Cornell Info Blogs

I'll see if I can't find a few of them so I can link them directly then. I certainly remember seeing a few.

As for the chilling effects, the problem with these things has always been a low visibility problem since you have no direct reference to compare against.

The nature is still an active area of research, the going understanding seems to be its a distortion of conformity to norms issue where views are distorted around actions you may signal under certain types of structures (uncertainty and ambiguity).

All you may see locally is skewed activity such as lower activity or less or no discussion in the words (regardless of meaning context) of posts signaled negatively in this way, very little disagreement.

You'd see more collective downvoting for neutral and any subjects related or touching on subjects signaled. Not enough for you to notice anything thought.

In many respects it follows a similar structure in education and reeducation under Mao, called the hot-potato, Lifton covers the details.

Objectively, you'd see higher downvotes, as well for anyone that did try to discuss these things, higher squelch marks, even neutral positions that may be tangentially related may lose speaking power/karma.

Unless you are running statistical analysis on a basket of subjects with a solid baseline, you likely wouldn't notice a thing, and that's by structure, which is why its insidious.

Certain structures of elements short circuit perception and take advantage of a psychological…

For people not aware of how computer chess engines work or what a tablebase is. TLDR: chess would be fully solved if there existed a 64-piece tablebase. These guys have done the chess world a massive favour by computing the most important subset of the 8-piece tablebase and making it available to the world.

Long version: Chess engines normally work by doing a highly optimised search of the game tree to some depth, evaluating the board position in each state using some evaluation function and then propagating the evaluation backwards up the tree. Then it’s a matter of picking the moves that lead to the game trees with the most favourable board state assuming both opponents make the best possible moves from the current position. The strength of the engine depends on the available computation, the efficiency of any tree pruning you’re able to do and the accuracy of the evaluation function, which is always going to be somewhat subjective.

However when “few enough” pieces remain on the board (in the endgame), the number of possible game states is small enough that it’s possible to brute force solve the game from each state by enumerating all possible moves and resulting states so as to find the absolute optimal move for any given board position. Looking up the evaluation and best possible move for a given state if you had done all this computation beforehand is obviously much more efficient and accurate than the tree-search minimax thing I described initially, and being able…

> I spent 10 years in mammography software, and I saw first hand how many outside factors can impact a physician's decision to biopsy or not a given artifact on an image.

This is slightly tangential, but I'm curious about your perspective on a classic example of medical statistical illiteracy. Whenever surveyed, the strong majority of doctors vastly overestimate the odds of a true positive mammogram (half of them by a factor of 10!!), due to flawed Bayesian thinking and the low base rate of breast cancer.[1]

Does your anecdotal experience contradict this data? If not, wouldn't two minutes of stats education (or a system that correctly accounted for base rate) utterly swamp intuition-driven analysis of tiny artifacts? Or is it simply that, through folk wisdom and experience, they implicitly adjust other terms in their mental calculus in order to account for this huge error in estimating one factor?

[1] https://blogs.cornell.edu/info2040/2014/11/12/doctors-dont-know-bayes-theorem/#:~:text=The%20probability%20that%20a%20woman,(%E2%80%9Cfalse%20alarm%20rate%E2%80%9D)

I think strategically they should encourage their voters to support whichever major party supports electoral reform (adopting a voting system that doesn't have the spoiler effect), and only vote third party if neither of them do.

In practice what this means is putting the Democrats on notice that they have to support RCV in every state, otherwise supporters of electoral reform will deliberately sabotage the party's chances and throw each election to the Republicans.

This is from the "don't mess with me! I'm crazy enough to do it!" school of thought, which worked so well against the "split or steal" choice given in a famous quiz show clip.[0] That game was deliberately designed to be equivalent to the Prisoner's Dilemma, just as the US voting system ends up being.

[0] https://blogs.cornell.edu/info2040/2012/09/21/split-or-steal-an-analysis-using-game-theory/

There are multiple facets to the problem. Technical site performance is a very small part of those.

The disruption, manipulation, and most of all erosion of trust which bad-faith actors create (AI or otherwise) are the most serious issues in my experience. The concept of "evaporative cooling", in which a platform starting to go bad sees an accelerated departure of well-intentioned, high-value participants.

See the original article from 2010: <https://web.archive.org/web/20101012105003/https://blog.bumblebeelabs.com/social-software-sundays-2-the-evaporative-cooling-effect/> (HN discussion: <https://news.ycombinator.com/item?id=1777665>).

And an interesting follow-up, 2015: <https://blogs.cornell.edu/info2040/2015/10/14/the-evaporative-cooling-effect-in-social-network/> (HN discussion, from 2025: <https://news.ycombinator.com/item?id=42597962>).

Assets that don't increase in value are "losing money", per economic theory. Homes are a low interest money sink. You can buy a home, hold it and get a decent return on your money.
You can also mortgage the home at low interest, and gamble that money for higher interest in stocks, etc. You can use rental income to offset your mortgage costs.

This is a perfect storm for pushing up costs and denying lower income Americans the ability to pay rent and buy homes.

citations:
https://blogs.cornell.edu/cradle/2019/02/11/what-the-federal-reserve-got-totally-wrong-about-inflation-and-interest-rate-policy-getting-real-about-rents/

https://www.forbes.com/sites/advisor/2020/07/28/fed-policy-has-kept-mortgage-rates-low-its-also-driving-up-home-prices/#1e6fa3a849c4