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’

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

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

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

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

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

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 do you do? The robots that are currently
deployed at the United Airlines lounge at SFO (one of
[these](https://www.reddit.com/r/unitedairlines/comments/10pdr0u/the_robots_arrived_today_at_the_new_ord_c_club/),
courtesy of [Bear Robotics](https://www.bearrobotics.ai)) thought
beeping, then bodying me with full military power was the right answer.
I'm not sure I agree.

::: {.page-columns .page-full}
(I'm fine. The robot's fine. This post isn't about that. I play a sport
that involves crazy strong people in wheelchairs that look straight out
of Mad Max ram into each other at full speed to let their violence out.
It takes a bit to dislodge me.)^1^

::: {.no-row-height .column-margin .column-container}
^1^ A few people have asked me for details on the incident. It really
wasn't even big enough a deal to report to the lounge stewards -- there
was no injury to me, no damage to the robot and overall no harm done.
The robot kept bumping into my chair and pushing against me as I was
trying to get out of the way, which of course made everything harder. I
was a little concerned that its frantic efforts might result in the
dishes it was carrying getting dislodged and falling on me, but
thankfully that didn't happen. It did, however, shine a light on the
lack of modern robotics' lack of understanding the needs of customers
with disabilities, and I am more than a little concerned by that -- not
everyone in a wheelchair is a 6'2 180lbs adaptive athlete. We can do
better than this. We *have* to do better than this.
:::
:::

The point is about this *modus vivendi* between humans and artificial
intelligences that we really haven't worked out adequately.

::: {#mental-models .section .level2}
## Mental models {.anchored anchor-id="mental-models"}

Humans aren't mind-readers... but they really, really want to be. We're
constantly trying to figure out what other people are thinking. Our
survival as a species has depended on it. The cost of this is worrying
what people think about us every time we enter a room. But the benefit,
oh, the benefit of it: we can create models of other people's minds, and
we can use those models to predict what they're going to do next. This
is a very useful skill to have when you're, say, hunting a woolly
mammoth. As you do.

This means that in trying to determine what to do next, we don't just
reason by some goal-directed reinforcement learning framework sitting on
top of some observations of reality. We create a model not just of
reality but of other minds, too.

Part of that is to understand what other minds do: their capabilities,
but also their limitations.
:::

::: {#your-fear-in-a-handful-of-dust .section .level2 .page-columns .page-full}
## Your fear in a handful of dust {.anchored anchor-id="your-fear-in-a-handful-of-dust"}

Consider, for instance, fear. A robot has about as little need, *ex
facie*, to understand that humans are afraid as it has for empathy to
understand that some people use a wheelchair and need some time to get
out of the way. A machine isn't mortal in the conventional sense. It has
had no need to develop the complex neurological-psychological responses
that, in excess, give us, say, a fear of heights (because *some* fear of
heights is definitely evolutionarily useful!).

Fear is not only a useful emotion to have, it's also something humans
*have*, like it or not. The consequence is that anyone and anything that
seeks to interact with humans has to understand that fact. If you don't,
you're collectively going to have a bad time.

::: {.page-columns .page-full}
And so, if a human is working on, say, a roof, they will reason from the
place the poet called "the unstill tremors of the fearful heart".^2^ A
machine working on its own on a roof can ignore fear as much as it
desires. A machine that seeks to interact with humans and live in human
society, however, cannot. And there's the rub. It's easy to create a
machine that does surgery. It's near impossible to create one to
*assist* in surgery. Interacting with humans is a tough call, and it's
not just because we're a bunch of weirdos (though that definitely
contributes).

::: {.no-row-height .column-margin .column-container}
^2^ Dyneley Hussey, who deserves to be known way more than he is.
:::
:::
:::

::: {#the-problem-of-other-minds .section .level2}
## The problem of other minds {.anchored anchor-id="the-problem-of-other-minds"}

A robot, then, doesn't have to understand that it has, or rather *is*, a
mind of a sort. But it absolutely has to understand that *other humans*
have minds of their own, and that those minds do and think stuff.

The problem of developing a theory of mind is one of those watersheds of
artificial intelligence that will have a clear before and after. There
isn't much room for gradualism here. A machine that can understand that
other humans have minds of their own is going to be one that will be
able to interact with other humans and live in some level of comity, and
one that doesn't, won't. This is the next big thing in AI, and it's
going to be a big thing indeed.

Or maybe I'm wrong. Who knows. I did just get bodied by a robot, after
all.
:::

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

<div>

::: {.quarto-appendix-secondary-label}
BibTeX citation:
:::

``` {.sourceCode .code-with-copy .quarto-appendix-bibtex}
@misc{csefalvay2023,
 author = {Chris von Csefalvay},
 title = {What {I} Learned from Getting Bodied by a Robot.},
 date = {2023-12-12},
 url = {https://chrisvoncsefalvay.com/posts/ai-human-interaction},
 doi = {10.59350/r8k9q-zdm06},
 langid = {en-GB}
}
```

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

::: {#ref-csefalvay2023 .csl-entry .quarto-appendix-citeas}
Chris von Csefalvay. 2023. "What I Learned from Getting Bodied by a
Robot." <https://doi.org/10.59350/r8k9q-zdm06>.
:::

</div>
:::
:::