On Fri, Jun 12, 2026 at 4:20 PM Matt Mahoney <[email protected]>
wrote:

> ...My issue was about data. What data would you compress
>

>From the Hume's Guillotine README:
Yes, people can *and will* argue over what data to include or exclude --
but the Algorithmic Information Criterion traps the intellectually
dishonest by making their job much harder since they must include
*exponentially* much more data that is biased towards their particular
agenda in order to wash out data coherence (and interdisciplinary
consilience) in the rest of the dataset. The ever-increasing diversity of
data sources *identifies* the sources of bias -- and then starts predicting
the behavior of data sources in terms of their bias, *as* bias. Trap
sprung! This is much the same argument as that leveled against conspiracy
theories: At some point it becomes simply impractical to hide a lie against
the increasing diversity of observations and perspectives.
(and earlier)
Out of all so-called "Information Criteria" for model selection, the
Algorithmic Information Criterion is the best we can do in scientific
discovery of causality *relative to a given set of observations*. "Many
analysts, one dataset"
<https://www.socialjudgments.com/docs/Silberzahn_Uhlmann_Martin_et_al_in_press_Many_Analysts.pdf>,
the current best practice in meta-scientific research hence scientific
ethics, is one step shy of the Algorithmic Information Criterion for causal
model selection. That step? Understand that the best analysts will be able
to *losslessly compress* the "one dataset" best. This is how you make
competition fair, objective and optimal between schools of thought.



> to answer questions like "how many weeks after conception should
> *abortion* remain legal?" Or "what is the optimal *immigration* policy?"
>

Again from the README:

 the real world isn't *static* nor composed of disconnected systems that
have a single dependent variable like "*crime*" or "*poverty*".



> Even if clean data existed and Kolmogorov complexity was computable
>

Matt, this repeated mention of "computable" by someone of your stature is
really quite disturbing.  I repeat:  No one has ever asked a scientist to
*prove* that his theory is the best of all possible models relative to all
data under consideration.  Don't you understand why I always say the same
thing in response to the "uncomputability" of Kolmogorov Complexity?  Do
you think it doesn't pertain to that issue?  Why must I repeat myself on
this?  Why isn't it glaringly OBVIOUS?

My take:

There is an institutional block against being held to account by an
objective metric.  Why?

No conspiracy is required.  All that is required is the incentive and
everything self-organizes around the goal:  Promote specious pedantry like
this "uncomputable" trope and hope no one notices you have no clothes!



> , the output is still just a few bits. Your choice of the language
> dependent constant could give you whatever answer you wanted.
>

The solution to both of these objections is an inevitable consequence of
the prior passage about incorporating data from a variety of competing
sources.  The "many analysts one dataset" projects are a small step toward
such transparency.  With a proper scale of data (which The Laboratory of
the Counties
<https://github.com/jabowery/HumesGuillotine/tree/master/LaboratoryOfTheCounties>
may or may not provide -- I'm in the midst of determining that -- but in
any case, it is only there to point the way) the KC of THAT dataset would
dwarf the Hutter Prize "constant" choice of UTM fiction (ie: x86
instruction set).

 We should be worried. I just saw a study showing fertility collapse
> coinciding with the introduction of the iPhone around 2009. This is going
> to accelerate with the introduction of artificial people.
>

I agree but that's only a proximate cause over which we can argue until
we're turned to protoplasm by the hypersonic tsunami.  When I say "we" I
mean to poiont to people like Raj Chetty and his proprietary access to
government data.



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