered analysis, Marshmallow Test performance was not strongly predictive of adult achievement, health, or behavior. Although modest bivariate associations were detected with educational attainment (r = .17) and body mass index (r = −.17), almost all regression-adjusted coefficients were nonsignificant. No clear pattern of moderation was detected between delay of gratification and either socioeconomic status or sex. Results indicate that Marshmallow Test performance does not reliably predict adult outcomes. The predictive and construct validity of the ability to delay of gratification are discussed.

Economic growth in Roman Britain over four centuries

Scott G. Ortman, José Lobo, Lisa Lodwick, Rob Wiseman, Olivia Bulik, Victoria Harbison , and Luís M. A. Bettencourt, Identification and measurement of intensive economic growth in a Roman imperial province, Science Advances, 5 Jul 2024, Vol 10, Issue 27, DOI: 10.1126/sciadv.adk5517

Abstract: A key question in economic history is the degree to which preindustrial economies could generate sustained increases in per capita productivity. Previous studies suggest that, in many preindustrial contexts, growth was primarily a consequence of agglomeration. Here, we examine evidence for three different socioeconomic rates that are available from the archaeological record for Roman Britain. We find that all three measures show increasing returns to scale with settlement population, with a common elasticity that is consistent with the expectation from settlement scaling theory. We also identify a pattern of increase in baseline rates, similar to that observed in contemporary societies, suggesting that this economy did generate modest levels of per capita productivity growth over a four-century period. Last, we suggest that the observed growth is attributable to changes in transportation costs and to institutions and technologies related to socioeconomic interchange. These findings reinforce the view that differences between ancient and contemporary economies are more a matter of degree than kind.

H/t Tyler Cowen.

Kurt Vonnegut on the value of making your own art of whatever kind

 I first saw this letter in a Facebook group, but it seems it's a well-known letter and is all over the internet. Click on the image to enlarge it.

Fatherhood changes the brain and brings meaning and purpose

Darby Saxbe, Dad Brain Is Real, and It’s a Good Thing, NYTimes, June 15, 2024.

The brain and hormonal changes we observe in new dads tell us that nature intended men to participate in child-rearing, because it equipped them with neurobiological architecture to do so. They too can show the fundamental instinct for nurturing that’s often attributed solely to mothers.

Not only that, but men’s involvement in fatherhood can have long-term benefits for their brain health — and for healthy societies. At a time when boys and men seem to be experiencing greater social isolation and declining occupational prospects, the role of father can provide a meaningful source of identity. [...]

In a 2022 study, my colleagues and I collaborated with researchers in Spain to gather brain scans of a small number of first-time fathers before and after their babies were born. Our results echoed studies of mothers done by some of the same researchers. In several landmark studies, they found that as women became mothers, their brains lost volume in gray matter, the layer of brain tissue rich with neurons, in regions across the brain, including those responsible for social and emotional processing.

Although a shrinking brain sounds like bad news, less can be more: These changes might fine-tune the brain to work more efficiently. [...] Women who lost more brain volume showed stronger attachment to their infants after birth, indicating that the shrinkage promoted bonding.

Our findings for fathers were similar. Men also lost gray matter volume in new fatherhood, in some of the same regions that changed in women. But volume reductions for dads were less pronounced.

Fatherhood brings meaning and purpose:

Even so, most fathers tell us that they derive tremendous meaning and purpose from their connection to their children. Contemporary fathers are almost as likely as mothers to say that parenthood is central to their identity, and men are even more likely to report that children improve their well-being than women are. And the newest data suggests that parenting may ultimately promote long-term brain health; among older men and women, a brain-age algorithm estimated that the brain looked younger among people who had children.

There's more at the link. I've linked the original research below the asterisks.

* * * * *

Magdalena Martínez-García, María Paternina-Die, Sofia I Cardenas, Oscar Vilarroya, Manuel Desco, Susanna Carmona, Darby E Saxbe, First-time fathers show longitudinal gray matter cortical volume reductions: evidence from two international samples, Cerebral Cortex, Volume 33, Issue 7, 1 April 2023, Pages 4156–4163, https://doi.org/10.1093/cercor/bhac333

Abstract: Emerging evidence points to the transition to parenthood as a critical window for adult neural plasticity. Studying fathers offers a unique opportunity to explore how parenting experience can shape the human brain when pregnancy is not directly experienced. Yet very few studies have examined the neuroanatomic adaptations of men transitioning into fatherhood. The present study reports on an international collaboration between two laboratories, one in Spain and the other in California (United States), that have prospectively collected structural neuroimaging data in 20 expectant fathers before and after the birth of their first child. The Spanish sample also included a control group of 17 childless men. We tested whether the transition into fatherhood entailed anatomical changes in brain cortical volume, thickness, and area, and subcortical volumes. We found overlapping trends of cortical volume reductions within the default mode network and visual networks and preservation of subcortical structures across both samples of first-time fathers, which persisted after controlling for fathers’ and children’s age at the postnatal scan. This study provides convergent evidence for cortical structural changes in fathers, supporting the possibility that the transition to fatherhood may represent a meaningful window of experience-induced structural neuroplasticity in males.

