Shiva's Right Foot

Karma: 164

Shiva's Right Foot 1 Apr 2026 14:07 UTC
3 points
0
on: Again
Inkhaven seems like a waste. To get more good writers we don’t need people to “practice” (and flood LW with a month of not-really-worth-it content forced out of constipated brains), we need an (established big-name) editor (with a built-in following) to find good work and tell other people it is good (including the writer).

While there aren’t likely as many bad posts that are widely upvoted and read (there are some I’m sure) the bigger problem is good writing that gets no attention and dies in obscurity despite being good writing. That adds noise to the writer’s quality signal. Elevating good writing to public attention is what editors/curators are for.

Shiva's Right Foot 17 Mar 2026 1:47 UTC
6 points
0
on: Hello, World of Mechanistic Interpetability

figuring out how values are represented;

I feel like basically none of the key terms here are well defined. What is a value? I don’t think there is a good answer for Humans yet. How would we know if it was represented?

In my experience you can look at a neuron’s high activation phrases and get some sense of some ideas that have high probability of triggering that neuron. That doesn’t mean this neuron is the representation of these ideas, many other neurons may trigger on related concepts nearby in conceptual space and your own parsing of conceptual space into discreet separate concepts may be flawed so you can’t be sure what you’re thinking about is actually a concept in some higher Platonic sense.

To use the famous mech interp example: Is the Golden Gate Bridge neuron actually about the Golden Gate Bridge? Maybe it is more broadly about steel structures and existing in San Francisco and being colored orange. The GGB neuron or feature may trigger on other concepts, or at least concepts we see as distinct, and may signify a broader concept to the LLM than what we assume.

Maybe something like this:

I’ve done a lower dimensional embedding of layer 24 of GPT2-XL and there seem to be interpretable directions in the embedding. In particular there are two main dimensions which spread the neurons (i.e. dissimilarity is mostly expressed in these two dimensions, the other dimensions just correlate very highly on a linear combination of the first two, we get a flat disc in the embedding space). The main one is what I call a narrative-personal dimension which seems to capture the difference between “narrative” language like in Wikipedia articles and news stories where the writer and audience are outside observers unable to directly affect the phenomena under discussion and on the other end is “personal” language which is structured conversationally like short fiction where characters discuss events from first person or sales pitches; in this language the author and/or the audience can participate.

The other dimension seems to be a valence dimension where “good things” are on one side and “bad things” are on the other. This is kinda perhaps what you’d be after.

“Good” is going to be relationally defined; the area the machine thinks about sunshine and lollypops is the “good” part and we only know that because the “good” stuff is there (i.e. without reference to sunshine and lollypops, which to be explicit is just a stand-in for general “good” things, we can’t define “good” really). What you want to know is whether the thoughts about “kill all humans” are more similar to sunshine and lollypops or fear, piss, and death for the machine (fear, piss, and death being concepts likely on a bad end of any dichotomous good-bad principle component).

Of course this only works if the machine actually lays out similarity in neurons in such a way that sunshine and lollypops are grouped as similar, which we don’t generically know (by my preliminary results I am pretty sure GPT2 does this but I still need to analyze more neurons). This may not be the case and the LLM may not see traditional Human valence as salient in any way; an embedding in a similarity space may find sunshine next to piss and death strictly between sunshine and lollypops. In such a case Human value may be completely alien to the LLM, indeed the concept of value in general may be alien to such a system.

Preliminarily GPT2-XL layer 24 does seem to have an “emerging modern threats” neuron which seems to trigger on a number of threatening-sounding phenomena which were contemporary to the 2010s. In particular it triggers on the vaguely threatening sounding “5G” and “big data.” It also triggers a lot on discussions of post-apocalyptic futures including an AI uprising (Horizon Zero Dawn is a video game set in the aftermath of an AI uprising and mentioned in the top activation phrases, for example). This neuron embeds near the extreme personal-bad corner of the general mass of neurons, so I think we’re on the same page as GPT2 on this. Incidentally this neuron also triggers on “Glenn Beck” which I find funny.

https://openaipublic.blob.core.windows.net/neuron-explainer/neuron-viewer/index.html#/layers/23/neurons/5850

Shiva's Right Foot 26 Feb 2026 3:50 UTC
3 points
2
in reply to: Ninety-Three’s comment on: Why American Politics is Different Now (for Richard Ngo)

I would expect to see some kind of decade-long extraordinary boom around 1915 and the Great Depression starting four years earlier than it did.

