The Zebrafish Go To Eleven

One or both of you may already know about It’s a site of GARGANTUAN fun, run by Janelle Shane (Ph.D., I presume, though the site only mentions her Ph.D. studies. It doesn’t specifically say she received the degree and I know too many people who are ABD). Her day job is in optics research (probably playing with lasers, because don’t all those optics researchers play with lasers? Don’t they?), but in her spare time she

train[s] neural networks, a type of machine learning algorithm, to write unintentional humor as they struggle to imitate human datasets.

She’s done quite a lot of this from her places of residence and work, located on the occupied territory of the Arapahoe nation. She’s had computers create heavy metal band names. She’s had them write backstories for Dungeons & Dragons characters. Perhaps most successfully, she’s had them create names for racehorses (most successfully because racehorse names never make any sense, so it’s pretty difficult for a computer to foul up the task). She even attempted to go against type and have a neural network write intentional humor in an experiment where she fed the neural network the text of a large number of jokes and then had the network output its own. The results were NOT fractal. On one level of analysis, the results were clearly predictable. Yet on another level of analysis that clearly did not hold true:

What did the new ants say after a dog?
It was a pirate.

On the other hand, I feel the neural network might have paid me a compliment and/or summed up the inevitable aftermath of every single Jurassic Park movie:

What do you get when you cross a dinosaur?
They get a lawyers.

Important safety tip: Don’t cross the dinosaurs.

“But wait!” you exclaim if you have developed object permanence. “Wasn’t this all supposed to be about zebrafish?”

Why yes, astute reader. This post was and is all about zebrafish. You see, the most recent effort by Dr. Shane was to train networks to take the title of a list and the first few items on a list and then complete the list. For instance, in Olympic events, the 9th place medal is the Sigil of Destruction. Still, that’s better than finishing 11th and getting City Pollen. Shane also experiments with cake ingredients and anniversary gifts, but there is nothing the neural nets love so much as animals. Indeed it gleefully listed its favorite animals, if I am not gratuitously anthropomorphizing. (Fact Check: I am gratuitously anthropomorphizing.) Here you have the favorite animals of neural net GPT-2:

1. Giraffes
2. Maize
3. Polar Bears
4. Pigeons and Giraffes
5. Cats and Warthog
6. Javanese Canines
7. Tiger Teeth
8. Black Swans
9. Alligators
10. Basilisks

and, of course, number

11. Zebrafish




Trump Would Rather Have His Racism Than $20 In His Pocket

So, when redesigning the US$20 bill, the treasury department took a poll on the best person to next be depicted. You may remember that Andrew Jackson, the genocidal maniac who was critiqued by other slave holders for how cruelly he treated his slaves, graces your US twenties right now. Since the US has been notoriously bad at featuring women on its currency and since the new bill was due to come out in 1920, the anniversary of women gaining the right to vote in the US, and because US citizens have more sense than the government, the person selected to honor the new bill is Harriet Tubman… except the men couldn’t have a white guy replaced by a Black woman, so the new design was to keep Jackson, but move him to the reverse side of the 20 while putting Tubman on the front.

Creating a new bill is a time-consuming task, not least because after the old one has been out for a while, counterfeiters will have learned to mimic most of the features and the new bills, in addition to being durable in water, somewhat more tear resistant than most papers, and meeting US consumers’ subjective expectations that a bill seem “official” and not feel plasticky (which implies “fake”), new anti-counterfeiting techniques need to be designed into each new bill. Even when the person featured in the portrait does not change, the bills themselves do every so often and updating the counterfeiting countermeasures is a significant part of that. For this reason, the Treasury is literally in a constant state of research and development of new features that can be built into any new bills.

This time round, however, Steve Mnuchin, the US Secretary of the Treasury, has just told congress that despite the long lead time and the overwhelming poll support for Tubman, she will not appear on the $20 bill in 2020. Instead, Mnuchin suggests, 2028 is a more likely date. This would extend the current design to 25 years of use. We are already at 16, and the previous record for the longest use of a single design is about 15 years. In 2017 Mnuchin suggested that the Treasury might not release Tubman on the 20 because consumers become attached to particular persons on particular bills. This rationale was given despite the fact that the decision had already been made to keep Jackson’s image on the bill, if on the other side. But now, in 2019, Mnuchin has just announced that due entirely to needing to develop new anti-counterfeiting techniques, Tubman’s image cannot appear when originally intended.