What about degrowth? Color me both sympathetic and skeptical. I'm thinking.

Jennifer Szalai, Shrink the Economy, Save the World? NYTimes, June 8, 2024. The article opens:

A rising tide and a bigger pie: Economic growth has long been considered such an obvious boon that it’s pursued by governments across the world as a matter of course. But in 2016, when a London professor warned an audience in Newcastle that Brexit would lead to a precipitous drop in Britain’s gross domestic product, that well-worn measure of economic activity, one woman’s heckling caught him by surprise. “That’s your bloody G.D.P.,” she shouted, “not ours!”

The eruption tapped into a suspicion supported by reality: Gains in economic growth have too often buoyed the fortunes of the richest instead of lifting all boats. Prosperity even in the most prosperous countries hasn’t been shared. But all the attention to inequality is just a crack in the edifice of economic orthodoxy. Now a much more radical proposition has emerged, looming like a wrecking ball: Is economic growth desirable at all? [...]

In 1972, the French theorist André Gorz coined the word décroissance to ask whether “no-growth — or even degrowth” in material production was necessary for “the earth’s balance,” even if it ran counter to “the survival of the capitalist system.”

While the idea of "earth's balance" is (at least superficially) attractive, I'm not sure what it means. It does seem to presuppose some line between "the natural" and "the human" such that the human has been messing up the natural. That strikes me as being too much like a repackaging of the idea of original sin. OTOH I've long been suspicious of an economic regime, like capitalism, that positively requires growth in order to function at all. Perhaps that suspicion is a repackaging of medieval Christian objects to usury? But it is also a recognition that we live in a finite world.

Continuing on:

For advocates of degrowth, it’s a core tenet that in high-income countries the constant expansion demanded by capitalism isn’t required to improve people’s lives; instead, the ensuing inequality and environmental havoc have frequently undermined them.

Take Hickel, an anthropologist who teaches in London and Barcelona and is one of the movement’s most spirited exponents. Like other contemporary critics of unfettered growth, he emphasizes the climate crisis. His book begins with scenes of ecological devastation: dying earthworms, declining crop yields, collapsing fish stocks. He points to the connection between growing G.D.P. and energy use, identifying an ideology of “growthism” that he equates with “a kind of madness.” He says that he is not promoting a deliberate reduction in G.D.P. But if G.D.P. stagnates or declines because we conserve energy instead of consuming it, so be it. [...]

Of course, such a sweeping pronouncement is far from uncontested. Economists like Paul Krugman and data scientists like Hannah Ritchie have maintained that technological advances mean that economic prosperity doesn’t have to lead to ecological degradation. But for all the debates over carbon pricing and parts per million and degrees of warming, the distinctive argument that Hickel and other degrowthers make is ultimately a moral one: “We have ceded our political agency to the lazy calculus of growth.”

What a piece of rhetoric: “... the lazy calculus of growth.” Color me sympathetic. Moving on:

As the economist Daniel Susskind notes in his new book, “Growth: A History and a Reckoning,” big questions that were pushed to the margins — about clashing notions of freedom, equality and justice — have roared back with a vengeance. Still, he sees this as cause for ambivalence, not despair. After all, growth has also emancipated much of the world from “an unforgiving struggle for subsistence,” Susskind points out. “Growth has an irresistible promise and an unacceptable price; it is miraculous and devastating; we need a lot more and vastly less.”

Although he denounces the blithe optimism of the economic establishment, Susskind is also highly critical of degrowthers, who are too dismissive of capitalism for his liking.

The article goes on to discuss the ideas of a Japanese Marxist philosopher, whose book, Slow Down: The Degrowth Manifesto, has sold half a million copies.

Saito admits that there is “some truth” to the argument that capitalism produces material wealth, and so he champions degrowth communism only for rich countries, not for poor ones. “Those in the Global North enjoy rich lifestyles enabled by the sacrifices of those in the Global South,” he writes. Degrowth would halt this injustice and offer a form of “reparations”: Reducing the resources and energy used by the Global North would allow the Global South to pursue its own economic growth instead.

Imagination, imagination, who's got imagination?