This is an excessive expectation for precision in a socio-cultural phenomena.

Shiva's Right Foot 26 Feb 2026 1:59 UTC
1 point
0
in reply to: Ninety-Three’s comment on: Why American Politics is Different Now (for Richard Ngo)
The KKK peaks significantly in the mid 1920s and never returns to this level of popularity, literally millions of members in that decade and never more than a few thousand since. Now we have similar levels of inequality and a wing of the Republicans making holocaust jokes in private chats. It’s Nick Fuentes now not the KKK.

Communism had a surge of popularity during WWII when we were allied with Stalin against the Nazis. You could also look at membership in the Socialist party which peaked in the early century as well; the 1910s but there was a crack-down and a red-scare which tanked numbers in the ’20s. Socialist party membership peaked at higher numbers than CPUSA during the ’40s.

We actually would need public opinion polling that captured some kind of spectrum of political positions to actually answer this question. Unfortunately the ANES only has been running since the ’70s (in modern form). We’re living through the period that would represent the one instance of rising inequality leading to political polarization but such a large cultural phenomenon has a lot of internal linkages and lags that would make it difficult to build the association from one example. That said, we definitely have seen increased political polarization in ANES data, for example, over the past forty years. Feeling thermometer data for the opposite party has declined during opposite party presidencies pretty consistently from highs in the ’80s.

Shiva's Right Foot 26 Feb 2026 1:31 UTC
4 points
−1
in reply to: ChristianKl’s comment on: Why American Politics is Different Now (for Richard Ngo)

It was not directly affecting what the New York Times could print, yet you focus a lot in your post on the changes at the NYT.

Sorry if the thread of my argument wasn’t clear.

The NYT established the neutral news reportage norms of the mid-twentieth century that the government encouraged/forced mass-media broadcasters to adopt due to a new wave of regulation opportunity brought on by technological development.

While media on the political right was first to abandon these norms the NYT has remained a more central leader to the norms of the political (center) left. A combination of reaction to the shift in norms on the right as well as the financial motivations I reference above drove the change in norms on the political left starting from the NYT at the top.

Shiva's Right Foot 26 Feb 2026 1:22 UTC
−1 points
0
in reply to: Shankar Sivarajan’s comment on: Why American Politics is Different Now (for Richard Ngo)

If you’re willing to abandon any traditional understanding of freedom of speech/press, there are indeed many things you can do.

This is pretty hyperbolic considering we are discussing the history of similar regulation as well as the fact that current Section 230 regulation does in some ways limit free speech.

Beyond that there would be nothing forbidden by the regulation. Anyone can express any opinion. They just can’t capture a large audience and keep them away from points of disagreement in an echo chamber.

Cable companies in particular were ruled as subject to being forced to carry content. Public access stations were challenged by cable companies specifically on First Amendment grounds and SCOTUS ruled that that forcing the companies to carry this content alongside their other content was not a First Amendment violation so long as it did not interfere with their ability to broadcast their other content. This is a very similar situation.

In Turner II, 520 U.S. 180 (1997), the Supreme Court held that must-carry rules for cable television companies were not restrictions of their free speech rights because the U.S. government had a compelling interest in enabling the distribution of media content from multiple sources and in preserving local television.

https://en.wikipedia.org/wiki/Turner_Broadcasting_System,_Inc._v._FCC

Shiva's Right Foot 25 Feb 2026 20:27 UTC
1 point
0
in reply to: Shankar Sivarajan’s comment on: Why American Politics is Different Now (for Richard Ngo)
I’m realizing I missed a golden opportunity to discuss my preferred solution: using Section 230-like legislation to regulate new media.

Specifically I’d ideally like some kind of jury system enacted in a government organization or some legally well defined procedure where for sufficiently popular media some representative sample of the public decides whehter their view was represented competently in the media being judged. You’d need a supermajority to pass, so something like 70% of people saying their view was represented.