The whole thing stinks, as I’m sure you’ve noticed. Take a moment to think and you’ll realize that even if no new anti-counterfeit measures were ready to be placed in the 2020 series bill, changing the design and keeping the current measures is better at challenging counterfeiting than doing nothing at all. So why delay?

The real answer we can only guess, but I have three good ones: 2020 is a Presidential election year, and not only does Trump idolize Jackson, but I think he’s also afraid that his racist supporters will be furious at him if his treasury department releases a $20 with a Black woman on it – no matter how many white men are on it with her. If enough of his supporters are racist (a reasonable proposition), then pissing off the racists will hurt Trump’s chances at reelection.

And so here we are, we can’t have nice things because

  1. Trump idolizes a genocidal maniac who embarked on the ethnic cleansing of indigenous peoples from the areas of US territories that were recognized states during his term, and generally from any economically valuable land,
  2. Trump’s supporters are too often racist to risk the US government promoting the picture of a Black woman during an election year, and
  3. Trump is his own racist supporter who doesn’t want to see a Black woman’s face on “his” money.

It’s amazing how Trump can combine the most obscenely consequential power grabs with the most trivial and petty exercises of that power.

PS. And will the Democrats call this out for the racism that it is? Of course not. We’ll get a few comments about how it’s disappointing that 100 years after the ratification of the 19th amendment we still have never had a woman’s portrait on US paper currency during a federal election in which women were entitled to vote. But they certainly won’t say anything about racism, or even about how Mnuchin’s assertions are literally irrational.


Pi = 3.2 says committee that is surely not at all drunk

Right, so. Many people here will have heard about Indiana’s attempt to legislate the value of pi. This was quite a long time ago, mind, but it’s still funny. I was just reminded of this by the delightful Pharyngula commenter Jaws. It inspired me to re-read an article from a couple years ago – before I started this blog. The story about the legislation is funnier than I remembered it.

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Overused Statistic #738: Mental Illness and Violent Victimization

So there’s a particular bit of overused truth whose use I want to challenge. Again, it’s not that it’s not true. AND it’s not that we shouldn’t be telling people that it’s true, BUT it seems to only ever be used in contexts where it doesn’t mean what people think it means.

Persons with mental illness are more likely to be victims of violent crime than to be perpetrators of violent crime. This is true.

Persons without mental illness are also more likely to be victims of violent crime than to be perpetrators of violent crime. This is also true.

But wait! How is that possible?

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“Not as bad as Alabama” is hardly the same thing as “good.”

So, for amusement I will periodically go catch up with my reading on the US-centric but still wildly funny law blog, “Lowering the Bar”. Recently they have been covering the case of a Judge in Texas who, because of a rarely-remembered but still operant clause in the Texas state constitution, had the misfortune of accidentally resigning the judgeship he won in an election only three months before.

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Stephen Moore: Not the Nominee Republicans Need

Before we start, I’m going to need to go into a bit about the Board of Governors of the Federal Reserve System of the United States of America (AKA the Federal Reserve Board). If you think you have enough context and just want to read about Stephen Moore, you can skip ahead to the “Now it gets interesting!” tag below.

Stephen Moore has been stealth-nominated by the White House for a position on the board of governors of the Federal Reserve System (AKA “the Federal Reserve”). Someone in such a position is called upon to make decisions about many things, but most often and most centrally decisions about the availability of credit in the United States. The Board of Governors’ principle tool to influence monetary policy is the ability to raise and lower the interest rate that banks must pay to borrow money from the Federal Reserve. Not only does this affect directly many interest rates for consumer and mortgage loans, but it also affects the total amount of money in the economy. For instance, if a bank has an opportunity to loan money out at a specific interest rate, but it doesn’t have enough to do so, it can borrow the money from the Fed at a low interest rate and then lend it out at a higher interest rate. This allows them to use the income from the higher interest customer loan to pay the interest they owe to the Fed and pocket the difference. But if the interest rate the Fed wishes to charge is high enough, the rate charged to the customer might be so high the customer does not want the loan or perhaps so high that the customer does not have credit sufficient to qualify for the same size load at that higher rate (the required monthly payments would be larger, and the customer many not be able to comfortably afford those higher payments, in the judgement of the bank, even if the customer believes they could).

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