Even degrowth’s skeptics may find that Saito’s examples of grass-roots organizing sound agreeably democratic and improvisational. But the prospect of global apocalypse that degrowthers keep emphasizing also has the perverse effect of making local measures sound acutely inadequate. Still, Saito says that such experiments do offer something crucial: an enlarged sense of what’s possible. Degrowth’s critics, he writes, suffer from “a poverty of imagination that simply accepts the status quo as unchangeable.”

As it happens, Susskind says precisely the same thing but in the reverse: that it’s degrowth’s advocates who suffer from a “lack of imagination.” The mirrored accusations are striking. Maybe it isn’t a matter so much of imagination scarcity as of where that imagination is directed. Techno-optimists place their faith in innovation; degrowthers place theirs in social movements. Both sides lay claim to being the genuine realists. Each insists that we simply don’t have enough time to do what the other side wants.

Hey! I've got an idea. Let's create a super-intelligent AI and then let it solve the problem.

The Synthesizing Mind: Steve Pinker interviews Howard Gardner

From the YouTube page:

With Howard Gardner's memoir "A Synthesizing Mind" as a point of departure, Steven Pinker will ask Gardner to review his varied scholarly interests and contributions over the course of Gardner's 62 years at Harvard. In addition to reflections on Gardner's well known theory of multiple intelligences, the speakers will cover several other strands of Gardner's research program including, most recently, what it means to have a 'synthesizing mind."

Using a kiddie-cam to train an Ai through the eyes and ears of a child

2/ First, we are incredibly grateful for the authors of the SAYCam paper and dataset (@mcxfrank, @andyperfors, and others not on twitter), which made our work possible and we were not involved in collecting. SAYCam provides an unprecedented look at a child's egocentric,…

— Wai Keen Vong (@wkvong) February 1, 2024

4/ To test this, what better than to train a neural network, not on enormous amounts of data from the web, but only on the input that a single child receives? What would it learn then, if anything? pic.twitter.com/bQ9aVbXUlB

— Wai Keen Vong (@wkvong) February 1, 2024

6/ Results: Even with limited data, we found that the model can acquire word-referent mappings from merely tens to hundreds of examples, generalize zero-shot to new visual datasets, and achieve multi-modal alignment. Again, genuine language learning is possible from a child's… pic.twitter.com/FCHfZCqftr

— Wai Keen Vong (@wkvong) February 1, 2024

8/ Limitations: A typical 2-year-old's vocabulary and word learning skills are still out of reach for the current version of CVCL. What else is missing? Note that the modeling, and the data, are inherently limited compared to children’s actual experiences and capabilities.
- CVCL…

— Wai Keen Vong (@wkvong) February 1, 2024

A long-term study of human development, 85 years of the same population [Happiness]

There's a ton of references at the YouTube site.

The overall finding is that healthy relationships with others is the single most important determinate of happiness. What does that imply about living in a world of "intelligent" machines? I hear and read people wondering, What will we do when machines are smarter than any of us? Setting aside the fact that I don't (really/quite) know what that means, perhaps that worry is misplaced. Perhaps we should be thinking about guiding the development and deployment of AI in directions that allow us to develop more fruitful relationships with others.

Back in my undergraduate years at Johns Hopkins I took a half-dozen or so courses from Richard Macksey. He always had one of more guest lecturers in his classes. One of these guests was an Episcopal priest named Ralph Harper. I forget just what he brought Harper in to talk about, but it may have been mysticism, which is certainly one of the things I thought a great deal about in those days (still do). I remember Macksey recommending a book that Harper had written. I forget the title, but it might have been Human love: Existential and mystical. In fact, I'm sure that's the book, which I got (and is now in storage somewhere in suburban New Jersey). In there Harper said something to the effect that the answer to the question, What is the meaning of life? is not some kind or proposition or statement. It is something we can do. What can we do?

Love? Cultivate our relationships? If so, isn't that orthogonal to this strange and wonderful technology we're now developing?

Developmental changes in exploration resemble stochastic optimization

Giron, A.P., Ciranka, S., Schulz, E. et al. Developmental changes in exploration resemble stochastic optimization. Nat Hum Behav 7, 1955–1967 (2023). https://doi.org/10.1038/s41562-023-01662-1

Abstract

Human development is often described as a ‘cooling off’ process, analogous to stochastic optimization algorithms that implement a gradual reduction in randomness over time. Yet there is ambiguity in how to interpret this analogy, due to a lack of concrete empirical comparisons. Using data from n = 281 participants ages 5 to 55, we show that cooling off does not only apply to the single dimension of randomness. Rather, human development resembles an optimization process of multiple learning parameters, for example, reward generalization, uncertainty-directed exploration and random temperature. Rapid changes in parameters occur during childhood, but these changes plateau and converge to efficient values in adulthood. We show that while the developmental trajectory of human parameters is strikingly similar to several stochastic optimization algorithms, there are important differences in convergence. None of the optimization algorithms tested were able to discover reliably better regions of the strategy space than adult participants on this task.

