Chris von Csefalvay is a computational epidemiologist/data scientist working at the intersection of AI, epidemiology and public health.

Chris von Csefalvay

The year is 1959. Eisenhower is on his second term, Castro just kicked Batista out of the country and Ray Charles’s Let the Good Times Roll is topping the charts.

The 95% myth

Over at the work blog, I’m discussing what knowledge means for large language models (LLMs), and the ways in which we can leverage this knowledge dividend for better inference.  Read the full post here.

The knowledge dividend of large language models

The awesome thing about language is that, well, we all mostly speak it, to some extent or another. This gives us an immensely powerful tool to manipulate transformational tasks. For the purposes of this post, I consider a transformational task to be essentially anything that takes an input and is largel intended to return some version of the same thing. This is not a very precise definition, but it will have to do for now.

LAIR - Language As Intermediate Representation

As the new Omicron variant of concern of COVID-19 emerged over Thanksgiving week (of all times!), attention has been turning to Paxlovid (PF-07321332). If, like me, you torment yourself by perusing conspiracy theories, you might have heard it referred to as Pfizermectin.

Peace, love, Paxlovid and ‘Pfizermectin’

I used to be on Quora. I’m not anymore. But I used to be. And I wrote some answers. Here are some of my favourites, categorised by field… sort of.

 AI

If I wrote an AI and trained it to score 200 on a standardized IQ test, what could a human of 100 IQ still do better? Read the full answer here. Will true AI come before the ability to completely simulate a human brain? Is there a difference? Read the full answer here.

My favourite Quora answers

Tip  If you’re here for the DOI matching script, the link is here. Quarto is a great tool for reproducible research. It is also a great tool for building websites. After about a decade of Wordpress-based websites, I’ve moved to Quarto primarily for two reasons. First, most of my content is largely static.

Quarto project scripts are awesomeness

There’s a notion in artificial intelligence known as Moravec’s paradox: it’s relatively easy to teach a computer to play chess or checkers at a pretty decent level, but near impossible to teach it something as trivial as bipedal motion. (Hassabis 2017) The sensorimotor tasks that our truly wonderful brains have mastered by our second birthday are much harder to teach a computer than something arguably as ‘complex’ as beating a chess grandmaster.

The hardest AI problem you’ve never heard of.

It appears that in what is clearly a wonderful little PR stunt, a Polish rum company managed to do a Sophia and appoint an ‘AI-driven’ ‘robot’ as its ‘CEO’.  The other guilty party to this pile of steaming bovine excrement is Hanson Robotics, famous for giving us Sophia, the “world’s first robot citizen”. Most of what I’m saying here goes just as well for Sophia.

The skeuomorphic fallacy

Yesterday, I completed a marathon on the SkiErg, with a pretty respectable time (see results here). I know I can do better, and I know I

 will

do better. On the other hand, this was a marathon where I pretty much did everything wrong. And that was sort of an instructive experience in its own right. The title is somewhat misleading. Not much went wrong – the marathon itself was smooth sailing.

How to do a SkiErg marathon entirely the wrong way (but still finish)

There’s something special about language. It is ‘our own’, it is ‘us’, in a profound way, and quite surprisingly, more so than art. I was deeply struck by this when I first saw reactions to large generative language models that created realistic, human-ish prose.

Beyond Broca

In my latest post for the Starschema blog, I discuss the end of dashboards, and what comes next:  Read the full post here.

As we may see: the world after dashboards

There might be valid concerns about the mRNA vaccines. Then there are the clearly insane ones, such as the claims that it involves the injection of a microchip. The argument that mRNA vaccines are a form of ‘gene therapy’ are somewhere in the middle, and that makes responding to it somewhat difficult.

Why the COVID-19 vaccines are not gene therapy

The temple of Asclepios, the Greek god of healing arts and medicine, at Epidaurus was pretty much the ancient Greek world’s equivalent of the Mayo Clinic. It then tells us a lot about the Greek worldview of healing that one of the things the temple complex prominently featured was a theatre. The Greeks believed in drama therapy, but in perhaps a slightly different way of how we think of it today.

The Moral Pulse of the Machine

Every year, the Commandant of the Marine Corps publishes a reading list of books that often only bear on warfighting tangentially at best. The idea behind this is that those entrusted with the lives of servicemembers should have an understanding of the world that goes beyond the profession of arms. In much the same way, I have been advising data scientists to go beyond professional literature.

