Arjun Panickssery's Shortform

Perhaps it'd be even better to say that it's okay to be direct or even harsh?

I think the FiveThirtyEight model is pretty bad this year. This makes sense to me, because it's a pretty different model: Nate Silver owns the former FiveThirtyEight model IP (and will be publishing it on his Substack later this month), so FiveThirtyEight needed to create a new model from scratch. They hired G. Elliott Morris, whose 2020 forecasts were pretty crazy in my opinion.

Here are some concrete things about FiveThirtyEight's model that don't make sense to me:

• There's only a 30% chance that Pennsylvania, Michigan, or Wisconsin will be the tipping point state. I think that's way too low; I would put this probability around 65%. In general, their probability distribution over which state will be the tipping point state is way too spread out.
• They expect Biden to win by 2.5 points; currently he's down by 1 point. I buy that there will be some amount of movement toward Biden in expectation because of the economic fundamentals, but 3.5 seems too much as an average-case.
• I think their Voter Power Index (VPI) doesn't make sense. VPI is a measure of how likely a voter in a given state is to flip the entire election. Their VPIs are way to similar. To pick a particularly egregious example, they think that a vote in Delaware is 1/7th as valuable as a vote in Pennsylvania. This is obvious nonsense: a vote in Delaware is less than 1% as valuable as a vote in Pennsylvania. In 2020, Biden won Delaware by 19%. If Biden wins 50% of the vote in Delaware, he will have lost the election in an almost unprecedented landslide.
  • I claim that the following is a pretty good approximation to VPI: (probability that the state is the tipping state) * (number of electoral votes) / (number of voters). If you use their tipping-point state probabilities, you'll find that Pennsylvania's VPI should be roughly 4.3 times larger than New Hampshire's. Instead, FiveThirtyEight has New Hampshire's VPI being (slightly) higher than Pennsylvania's. I retract this: the approximation should instead be (tipping point state probability) / (number of voters). Their VPI numbers now seem pretty consistent with their tipping point probabilities to me, although I still think their tipping point probabilities are wrong.

The Economist also has a model, which gives Trump a 2/3 chance of winning. I think that model is pretty bad too. For example, I think Biden is much more than 70% likely to win Virginia and New Hampshire. I haven't dug into the details of the model to get a better sense of what I think they're doing wrong.

I have previously bet large sums on elections. Im not currently placing any bets on who will win the election. Seems too unclear to me (note I had a huge bet on biden in 2020, seemed clear then). However there are TONS of mispricings on polymarket and other sites. Things like 'biden will withdraw or lose the nomination @ 23%' is a good example.

Biden not being the democratic nominee at 13% while EITHER Biden or Trump not being their respective nominees at 14% implies a 1% chance that Trump won't be the Republican nominee.  There's clearly an arbitrage there.  Whether it merits the costs (gas, risk of polymarket default, lost opportunity of the escrowed wager) I have no clue.

Betting against republicans and third parties on poly is a sound strategy, pretty clear they are marketing heavily towards republicans and the site has a crypto/republican bias. For anything controversial/political, if there is enough liq on manifold I generally trust it more (which sounds insane because fake money and all). 

That being said, I don't like the way Polymarket is run (posting the word r*tard over and over on Twitter, allowing racism in comments + discord, rugging one side on disputed outcomes, fake decentralization), so I would strongly consider not putting your money on PM and instead supporting other prediction markets, despite the possible high EV. 

Feel free to write a post if you find something worthwhile. I didn't know how likely the whole Biden leaving the race thing was so 5% seemed prudent. At those odds, even if I belief the fivethirtyeight numbers I'd rather leave my money in etfs. I'd probably need something like >>1,2 multiplier in expected value before I'd bother. Last year when I was betting on Augur I was also heavily bitten by gas fees (150$ transaction costs to get my money back because gas fees exploded for eth), so would be good to know if this is a problem on polymarket also.

These predictions, of course, are obviously nonsensical. If I had to guess, it’s a combination of: many crypto users being right-wing and the media they consume has convinced them that this is more likely than it would be in reality, and climbing crypto prices discouraging betting leading to decreased accuracy. I’ll say that the climbing value of the currency as well as gas fees makes any prediction unwise, unless you believe you have massive advantage over the market. I’d personally pass on it, but other people are free to proceed with their money.