Main

Human development has fascinated researchers of both biological and artificial intelligence alike. As the only known process that reliably produces human-level intelligence1, there is broad interest in characterizing the developmental trajectory of human learning2,3,4 and understanding why we observe specific patterns of change5.

One influential hypothesis describes human development as a ‘cooling off’ process4,6,7, comparable to simulated annealing (SA)8,9. SA is a stochastic optimization algorithm named in analogy to a piece of metal that becomes harder to manipulate as it cools off. Initialized with high temperature, SA starts off highly flexible and likely to consider worse solutions as it explores the optimization landscape. But as the temperature cools down, the algorithm becomes increasingly greedy and more narrowly favours only local improvements, eventually converging on an (approximately) optimal solution. Algorithms with similar cooling mechanisms, such as stochastic gradient descent and its discrete counterpart stochastic hill climbing (SHC) are abundant in machine learning and have played a pivotal role in the rise of deep learning10,11,12,13.

This analogy of stochastic optimization applied to human development is quite alluring: young children start off highly stochastic and flexible in generating hypotheses4,14,15,16 and selecting actions17, which gradually tapers off over the lifespan. This allows children to catch information that adults overlook18, and learn unusual causal relationships adults might never consider4,15. Yet this high variability also results in large deviations from reward-maximizing behaviour3,19,20,21,22, with gradual improvements during development. Adults, in turn, are well calibrated to their environment and quickly solve familiar problems, but at the cost of flexibility, since they experience difficulty adapting to novel circumstances23,24,25,26.

While intuitively appealing, the implications and possible boundaries of the optimization analogy remain ambiguous without a clear definition of the process and a specification of what is being optimized. As a consequence, there is a need for a direct empirical test of the similarities and differences between human development and algorithmic optimization.

Perhaps the most direct interpretation is to apply cooling off to the single dimension of random decision temperature, controlling the amount of noise when selecting actions or sampling hypotheses6,16,27, although alternative implementations are also possible28,29. Evidence from experimental studies suggest that young children are harder to predict than adults17,30, implying greater stochasticity, which is amplified in neurodevelopmental disorders such as attention deficit hyperactivity disorder28 and impulsivity31. However, this interpretation is only part of the story, since developmental differences in choice variability can be traced to changes affecting multiple aspects of learning and choice behaviour. Aside from a decrease in randomness, development is also related to changes in more systematic, uncertainty-directed exploration19,27,32, which is also reduced over the lifespan. Additionally, changes in how people generalize rewards to novel choices27 and the integration of new experiences33,34 affect how beliefs are formed and different actions are valued, also influencing choice variability. In sum, while decision noise certainly diminishes over the lifespan, this is only a single aspect of human development.

Alternatively, one could apply the cooling off metaphor to an optimization process in the space of learning strategies, which can be characterized across multiple dimensions of learning. Development might thus be framed as parameter optimization, which tunes the parameters of an individual’s learning strategy, starting off by making large tweaks in childhood, followed by gradually lesser and more-refined adjustments over the lifespan. In the stochastic optimization metaphor, training iterations of the algorithm become a proxy for age.

This interpretation connects the metaphor of stochastic optimization with Bayesian models of cognitive development, which share a common notion of gradual convergence35,36. In Bayesian models of development, individuals in early developmental stages possess broad priors and vague theories about the world, which become refined with experience35. Bayesian principles dictate that, over time, novel experiences will have a lesser impact on future beliefs or behaviour as one’s priors become more narrow36,37. Observed over the lifespan, this process will result in large changes to beliefs and behaviour early in childhood and smaller changes in later stages, implying a similar developmental pattern as the stochastic optimization metaphor. In sum, not only might the outcomes of behaviour be more stochastic during childhood, but the changes to the parameters governing behaviour might also be more stochastic in earlier developmental stages.

The whole article is at the link.