Five non-data-science books for data scientists

In the middle of the green and pleasant countryside of England lies a small piece of commons –– land, that is, over which a number of people share certain rights. In this hypothetical scenario, it’s six farmers,  to . Each of them has a hypothetical cow, which differs from ordinary cows in that it grazes a fixed unit, and produces a fixed amount of milk (unlike real cows, which vary wildly in their input and output parameters, or so I’m told).

Ransomware attacks as n-person prisoner’s dilemmas

Say you’re busing tables and you’re trying to pass someone in a wheelchair. What do you do? Do you say “excuse me” and wait for them to move? Do you say “excuse me” and then try to pass them? Do you just try to pass them? Do you say nothing and just try to pass them? All of these are, actually, pretty legitimate answers. Now, say you’re a robot.

What I learned from getting bodied by a robot.

Asemantic Induction of Hallucinations in LLMs

There’s a style of visual design I’m inordinately fond of called Raygun Gothic. It’s hard to describe what the hell exactly one needs to be on to enjoy it, but think of it like the aesthetic from the latter Fallout games with a more optimistic outlook on the future. Gibson described it as “the future that never was”, and I think that’s a pretty apt description. We get these competing futures in technology all the time.

Prompt Engineering: The Art of Yesterday

It’s not every day that you find out you have climbed the exalted heights of another discipline. My work is pretty interdisciplinary, but it shocked me, too, that I’m apparently holding forth on neoliberalism and the epistemic question in African universities (archive link):  This, of course, came at some surprise to me, as I have never written anything on the topic.

Stochastic parrots, cap and gown edition

In the first four entries (1 2 3 4) of this sequence, I have focused primarily on what LLMs aren’t, can’t, won’t, wouldn’t and shouldn’t. It’s probably time to conclude this series by that much awaited moment in all stories, where the darkest night finally turns into a glorious dawn, where we finally arrive at the promised land, where we finally get to talk about what LLMs

 could

be. What I see as the most successful potential model of

Teams of Rivals

My recent post on the Starschema blog discusses the need for better data products to tackle future pandemic challenges:  Read the full post here.

Data for the next pandemic

I have probably spent more time looking at Poussin’s

 Dance to the Music of Time

than any other work of art. Sneaking off to the Wallace Collection in London and just looking at the

 Dance

was my comfort activity while living in London – a time that was not exactly devoid of its trials. It’s not, by any measure,

 great

art, insofar as such judgments can be made with any objectivity.

The Lyre of Hephaestus

In a recent paper that has attracted the interest of popular media as well, Fabio Urbina and colleagues examined the use (or rather, the abuse) of computational chemistry models of toxicity for generating toxic compounds and potential chemical agent candidates.(Urbina et al. 2022) Urbina and colleagues conclude that Urbina, Fabio, Filippa Lentzos, Cédric Invernizzi, and Sean Ekins. 2022.

A different shade of grey

I love posts that allow me to merge some of my addictions.

Auto-DOI for Quarto posts via Rogue Scholar

Every year, the Commandant of the Marine Corps publishes a reading list
of books that often only bear on warfighting tangentially at best. The
idea behind this is that those entrusted with the lives of
servicemembers should have an understanding of the world that goes
beyond the profession of arms.

In much the same way, I have been advising data scientists to go beyond
professional literature. Below are the five books every data scientist
should have read. As a profession, we are increasingly tackling morally
complex issues. In the context of nuclear weapons, General Omar Bradley
referred to nuclear giants but ethical infants. In a world that is
shaped by data, and those who work with it, more than it has ever been
in the history of humankind, may we take this chance to grow not only in
skill but also in ethics, professionalism and humanity.

::: {#alexander-solzhenitsyn-in-the-first-circle .section .level1}
# Alexander Solzhenitsyn: *In the First Circle*

Solzhenitsyn's most famous books, such as *A Day in the Life of Ivan
Denisovich* and *The Gulag Archipelago*, deal with the every-day
privations of Soviet prison camps. *In the First Circle* is different:
its characters exist literally in a limbo (the 'First Circle' of Dante's
*Inferno* of the righteous but unbaptised souls), subject to repression
by the regime on one hand but due to their scientific knowledge, valued
as workers in a sharashka, a 'special engineering bureau' staffed by
prisoner scientists. In his Gulag books, Solzhenitsyn asks what it means
to be human in a system of calculated inhuman repression. In the First
Circle, his question is more specific: what does it mean to be a
scientist in an unjust regime, and what compromises a scientist should
not make, even if the cost is their freedom or their very survival. As
AI and ML is increasingly used by tyrannical regimes as a tool of
political repression, Solzhenitsyn's In the First Circle speaks as
loudly to today's data scientists as it did to the Soviet and Western
scientists who first read it in samizdat copies in the late 1960.
:::