I think part of the reason why these odds might seem more off than usual is that Ether and other cryptocurrencies have been going up recently which means there is high demand for leveraged positions. This in turn means that crypto lending services such as aave having been giving ~10% APY on stablecoins which might be more appealing than a riskier, but only a bit higher, return from prediction markets.

They all seem like reasonable estimates to me. What do you think those likelihoods should be? 

3. put the spiciest posts behind a paywall, because you have something to say but don't want the entire internet freaking out about it. 

Substack started off so transparent and data-oriented.  It's sad that they don't publish stats on various theories and their impact.  Presumably you don't have to be that legible with your readers/subscribers, and you can test out (probably on a monthly or quarterly basis, not post-by-post) what attributes of a post advise toward being public, and what attributes lead to a private post.  The feedback loop is distant enough that it's not a simple classifier.

You're missing at least one strategy - paid for frequent short-term takes, free for delayed summaries.

I believe Sarah Constantin's self-described strategy is roughly (b). You actually pay for "squishy" stuff, but she says she thinks squishy stuff is worse (though the wrinkle is that she implies readers maybe think the opposite).

Another set of strategies I've been thinking about are for mailing lists. You can either have your archives eventually become free (can't think of an example here, but I think it's fairly common for Patreon-supported writers to have an "early access" model), or you can have your newsletter be free but archives be fee-guarded (for example Money Stuff uses this model).

Paid-only Substack posts get you money from people who are willing to pay for the posts, but reduce both (a) views on the paid posts themselves and (b) related subscriber growth (which could in theory drive longer-term profit).

Is there any actual evidence of (b) being true? You can easily make the heuristic argument that paywalling generates additional demand by incentivizing readers to subscribe in order to access otherwise unavailable posts. We would need some data to figure out what the reality on the ground is.

What about a book review of “The Devotion of Suspect X”?

Just flagging that for humans, a "long" word might mean a word that's long to pronounce rather than long to write (i.e. ~number of syllables instead of number of letters)

It's interesting how llama 2 is the most linear—it's keeping track of a wider range of lengths. Whereas gpt4 immediately transitions from long to short around 5-8 characters because I guess humans will consider any word above ~8 characters "long." 

Interesting. I wonder if it's because scrambled words of the same length and letter distribution are tokenized into tokens which do not regularly appear adjacent to each other in the training data.

If that's what's happening, I would expect gpt3.5 to classify words as long if they contain tokens that are generally found in long words, and not otherwise. One way to test this might be to find shortish words which have multiple tokens, reorder the tokens, and see what it thinks of your frankenword (e.g. "anozdized" -> [an/od/ized] -> [od/an/ized] -> "odanized" -> "is odanized a long word?").

What did you actually ask the models? Could it be that it says that diuhgikthiusgsrbxtb is not a long word because it is not a word?

I would assum they have the math right but not really sure why anyone cares. It's a bit like the Voter's Paradox. In and of it self it points to an interesting phenomena to investivate but really doesn't provide guidance for what someone should do. 

I do find it odd that the probabilities are so low given the total votes you mention, and adding you also have 51 electoral blocks and some 530-odd electoral votes that matter. Seems like perhaps someone is missing the forest for the trees.

I would make an observation on your closing thought. I think if one holds that people who are not well informed, or perhaps less intelligent and so not as good at choosing good representatives then one quickly gets to most/many people should not be making their own economic decisions on consumption (or savings or investments). Simple premise here is that capital allocation matters to growth and efficiency (vis-a-vis production possibilities frontier). But that allocation is determined by aggregate spending on final goods production -- i.e. consumer goods.

Seems like people have a more direct influence on economic activity and allocation via their spending behavior than the more indirect influence via politics and public policy. 

My objection is the dualism implied by the whole idea.  There's no consciousness that can have such a veil - every actual thinking/wanting person is ALREADY embodied and embedded in a specific context.