The Effects of Adverse Childhood Experiences on Adults' Subjective Wellbeing

Blanchflower, David G. and Bryson, Alex, The Effects of Adverse Childhood Experiences on Adults' Subjective Wellbeing. IZA Discussion Paper No. 16479, Available at SSRN: https://ssrn.com/abstract=4587415 or http://dx.doi.org/10.2139/ssrn.4587415

Abstract: Using four cross-sectional data files for the United States and Europe we show that Adverse Childhood Experiences (ACE) have a significant impact on subjective wellbeing (SWB) in adulthood. Death of a parent, parental separation or divorce, financial difficulties, the prolonged absence of a parent, quarreling between parents, parental unemployment, sexual assault, experiencing long-term health problems, being bullied at school and being beaten or punched as a child all have long-term impacts on wellbeing. These experiences impact a wide range of wellbeing measures in adulthood including satisfaction with many aspects of everyday life, happiness and life satisfaction, self-assessed health, and are positively linked to measures of negative affect including the GHQ6. The evidence linking ACEs to lower SWB in adulthood is consistent across fifty different measures including sixteen positive affect and twenty-six negative affect measures relating to assessments of one's one life, and eight variables capturing how the individual feels about the area she lives in, including unemployment, drugs, violence and vandalism plus democracy in their country. Trauma in childhood is long lasting.

H/t Tyler Cowen

I'm reminded of the literature on childhood attachment,  a subject I studied as an undergraduate at Johns Hopkins where I took an independent study with Mary Ainsworth (and in Wikipedia), one of the founders of attachment theory. That has been central to my thinking every since.

Towards Self-Assembling Artificial Neural Networks

Elias Najarro, Shyam Sudhakaran, Sebastian Risi, Towards Self-Assembling Artificial Neural Networks through Neural Developmental Programs, arXiv:2307.08197v1 [cs.NE]

Abstract: Biological nervous systems are created in a fundamentally different way than current artificial neural networks. Despite its impressive results in a variety of different domains, deep learning often requires considerable engineering effort to design high-performing neural architectures. By contrast, biological nervous systems are grown through a dynamic self-organizing process. In this paper, we take initial steps toward neural networks that grow through a developmental process that mirrors key properties of embryonic development in biological organisms. The growth process is guided by another neural network, which we call a Neural Developmental Program (NDP) and which operates through local communication alone. We investigate the role of neural growth on different machine learning benchmarks and different optimization methods (evolutionary training, online RL, offline RL, and supervised learning). Additionally, we highlight future research directions and opportunities enabled by having self-organization driving the growth of neural networks.

From the introduction:

The study of neural networks has been a topic of great interest in the field of artificial intelligence due to their ability to perform complex computations with remarkable efficiency. However, despite significant advancements in the development of neural networks, the majority of them lack the ability to self-organize, grow, and adapt to new situations in the same way that biological neurons do. Instead, their structure is often hand-designed, and learning in these systems is restricted to the optimization of connection weights.

Biological networks on the other hand, self-assemble and grow from an initial single cell. Additionally, the amount of information it takes to specify the wiring of a sophisticated biological brain directly is far greater than the information stored in the genome (Breedlove and Watson, 2013). Instead of storing a specific configuration of synapses, the genome encodes a much smaller number of rules that govern how to grow a brain through a local and self-organizing process (Zador, 2019). For example, the 100 trillion neural connections in the human brain are encoded by only around 30 thousand active genes. This outstanding compression has also been called the “genomic bottleneck” (Zador, 2019), and neuroscience suggests that this limited capacity has a regularizing effect that results in wiring and plasticity rules that generalize well.

In this paper, we take first steps in investigating the role of developmental and self-organizing algorithms in growing neural networks instead of manually designing them, which is an underrepresented research area (Gruau, 1992; Nolfi et al., 1994; Kow Aliw et al., 2014; Miller, 2014). Even simple models of development such as cellular automata demonstrate that growth (i.e. unfolding of information over time) can be crucial to determining the final state of a system, which can not directly be calculated (Wolfram, 1984). The grand vision is to create a system in which neurons self-assemble, grow, and adapt, based on the task at hand.

Towards this goal, we present a graph neural network type of encoding, in which the growth of a policy network (i.e. the neural network controlling the actions of an agent) is con- trolled by another network running in each neuron, which we call a Neural Developmental Program (NDP). The NDP takes as input information from the connected neurons in the policy network and decides if a neuron should replicate and how each connection in the network should set its weight. Starting from a single neuron, the approach grows a functional policy network, solely based on the local communication of neurons. Our approach is different from methods like NEAT (Stanley and Miikkulainen, 2002) that grow neural networks during evolution, by growing networks during the lifetime of the agent. While not implemented in the current NDP version, this will ultimately allow the neural network of the agents to be shaped based on their experience and environment.

I speculate that such a regime seems to be a way of eliminating the problem that current models cannot be readily modified once they have been trained. Rather, they must be completely retrained if one wishes to add new information to them. This represents a step toward polyviscosity.