::: {#thornton-wilder-the-bridge-of-san-luis-rey .section .level1}
# Thornton Wilder: *The Bridge of San Luis Rey*

Wilder's *The Bridge of San Luis Rey* might well be the first novel to
feature a data scientist (of sorts) as a protagonist -- the best part of
a century before data science as such existed. Brother Juniper, an
Italian monk in Peru, witnesses the collapse of an Inca rope bridge,
leading to the death of five people. He devotes his following years to
unraveling the mystery behind what seems random and senseless at first
-- why did these five people die, and why didn't others? What made them
special? He goes about this in much the same way as we would in any
current problem: by gathering information on the decedents, and try to
find what common factors set them apart. Wilder's book is about a lot of
things -- not the least fate, randomness and our innate expectation of
an ordered universe.
:::

::: {#david-halberstam-the-best-and-the-brightest .section .level1}
# David Halberstam: *The Best and the Brightest*

Robert S. McNamara was nicknamed the Electric Brain for his almost
preternatural grasp of quantitation. McGeorge Bundy was a foreign policy
prodigy. JFK inspired Americans in a way few other Presidents have,
before or after. The list goes on and on -- JFK's and later Lyndon B.
Johnson's cabinet was full of men of exceptional intelligence,
knowledge, education and sophistication. And yet, in the face of a
mounting crisis in Vietnam, they were worse than powerless: they
contributed the worst shortcomings of their thinking to the problem that
eventually embroiled America in a hopeless conflict. Halberstam's *The
Best and the Brightest* is a story of good people making bad decisions,
the psychological pitfalls of interpreting the world not as it is but as
we wished it to be to conform to our innermost prejudices. In the end,
the 'best and the brightest' of America, together with prodigious
amounts of information and data, missed the opportunity to prevent the
fall of South Viet Nam to the Communists. The drama of Vietnam played
out on the world stage, but the same cognitive biases Halberstam
describes are at work in boardrooms, data science teams and
decision-makers' offices every single day.
:::

::: {#frank-herbert-the-dosadi-experiment .section .level1}
# Frank Herbert: *The Dosadi Experiment*

Herbert's *The Dosadi Experiment* should be required reading in
Responsible Conduct of Research courses. The book deals with a perennial
question: is it ethical to allow an injustice to a small number of
individuals to continue if it protects an entire populated universe from
potentially disastrous upheaval? Because this is Frank Herbert, there's
a decent amount of trippy 1970s sci-fi stuff, including ego sharing,
tree bark like creatures that create FTL information transmission and
dogs bred to be semi-sentient items of furniture. Taking those curves as
they come, however, *The Dosadi Experiment* is a masterpiece, a
weird-but-wonderful meditation on the rights of the many and the rights
of the few, in a research ethics context.
:::

::: {#eric-schlosser-command-and-control .section .level1}
# Eric Schlosser: *Command and Control*

In 1980, a Titan II inter-continental ballistic missile of the US Air
Force suffered a liquid fuel explosion inside its silo near Damascus,
Arkansas -- with a nuclear warhead on top. Schlosser's book reveals that
this kind of incident was, unsettlingly, much less infrequent than one
might be comfortable with. What happens when the literal survival of the
planet depends on technology, and how comfortable are we in replacing
the human decision-maker -- often enough, a twenty-something 1st
Lieutenant in a missile silo's command centre -- with technology that
may run away from us? Schlosser's book is an impassioned plea for better
design of critical systems, presenting the near-disasters of nuclear
weapons -- which ought to be the epitome of safety engineering! -- as an
indication of all that can, and does, go wrong.
:::

::: {#quarto-appendix .default}
::: {.section .quarto-appendix-contents}
## Citation {#citation .anchored .quarto-appendix-heading}

<div>

::: {.quarto-appendix-secondary-label}
BibTeX citation:
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``` {.sourceCode .code-with-copy .quarto-appendix-bibtex}
@online{csefalvay2022,
 author = {Chris von Csefalvay},
 title = {Five Non-Data-Science Books for Data Scientists},
 date = {2022-04-13},
 url = {https://chrisvoncsefalvay.com/posts/five-non-data-science-books-for-data-scientists},
 langid = {en-GB}
}
```

::: {.quarto-appendix-secondary-label}
For attribution, please cite this work as:
:::

::: {#ref-csefalvay2022 .csl-entry .quarto-appendix-citeas}
Chris von Csefalvay. 2022. "Five Non-Data-Science Books for Data
Scientists." April 13, 2022.
<https://chrisvoncsefalvay.com/posts/five-non-data-science-books-for-data-scientists>.
:::

</div>
:::
:::