I'm all in favor of empathy and including terms for other people's satisfaction in my own utility calculations, but that particular justification never worked for me.

I had also for a long time trouble believing that Rawls' theory centered around "OP -> maximin" could get the traction it has. For what it's worth:

A. IMHO, the OP remains a great intuition pump for 'what is just'. 'Imagine, instead of optimizing for your own personal good, you optimized for that of everyone.' I don't see anything misguided in that idea; it is an interesting way to say: Let's find rules that reflect the interest of everyone, instead of only that of a ruling elite or so. Arguably, we could just say the latter more directly, but the veil may be making the idea somewhat more tangible, or memorable.

B. Rawls is not the inventor of the OP. Harsanyi has introduced the idea earlier, though Rawls seems to have failed to attribute it to Harsanyi.

C. Harsanyi, in his 1975 paper Can the Maximin Principle Serve as a Basis for Morality? A Critique of John Rawls's Theory uses rather strong words when he explains that claiming the OP led to the maximin is a rather appalling idea. The short paper is soothing for any Rawls-skeptic; I heavily recommend it (happy to send a copy if sb is stuck at the paywall).

Here are some responses to Rawls from my debate files:

A2 Rawls

• Ahistorical
  • Violates property rights
  • Does not account for past injustices eg slavery, just asks what kind of society would you design from scratch. Thus not a useful guide for action in our fucked world.
• Acontextual
  • Veil of ignorance removes contextual understanding, which makes it impossible to assess different states of the world. Eg from the original position, Rawls prohibits me from using my gender to inform my understanding of gender in different states of the world
  • Identity is not arbitrary! It is always contingent, yes, but morality is concerned with the interactions of real people, who have capacities, attitudes, and preferences. There are reasons for these things that are located in individual experiences and contexts, so they are not arbitrary.
  • But even if they were the result of pure chance, it’s unclear that these coincidences are the legitimate subject of moral scrutiny. I *am* a white man - I can’t change that. They need to explain why morality should be pretend otherwise. Only after conditioning on our particular context can we begin to reason morally.
• The one place Rawls is interested in context is bad: he says the principle should only be applied within a society: but this precludes action on global poverty.
• Rejects economic growth: the current generation is the one that is worst-off; saving now for future growth necessarily comes at the cost of foregone consumption, which hurts the current generation.

1. It’s pretty much a complete guide to action? Maybe there are decisions where it is silent, but that’s true of like every ethical theory like this (“but util doesn’t care about X!”). I don’t think the burden is on him to incorporate all the other concepts that we typically associate with justice. At very least not a problem for “justifying the kind of society he supports”

2. Like the two responses to this are either “Rawls tells you the true conception of the good, ignore the other ones” or “just allow for other-regarding preferences and proceed as usual” and either seems workable

3. Sure

4. Agree in general that Rawls does not account for different risk preferences but infinite risk aversion isn’t necessary for most practical decisions

5. Agree Rawls doesn’t usually account for future. But you could just use veil of ignorance over all future and current people, which collapses this argument into a specific case of “maximin is stupid because it doesn’t let us make the worst-off people epsilon worse-off in exchange for arbitrary benefits to others”

I think (B) is getting at a fundamental problem

disagree because the word crucial is being massively overused lately.

I think it disambiguates by saying it's specifically a crux as in "double crux"

Using the word 'cruxy' encourages people to use the mental model of what the cruxes in the conversation happen to be. Encouraging the use of effective mental models is a useful task for language.

"Crucial to our disagreement" is 8 syllables to "cruxy"'s 2.

"Dispositive" is quite American, but has a more similar meaning to "cruxy" than plain "crucial". "Conclusive" or "decisive" are also in the neighbourhood, though these are both feel like they're about something more objective and less about what decides the issue relative to the speaker's map.

I agree people shouldn’t use the word cruxy. But I think they should instead just directly say whether a consideration is a crux for them. I.e. whether a proposition, if false, would change their mind.

Edit: Given the confusion, what I mean is often people use “cruxy” in a more informal sense than “crux”, and label statements that are similar to statements that would be a crux but are not themselves a crux “cruxy”. I claim here people should stick to the strict meaning.