Dynamics in the epigenetic landscape

The molecular and mathematical basis of Waddington's epigenetic landscape: a framework for post-Darwinian biology? https://t.co/pXUg3PVxkx - this (2012) paper gives a great dynamical systems view of gene regulatory networks pic.twitter.com/UnNcOtxb6D

— Kevin Mitchell @WiringtheBrain@ mstdn .social (@WiringTheBrain) October 1, 2023

A phylogenetic approach to the neural basis of behavior

It provides a much better way to think about all this than simplistic shorthand notions like the "lizard brain" pic.twitter.com/ixVspsdCHZ

— Kevin Mitchell @WiringtheBrain@ mstdn .social (@WiringTheBrain) May 4, 2023

Abstract of the linked article, Resynthesizing behavior through phylogenetic refinement:

This article proposes that biologically plausible theories of behavior can be constructed by following a method of "phylogenetic refinement," whereby they are progressively elaborated from simple to complex according to phylogenetic data on the sequence of changes that occurred over the course of evolution. It is argued that sufficient data exist to make this approach possible, and that the result can more effectively delineate the true biological categories of neurophysiological mechanisms than do approaches based on definitions of putative functions inherited from psychological traditions. As an example, the approach is used to sketch a theoretical framework of how basic feedback control of interaction with the world was elaborated during vertebrate evolution, to give rise to the functional architecture of the mammalian brain. The results provide a conceptual taxonomy of mechanisms that naturally map to neurophysiological and neuroanatomical data and that offer a context for defining putative functions that, it is argued, are better grounded in biology than are some of the traditional concepts of cognitive science.

Cf. Benzon and Hays, 1988, Principles and Development of Natural Intelligence. Note as as well that Cisek has been influenced by William Powers.

It’s time to trade the Rikers Island jail in for a casino complex

Neil Barsky, Where’s the Best Place to Build a Casino in New York City?, The New York Times, December 29, 2022.

On the one hand New York City must close down the Rikers Island Jail complex by Aug, 31, 2027. On the other hand, it is now looking for a location to place a casino. Why not, Neil Barsky asks, put the casino on Rikers Island?

The city should build a large Las Vegas-style hotel and casino complex on Rikers after the jail complex is shut down.

Such a project would be a major attraction for the 23 million people living in the metropolitan area and the tens of millions more who visit the city each year. It would provide thousands of construction jobs for New Yorkers, and steady employment for thousands more. It would stem the flow of the billions of dollars that have been sucked out of the city and into casinos in nearby states over the past half century. And it would demonstrate that New York City can still get things done on a colossal scale.

But the real value of a Rikers casino goes way beyond dollars and cents. It should be structured so that the city’s ownership share must be earmarked from Day 1 for programs that are directly connected to incarceration and crime — fighting poverty, job training, drug rehabilitation, mental health services and public safety.

If the city can assure that its share of the profits is used to help its most needy citizens, a Rikers casino could become one of the most impactful public development projects in the city’s history.

At 413 acres, about two-thirds of a square mile, Rikers Island is nearly 15 times the size of Hudson Yards on Manhattan’s West Side. That is more than enough space to build a casino, a convention space, a 3,000-room hotel, a concert venue and restaurants. A narrow bridge connects the island to Queens and would need to be expanded. Ferries from the Bronx could provide access from the north. Bus lines could be established from the south. Parking could be built on the island. It is an urban planner’s dream.

That sounds good to me.

With “a convention space, a 3,000-room hotel, a concert venue and restaurants” in addition to the casino it reminds me a bit about the World Island Project that Zeal Greenberg had proposed for Governors Island.

He proposed to transform Governors Island, a 172 acre former Coast Guard base in New York Harbor, into World Island, which he described as a “permanent world’s fair for a world that’s permanently fair”. Think of it as a combination of the best features of the United Nations, Disney World, a kid’s rumpus room, the trading floor at the Chicago Board of Trade, the Bibliothèque nationale de France, and the Japanese exhibit at the 1893 World’s Fair in Chicago. (Wow!) It would cost $25 billion or so (Wow wow woW!) and be planted with orchids. (I’m likin’ this guy…) Why orchids? Beauty aside, they’re an early warning system for climate change, when the orchids go, we’re not going to be far behind. (…a lot!)

See you there on opening day.

Does ChatGPT’s performance warrant working on a tutor for children? – Extra! ChatGPT can "talk" to a 3-year-old and write like 10 and 14 year-olds.

Of course we already have sophisticated robot toys and companion robots for, e.g. older people, but I have no direct experience with any of these. Tutoring is quite different.

Here’s a dialog I had yesterday with ChatGPT:

Tell me about the digestive process. We put food and drink in our mouths, then what happens?

The digestive process begins when you put food and drink in your mouth. When you chew, you mechanically break down the food into smaller pieces, which makes it easier to digest. As you chew, your salivary glands produce saliva, which moistens the food and helps to break it down further.