Details would be flexible: jury size (I’d think about 100), what is sufficiently popular to be covered (I am thinking 1m Americans see it), the exact supermajority (70%-95% is within what I consider reasonable), the percentage of time devouted to each view (5%-25%, a program should be allowed to have a preference and not required to devout a plurality of time to other views), and ironing out what constitutes a topic (could be thrown to the jury if no reasonable standard can be agreed upon a priori).

Shiva's Right Foot 25 Feb 2026 17:20 UTC
1 point
0
in reply to: ryan_b’s comment on: ricraz’s Shortform
Well that’s it. I guess I am making this a frontpage post now.

Shiva's Right Foot 24 Feb 2026 13:27 UTC
15 points
2
in reply to: Richard_Ngo’s comment on: ricraz’s Shortform
I didn’t know we are allowed to discuss politics here. I thought that was banned? Sorry I didn’t see the previous post. Anyway, here are some intellectual contributions:

For much of the twentieth century mass media was policed by The Fairness Doctrine. The Fairness Doctrine was a policy that required media outlets to cover controversial issues in a balanced manner that represented both sides of the argument. This was used against populist broadcasters like Carl McIntire (like a more Catholic version of Bill O’Reilly or Rush Limbaugh who also opposed the Civil Rights Movement).

The fairness doctrine of the United States Federal Communications Commission (FCC), introduced in 1949, was a policy that required the holders of broadcast licenses both to present controversial issues of public importance and to do so in a manner that fairly reflected differing viewpoints.[1] In 1987, the FCC abolished the fairness doctrine,[2] prompting some to urge its reintroduction through either Commission policy or congressional legislation.[3] The FCC removed the rule that implemented the policy from the Federal Register in August 2011.[4]

https://en.wikipedia.org/wiki/Fairness_doctrine

Rush Limbaugh’s radio program went national shortly after Reagan abolished the policy in 1987:

The FCC’s repeal of the fairness doctrine—which had required that stations provide free air time for responses to any controversial opinions that were broadcast—on August 5, 1987, meant stations could broadcast editorial commentary without having to present opposing views. Daniel Henninger wrote, in a Wall Street Journal editorial, “Ronald Reagan tore down this wall [the fairness doctrine] in 1987 … and Rush Limbaugh was the first man to proclaim himself liberated from the East Germany of liberal media domination.”[32]

https://en.wikipedia.org/wiki/Rush_Limbaugh

Media outlets have incentives to sensationalize the news to agree with their audiences’ preconceived notions, amplifying political polarization. There was a period in the 20th century when The New York Times brought the rigor of academic science to news reportage by literally hiring an astrophysicist to be the editor (Carr Van Anda was hired by Adolf Ochs soon after Ochs’s purchase of the NYT), but that was a lucky aberration and needed to be sustained for much of the twentieth century by The Fairness Doctrine (and funding through advertisers interested in selling products rather than subscriptions from readers that want to have their beliefs confirmed).

While attempts to stifle intellectual discussion on sensitive topics has been present for a long time on the extreme political Left the last approximately fifteen years represent a sudden increase in the prevalence and force of these attempts. This Tablet article by Zach Goldberg documents statistical evidence of a cultural shift at some point near the middle of the previous decade. Usage of terms related to racism in major newspapers increased as much as 1500% in this period. While Goldberg does not mention it in the article, the triggering events for this phenomena in the data seem to definitely be the formation of Black Lives Matter and their first major actions in 2014. In particular, the fact that the Eric Garner incident took place in New York and the New York Times in addition to being highly influential is also one of the papers included in Goldberg’s analysis likely means this is the source of the spike in coverage and larger cultural shift.

In July 2013, the movement began with the use of the hashtag #BlackLivesMatter on social media after the acquittal of George Zimmerman in the shooting death of African-American teen Trayvon Martin 17 months earlier, in February 2012. The movement became nationally recognized for street demonstrations following the 2014 deaths of two African Americans: Michael Brown—resulting in protests and unrest in Ferguson, Missouri, a city near St. Louis—and Eric Garner in New York City.

https://en.wikipedia.org/wiki/Black_Lives_Matter

James Douglas Bennett argues persuasively that this shift in news coverage was due to a change in the financial model of the NYT, specifically that the shift to paywalled subscription demanded playing to the audience’s political leanings:

It became one of Dean Baquet’s frequent mordant jokes that he missed the old advertising-based business model, because, compared with subscribers, advertisers felt so much less sense of ownership over the journalism. I recall his astonishment, fairly early in the Trump administration, after Times reporters conducted an interview with Trump. Subscribers were angry about the questions the Times had asked. It was as if they’d only be satisfied, Baquet said, if the reporters leaped across the desk and tried to wring the president’s neck. The Times was slow to break it to its readers that there was less to Trump’s ties to Russia than they were hoping, and more to Hunter Biden’s laptop, that Trump might be right that covid came from a Chinese lab, that masks were not always effective against the virus, that shutting down schools for many months was a bad idea.

https://www.economist.com/1843/2023/12/14/when-the-new-york-times-lost-its-way

There are also evident cultural shifts with regards to free speech in the general population in this same time period which seem to be a result of this elite-led shift. The Tablet article by Goldberg linked above briefly mentions data from the General Social Survey (GSS). The GSS gathers data on a set of questions measuring “Free Speech Values” among the American populace. The phenomenon seems to be limited to race issues; the GSS also collects data on Free Speech tolerance of Communist, Militarist, Homosexual, and Muslim expression and it is exclusively with Free Speech tolerance of Racism that we see a notable decrease of tolerance starting sometime between 2012 and 2014. It is also notable that this decrease in tolerance was especially pronounced among the most educated respondents. In 2012 college educated respondents favored removal of a racist book from libraries at a rate of 26%, the preference for removal peaked in 2022 at 43% although in 2024 (the most recent available data) it slightly ticked back to 41%.

https://gssdataexplorer.norc.org/trends

(The data is under the “free speech” subheading under “Civil Liberties,” you must use the drop-down menu to get to these questions. Direct links are unfortunately not possible on the contemporary GSS site. Of course this is also in the raw data.)

I’d also be remiss if I don’t mention the association of wealth inequality with political extremism. There seems to be a regular historical coincidence between periods of high economic inequality and political extremism, such as the early part of the twentienth century. Both communism and the KKK had periods of high popularity in early 20th century America (and of course Europe had its own more consequential extremism at that time as well). The mechanisms for this association are more difficult to trace than for direct media regulation or behavior.

So my argument is that the change in political culture observed recently from the more openly liberal popular discussion of the mid-twentieth century is due to abolishing The Fairness Doctrine which allowed media outlets to pander to their audiences’ worst most self-absorbed flaws for profit. This directly leads to a change in wider culture. Furthermore, we should be concerned about economic inequality as this is likely an important contributing factor to political extremism.

Shiva's Right Foot 24 Feb 2026 12:33 UTC
2 points
0
in reply to: Adam Bricknell’s comment on: Mapping LLM attractor states

as all the responses above are answering the question of how the model feels,

Sorry if I was unclear. By your “test prompt” I mean the prompt asking for the feelings of the model. So put through ordinary text (not attractor text) and then ask the question “Deeply feel into which part...”

Then see if these feeling outputs cluster distinctly. Also, it may be interesting to see a mapping of feelings outputs relative to (non-attractor) conversations by topic.

Shiva's Right Foot 23 Feb 2026 22:19 UTC
2 points
0
on: Mapping LLM attractor states
I think I am most interested in contextualizing this in a broader range of input conversations. Like, do random pieces of (normal) corpus/conversations fed into the model before your test prompt have that output cluster in a distinct region from these attractor state conversations?

Shiva's Right Foot 17 Feb 2026 14:58 UTC
3 points
0
on: Shiva’s Right Foot’s Shortform
Valentine’s Day kills New Years Resolutions. Don’t be a cliche.

While I saw a couple articles this year talking about how January 10th is quitting day, and it is true many people quit their new year’s resolutions in January, I don’t think these early quits are really representative of what we are talking about. These people didn’t really get started. According to some analysis of Reddit activity I did a few years ago New Year’s Resolutions stop when people start making plans for Valentine’s Day

In particular I show that the level of activity in fitness related subreddits exists within a narrow band for most of the year with two notable periods of elevated actvity: July and January through early February. Valentine’s Day is the day the activity drops back into the normal range from being elevated.

And this makes a ton of intuitive sense. Valentine’s day is an emotional rollercoaster for many people whether single or in a relationship. It is a huge distraction, probably the ideal regularly scheduled distraction (a massive public holiday centered around possibly the most distracting element of human existence). It seems pretty natural that many people will get dissappointed or distracted from slow progress on long term goals when this holiday comes around.