After you swallow the food, it passes down the esophagus, a muscular tube that connects your mouth to your stomach. The muscles in the walls of the esophagus contract in a coordinated way, a process called peristalsis, to push the food down towards the stomach.

Once the food reaches the stomach, it is mixed with stomach acid and enzymes, which continue to break it down into smaller pieces. The stomach also mixes the food with digestive juices and churns it to form a thick liquid called chyme.

From the stomach, the chyme is slowly released into the small intestine, where it is mixed with bile, a greenish-yellow fluid produced by the liver and stored in the gallbladder. Bile helps to digest fats and absorb fat-soluble vitamins.

As the chyme moves through the small intestine, the walls of the intestine absorb the nutrients from the chyme. The small intestine is lined with tiny finger-like projections called villi, which help to increase the surface area for absorption.

Any undigested food and waste products pass into the large intestine, where most of the water and electrolytes are absorbed back into the body. The remaining material, which is mostly indigestible fiber and bacteria, is compacted and eliminated from the body through the rectum and anus as feces.

That's a general overview of the digestive process. It's a complex and highly coordinated process involving many different organs and systems in the body.

Young children don’t understand things as well as adults do. That’s too complicated for a three-year old. How would you explain the digestive process to a three-year old?

Sure, I can give you a simpler explanation of the digestive process for a three-year-old child.

When we eat, our body breaks down the food into tiny pieces that our body can use for energy and nourishment. This happens in our stomach and intestines.

First, the food goes down our throat and into our stomach. Our stomach is a special bag inside our body that helps to mash up the food and make it smaller.

Then, the mashed-up food goes into our intestines. The intestines are long tubes inside our body that help to absorb all the good things from the food, like vitamins and minerals.

After the body has taken all the good things it needs from the food, the rest comes out of our body as poop. Poop is the leftover food that our body can't use.

I hope that helps to give you a basic idea of the digestive process for a three-year-old. Let me know if you have any other questions.

There is a Japanese book, みんなうんち. It was very popular and has been translated into English. What can you tell me about it?

みんなうんち is a Japanese children's book written by Tarō Gomi that has been translated into English under the title "Everyone Poops." The book is a simple and straightforward explanation of the digestive process and the natural occurrence of bowel movements in all living organisms. It aims to help young children understand and feel comfortable with their own bodily functions and to demystify the topic of poop for them.

The book uses simple illustrations and language to explain that everyone has to poop, and that it is a normal and necessary part of life. It also explains the process of digestion and how the food we eat is broken down and eliminated from the body.

"Everyone Poops" has become a popular and enduring children's book and has been widely translated and published in many languages around the world. It has also inspired a series of related books by the same author, including "Everyone Pee," "Everyone Eats," and "Everyone Sleeping."

Thank you very much.

You're welcome! I'm glad I could help. If you have any more questions, don't hesitate to ask. I'm here to help.

I take that as provisional evidence that it can craft its dialog to a child’s level. If I were to ask it to speak to a 10-year-old, would it have been able to do so accurately? I don’t know, I didn’t think to ask. What I’m getting at is whether or not it just knows the difference between regular output and simple output, or is it more sophisticated than that. And, if so, how is it able to make the gradations? These questions are worth checking out.

Then there is the question in input-output. Three-year-olds can’t read or type. But I suspect current voice recognition and text-to-voice output is adequate. Moreover such a tutor could call on a wealth of videos at YouTube, Vimeo, and other sources.

There are problems, of course. ChatGPT doesn’t have any sense of ground truth and tends to hallucinate, a term of art. It’s still got the sorts of problems that Gary Marcus, among many others, talks about. And it’s not politically house-broken. Those problems are being worked on. I have no idea how long it will take to make this technology safe for children.

But I also note that, at the moment, I don’t think those problems will ever be solved, totally. Even when Marcus and others have succeeded in integrating symbolic tech with deep learning tech, even when Eric Jang’s robots have had a decade or three to collect detailed data through interacting with the world, there will be more to do. The world is messy and complex. It does not lend itself to being parceled out into neat categories. Any technology that has the power to meet and move around in that world, it must necessarily be messy and complex. I conclude that the process of aligning AIs with human values – which are hardly coherent among themselves and which vary across cultures – will be never ending.

With that in mind, who’s working on hooking up LLMs with speech input and output, with access to videos, and with the capacity to interact with children of all ages as well as with adults? If no one is, no university, no corporate R & D lab, then someone needs to get started. Note that I'm particularly interested in tutors for young children. As a target, think of young Sutan in this video.

For inspiration, read Neil Stephenson’s The Diamond Age: Or, A Young Lady's Illustrated Primer. 

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Addendum 12.26.22: This just in: ChatGPT is able to write like a fourth grader and an eighth grader! This answers the question I posed above:

What I’m getting at is whether or not I just knows the difference between regular output and simple output, or is it more sophisticated than that. And, if so, how is it able to make the gradations? These questions are worth checking out.

Yes, it can make gradations. Reporting in The New York Times, Claire Cain Miller, Adam Playford, Larry Buchanan and Aaron Krolik report an informal experiment in which ChatGPT was presented with essay from the National Assessment of Educational Progress. It was asked to write like a fourth grader (10 years old) and an eighth grader (14). It did so successfully. The essays coupled with essays by real children and were presented to four experts on child's writing for evaluation. These experts had trouble telling the difference – FWIW, I did not; I got 9 out of 10 correct.

Some observations from the article:

The fact that ChatGPT can write well could change or even transform many professions — law, therapy, coding, screenwriting, medicine, to name just a few. In the process, it could remake how we think about learning to write.

One widespread concern has been about cheating, and whether children will ask the chatbot to do their homework. But Ms. Nielsen said students already have access to technology all day, giving them plenty of ways to cheat, and most don’t want to.

More sophisticated ways to detect the bot’s writing are also coming.

And then:

The bigger question: If a bot can write like a human, should schools still teach writing?

Already, schools teach less spelling and grammar because students have access to spellcheck or write in Google Docs, which corrects their mistakes. Yet it’s not dissimilar from continuing to teach students long division when calculators exist, said Professor Levine — doing something yourself gives you a deeper understanding of how it works and why it matters.

“It’s still useful to understand the principle of addition, even if you can give the work of the outcome to the computer,” she said. In English and language arts, she said, “writing as a way of talking to yourself to clarify your own thinking is a valuable tool.”

Instead, she said, she thinks the chatbot technology could be a catalyst for schools to teach writing differently.

I like this suggestion:

The bot could also be used as a way to practice revision, something few teachers have time to do in depth now, they said. Ms. Blume said she’s tried to convince children that rewriting is the best part of the process — she does it at least five times for her own writing — but “they hate to be told they have to, as they call it, do their story again.”

If the chatbot could produce an essay akin to a first draft, she said, students asked to build on it could see how rewriting gives them the chance to make it their own.

Following a suggestion my friend Rich made: the students could also prompt the chatbot in revising its own essay. That would be fun – let's play with the robot! – and would, I suspect, be very effective. Teaching someone else is a very good way to improve one's own knowledge and skill. If that someone else is a computer, who cares?

Input-dependent segregation of visual and somatosensory circuits in the mouse superior colliculus during development

Thrilled to share our new paper published today in @ScienceMagazine! Huge congrats to @T_Guillamon and all the coauthors for the great work 👏 @GuilleLBendito @Mar_AnibalM @lpuche_1 @JAMoreno_Bravo @NeuroAlc 🧵1/3 https://t.co/5q8vn0JBCl

— Lopez_Bendito Lab (@GLB_Lab) August 18, 2022

2. At birth, superior colliculus circuit reorganization provides sensory-modality specificity
3. Perinatal retinal waves drive the SC circuit reorganization
4. Failure to timely segregate drives long-lasting circuit alterations 3/3

— Lopez_Bendito Lab (@GLB_Lab) August 18, 2022

Allocating sensory responsibilities

During late embryogenesis, the developing mouse brain has inputs from both visual and sensory systems that activate overlapping regions of the cortex. Guillamón-Vivancos et al. now show how spontaneous activity in the perinatal retina tunes the visual cortex to specialize in interpreting retinal activity as vision. Without such spontaneous retinal activity, this part of the brain will take on somatosensory responsibilities instead. This handshake between the sensory system and the cortical recipient is established during a limited time in the perinatal phase of development. —PJH

Abstract

Whereas sensory perception relies on specialized sensory pathways, it is unclear whether these pathways originate as modality-specific circuits. We demonstrated that somatosensory and visual circuits are not by default segregated but require the earliest retinal activity to do so. In the embryo, somatosensory and visual circuits are intermingled in the superior colliculus, leading to cortical multimodal responses to whisker pad stimulation. At birth, these circuits segregate, and responses switch to unimodal. Blocking stage I retinal waves prolongs the multimodal configuration into postnatal life, with the superior colliculus retaining a mixed somato-visual molecular identity and defects arising in the spatial organization of the visual system. Hence, the superior colliculus mediates the timely segregation of sensory modalities in an input-dependent manner, channeling specific sensory cues to their appropriate sensory pathway.