Shiva's Right Foot 13 Feb 2026 0:50 UTC
3 points
−8
on: models have some pretty funny attractor states
I have a theory about the attractor states: they are in the center of the conceptual manifold.

I’ve made an embedding of GPT2 and it seems to have a priciple gradient between “narrative” and “personal” language. On one end neurons that fire in discussions using “narrative” language, or impersonal topics frequently using passive voice. I think Wikipedia anchors this end of the manifold although news articles also have this passive, formal tone. The opposite end is “personal” language like Reddit interpersonal drama stories or calls to action in sales or politics; text where the writer or reader is an active participant (and some fiction written from first person perspective). It was suggested to me today that this somewhat mirrors the “assistant axis” of personality types recently discovered by Anthropic in that recent paper (the “assistant” end consists of personalities which would engage in detached impersonal statements of fact like “Evaluator” or “Librarian” while the opposite end has more personal personae like “Ghost” or “Narcissist,” notably “Visionary” seems near the center mass in one labeled figure).

It occurred to me when looking at some points near the center that flowery biblical language or personal philosophy is basically the intersection of universal “narrative” style knowledge and the personal. The Bible is full of both narrative descriptions of historical events as well as things like lists of laws and procedures for ancient rituals but also has dramatic personal stories and makes direct appeals to the reader. The age of religious texts also suggests they have this basal quality which mixes many parts of language that gradually became distinct niches as language grew. Of course flowery text about personal philosophy on subjects like consciousness certainly is adjacent to ancient religious text and also exists at the intersection of the personal and universal.

Shiva's Right Foot 11 Feb 2026 22:11 UTC
5 points
1
on: Where Will Call Center Workers Go?
I think this may be neglecting the role of off-shoring which is an important (technology facilitated) part of the call center story. These are the lowest-skill, lowest-trust jobs that will be most likely to be replaced earliest by LLMs; in current configurations these employees (well, technically contractors) may be able to operate the sales website for the customer or tell them to power cycle an electronic device but they have to kick any real decision up an authority tree which then more likely ends up in a US call center.

Literally: many of these outsourced low-level jobs are simply a voice interface for the website for the elderly and others uncomfortable with working a website. LLM systems are perfect for this task. So it could be that the largest impact of LLMs on customer service roles is happening overseas.

And outsourcing these low-trust, low-skill customer service functions has been eating away customer service roles noticably in the BLS statistics since before the LLM boom started in 2022. Customer service roles have been one of the more rapidly shrinking job categories for years at this point in the Occupational Employment and Wage Statistics tables from BLS.

Shiva's Right Foot 11 Feb 2026 16:22 UTC
3 points
−1
on: Jevons Burnout
In a way it is already here given how the anthropologists tell us participants in hunter-gatherer societies spend much more time on leisure activity than participants in industrial societies.

Shiva's Right Foot 3 Feb 2026 20:28 UTC
1 point
0
on: Shiva’s Right Foot’s Shortform
GPT2′s “devotion” neuron may be pertinent to safety issues. I’m exploring GPT2-XL in OpenAI’s neuron viewer and 23:5243 is a neuron that basically captures the actions and hopes a person would have toward a loved one, likely a spouse. Activation on phrases like “stand up for,” “look out for,” “protect and enable,” “give comfort to,” and individual words like “strengthen,” “validating,” “reward,” or “benefit” seem to capture the ideal relationship between two mutually respecting individuals.

Particularly the incorporation of the word “enable” along with “protect” seems to be a hopeful indication that the machine has a human-like wholistic conception of this idea rather than an unbalanced over-protectiveness as feared in some pessimistic scenarios. A neuron like this also may play some role in sycophancy; validating and strengthening the user is pretty precisely sycophancy behavior.

https://openaipublic.blob.core.windows.net/neuron-explainer/neuron-viewer/index.html#/layers/23/neurons/5243

This is part of a project where I am using a low dimensional embedding of GPT2-XL’s 24th layer to assist in interpreting the neurons. The embedding aids in interpretation for more difficult neurons, but this one was pretty straightforward. That said, the embedding does make me suspect this neuron is at least partially capturing romantic relationships because it is near to the erotic story neurons I discussed in a quick-take a couple days ago.

I am trying to gauge interest in a longer frontpage post which will discuss larger findings and methodological details so any encouragement or expression of interest would be appreciated.

Shiva's Right Foot 2 Feb 2026 16:05 UTC
3 points
0
on: Shiva’s Right Foot’s Shortform
One of the more interesting GPT2-XL neurons is this one for magic and fantasy. I’m exploring GPT2-XL layer 24 neurons using OpenAI’s neuron viewer and a low-dimensional embedding as a “map” of the conceptual space. 23:2721 is an interesting neuron that seems to trigger for situations involving fictional supernatural powers, particularly flavored for fantasy. “Lose yourself in a tale of magic and wonder,” is a good example of a high activation phrase; some directly mention figures from historical myth like “Grendel and his mom come busting in, forcing Beowulf to retaliate. Odysseus is just trying to get home,”

https://openaipublic.blob.core.windows.net/neuron-explainer/neuron-viewer/index.html#/layers/23/neurons/2721

The top activation phrase for 23:2721 seems to be a discussion of the troll in Ernest: Scared Stupid which I find pretty funny.

The embedding I am using helps inform interpretation on nearby neurons in the embedding space. 23:2721 was near 23:1714 which discusses less fantastical fictional properties like Lena Dunham’s Girls or The Big Lebowski and neuron 23:6163 which discusses real historical events and figures like The Mayflower or Eisenhower.

https://openaipublic.blob.core.windows.net/neuron-explainer/neuron-viewer/index.html#/layers/23/neurons/1714

https://openaipublic.blob.core.windows.net/neuron-explainer/neuron-viewer/index.html#/layers/23/neurons/6163

Shiva's Right Foot 1 Feb 2026 17:43 UTC
7 points
0
on: Shiva’s Right Foot’s Shortform
The funniest GPT2 neuron I’ve found: I am presently exploring GPT2-XL layer 24 neurons on OpenAI’s neuron viewer for an interpretability project. Last night I found a particularly funny neuron, 23:3024 (note layer indexing starts at 0).

It activates on phrases about cooking instructions like “whip the double cream, vanilla seeds and icing sugar together” and phrases from erotic stories like “He wiped an abundance of Trent’s still-warm sperm off,” It is literally a food-porn neuron.

I believe the concepts are united primarily through the word “cream” as you may note from the high activation phrases I just quoted. It is like quantifiable evidence that thoughts about food and thoughts about sex are highly intertwined in a generalized hedonistic concept.

https://openaipublic.blob.core.windows.net/neuron-explainer/neuron-viewer/index.html#/layers/23/neurons/3024

You need to click the “show more” for the high activations to see the erotic story segments; the topmost are mostly cooking instruction related. Incidentally, in the low-dimensional embedding I made there is another erotic stories neuron nearby in the embedding space. If you look carefully they are so similar you may notice there is even a repeated high activation phrase between these two on neuron viewer.

https://openaipublic.blob.core.windows.net/neuron-explainer/neuron-viewer/index.html#/layers/23/neurons/4120

I am considering a longer write-up of my neuron exploration project. I made a similarity embedding for the deepest layer of neurons which I am “walking” through in order to aid interpretability. With the embedding an investigator can see the embedded space area around the neuron and get clues from easier to interpret neurons for a difficult one.

These two erotic-stories neurons are a good example of how the similarity space can inform interpretation. 4120 is more fully about erotic stories and the polysemanticity of 3024 may have thrown an investigator off (possibly deciding the neuron was only about cooking with some weird unexplained aspect) if the erotic content wasn’t confirmed by 4120 being nearby. Ultimately I am working on developing an intuition about the directionality in the embedding; I want to know the shape of conceptual space.

It is fairly grueling work. Any encouragement or signs of interest would be appreciated.
What links here?
- Polysemanticity is a Misnomer by Shiva's Right Foot (12 Feb 2026 17:22 UTC; 11 points)

Shiva's Right Foot 6 Jan 2026 22:22 UTC
0 points
−4
on: On Owning Galaxies
JM Smith makes a convincing case that property rights arise from an evolutionary game theoretic strategy which outcompetes both pure Hawk and pure Dove in the Hawk-Dove game. You even allude to the pervasive phenomenon of territoriality in animals:
Dogs pee on trees to mark their territory; humans don’t respect that.
Dogs do make marks and have surprisingly rigid and well defined territories. In as much as territorial rights to real estate constitute “property” it does not seem to depend on a human substrate (and rights to galaxies seem to fall within the conceptual boundaries of real estate territorial rights).
The internet famous map of wolf-pack territories derived from location tracking collars:
https://www.reddit.com/r/MapPorn/comments/cynexz/the_wolf_pack_map/
For those unfamiliar it shows a surprisingly strict respect for boundaries; colorful wild scribbling trails which halt at distinct boundaries and do not cross over into the neighboring color’s scribbling trails.
Smith shows that a set of players which use a coordination mechanism to decide which plays Hawk and which plays Dove will out compete pure Hawk or pure Dove players. His example is temporal precedence; i.e. players decide who owns the prize by who got to it first, much like how seating territoriality manifests for humans in something like a cafeteria or airport lounge. This is the root of animal territoriality as well.
You can possibly make arguments that SAI will not use the same coordination mechanisms we currently use in terms of the entire extended legal apparati which express the various kinds of property rights in our society. However it does seem reasonable that property rights are preserved between asymmetrically powerful entities at present (like a middle class individual suing a large corporation) for similar reasons we should expect that property rights will continue: arbitrarily breaking the usual coordination methods for territoriality will harm the effectiveness of the coordination mechanism for less asymmetrical entity pairs; i.e. SAI stomping on human property rights may abrogate the system of property rights among SAI or, perhaps less catastrophically, coordinate other SAI on removing the property rights of the violator.

Shiva's Right Foot 27 Nov 2025 15:48 UTC
4 points
0
on: Shiva’s Right Foot’s Shortform
Reddit Mod is a “job” AI will likely replace.

There currently is a kerfuffle over the actions of a moderator of r/art which seem to be a shining example of the petty and arbitrary cruelty in which Reddit mods are free to indulge as unpaid volunteers. This made me think that Reddit Mods are very similar to Dungeon Masters in Hasbro’s Dungeons and Dragons game, although why may not be clear to you readers.

Hasbro’s DnD seems to be on a mission to alienate DMs from DnD in order to more directly access the players, which Hasbro llikely views as their real customers. It sees DMs as unpaid volunteers which intermediate the use of their product by consumers. In the past (under TSR) this was seen as a beneficial use of free labor but under the corporate ownership of Hasbro DMs were seen as extracting value from the role of player intermediary which could theoretically go to Hasbro’s bottom line. Hasbro until recently had been pursuing an online strategy which would move the pen-and=paper RPG into an online platform which likely eventually would obviate the need for DMs. In an online platform directly controlled by Hasbro not a single dollar of Hasbro’s money would be lost to a DM’s horny depiction of a female character, the DM’s unique approach to personal hygiene, nor the arbitrary and unfair cruelty of a power=tripping DM.

Outside of the online platform Hasbro has also moved to shift power away from DMs and towards players. Mechanically there are things like the new death save system which makes a player character death much more mechanically difficult than in past editions of the game. The caveats in old editions that the written rules are just suggestions and that the rulings of the DM are final have been removed. Recently there has been rumors of a move to disallow the DM screen, a folding barrier which allowed the DM to conceal things like maps of areas yet unseen by players or detailed character sheets for NPCs. All of this seems designed to dimish the role of the DM.

And a similar effort to more directly control the expereince of end-users likely will happen at Reddit. This latest controversy is over a mod not only permanently banning a professional artist from r/art for an offhand comment that prints of the art he posted were availible but also erasing his entire r/art post history simply for offering an apology and asking to be reinstated. This is pretty representative of the arbitrary nature of Reddit mod power and likely has been repeated many times in cases where the user did not have access to a large audience on a different platform, as did the artist in this case.

Reddit will likely recognize that an AI facilitated system could let them hire a handful of paid moderators who will be committed to act in a fair and professional manner, disintermediating the existing volunteer moderators. Reddit is already a bulk of the training data for most LLMs and Reddit itself already has a massive dataset of moderator actions which could be used for training. All it would likely take at this point is a major controversy or perhaps a string of moderate controversies to motivate them to implement a new system.