#Driven By Data

[pvtpunsart]

people who care need people who care

[senorboombastic]

Editor’s Picks: Top 50 songs of 2023 – Part Two

In classic fashion, my personal favourite record from 2023 came out a year ago. Eagle-eyed Instagram followers might’ve noticed too that when it came to the big Spotify Wrapped reveals, my number one song (and quite a few within the top five) were from an album that came out seven years ago! As our reviews man Ben Forrester likes to say though – don’t get it twisted! We bleed new music through…

[wistfulwatcher]

[asgardian--angels]

mage viktor discourse again on twitter and all i can say in my little corner over here once again is, I don't know why the entire fandom takes it as canon that mage Viktor failed to save every world he manipulated.

Canon does not provide evidence of this. This is fanon speculation. It's a fine headcanon to have, but everyone talks about it like it's canon when it isn't. Canon is ambiguous about the outcome of the timelines mage Viktor altered. The little nods we are given point, in my opinion, towards the opposite conclusion, that he successfully averted destruction.

I've written meta on this before but in summary:

1) 'In all timelines, in all possibilities' is worded precisely, it's not 'out of all timelines'; the implication is that every time, Jayce brings Viktor back from the brink, not just in our timeline. 'Only you' doesn't refer to our timeline's Jayce, it refers to all Jayces. Jayce always brings him home. If Viktor continuously put the fate of each timeline in Jayce's hands and Jayce failed over and over, I don't think he'd say those words. And the way he says them matters. His words are tinged with wonder, not sorrow. As if over and over again, he is shown that Jayce saves him, and it continues to amaze him. He doesn't sound defeated, like this is the next in a long line of Jayces he's sending off to die. The feeling is that Viktor's faith in Jayce has not been misplaced.

2) If mage Viktor doomed every timeline, there would be hundreds (or more) mage Viktors. All running around manipulating timelines. I highly doubt the writers wanted to get into that kind of sticky situation. The tragedy of mage Viktor is that he is singular. Alone. Burdened with the responsibility of the multiverse. The emotional gut punch of his fate is ruined if other timelines led to the same outcome, and from a practical standpoint, having multiple reality-bending omniscient mages would rip apart the fabric of the arcane.

There are other points, such as there being only one corrupted Mercury Hammer and our Jayce is the only one to receive it, and the fact that if mage Viktor is as omniscient as he is implied to be, he could easily step back into other timelines and correct course, because it's highly unlikely he could sit still and watch things go down in flames. But these things can be argued elsewhere.

While I love conversations about mage Viktor's motives and selfishness vs altruism, the writers & artbook have expressed that Jayce and Viktor care greatly about Runeterra and want to fix their mistakes to save it, and that their reconciliation is symbolic of Piltover and Zaun coming together as well. Yes, they make disastrous decisions towards each other, making choices for the other or without the other, which has negative consequences for their relationship and for Runeterra - but I think fandom pushes their selfishness even past what's canon sometimes, as if their entire goal hadn't always been to selflessly help the world around them. Their final reconciliation is about bridging the gap that grew between them - the pain and grief and secrets, betraying themselves and each other - to mutually choose each other openly and honestly. Part of the beauty of their story, as expressed by the creators, is that in their final moments, they chose each other and took responsibility for their actions by sacrificing themselves to end what they started, together - and that choosing each other saved the world. TPTB have stated this - that Jayce and Viktor are the glue holding civilization together, and when they come back to each other, they can restore balance. It's when they're apart, when they hurt each other and miscommunicate, when they abandon their commitment to each other and their dream, that the greater world suffers. Their strife is mirrored in the story-world at large.

Mage Viktor is framed as a solitary penitent figure, damned to an eternity of atoning for his mistakes. He paid the ultimate price and now is forced to live his personal nightmare of exactly what he was trying to avoid for himself with the glorious evolution. The narrative clues we're given point more in the direction that he saves timelines rather than dooms them. If Viktor's actions kept killing Jayce, the very boy he couldn't bear to not save each time, it would undermine these narrative choices. Yes, Viktor couldn't stand to live in a world where he never meets Jayce, so he ensures it keeps happening. But in that same breath, he couldn't bear to see a world where his actions continue to destroy Jayce and destroy Runeterra. His entire arc in s2 is born of his selfless desire to help humanity, help individual people. He would not lightly destroy entire worlds. That's his original grief multiplied a thousandfold, and narratively it would lessen the impact of the one, true loss he did suffer, his own Jayce. It wouldn't make sense for him to be alright with damning other timelines to suffer the same catastrophic tragedy that created him. I mean, maybe I'm delusional here, but is that not the entire point? Because that's what I took away when I watched the show.

As I said, I love discussions about mage Viktor, as there's a lot to play with. All I wish is that the fandom at large would not just assume or accept the Mage Viktor Dooms Every Timeline idea as canon, when there is nothing in the actual canon that confirms this. Maybe people need to just, go back and rewatch the actual episode, to recall how mage Viktor is presented to us, and what it's implied we're supposed to take away from his scenes, and separate that from the layers of headcanon the fandom has constructed.

[rosewind2007]

Murderbot and ART have a row and Murderbot storms off to its cabin aboard the Perihelion (yeah, I know) and slams the door

The a T-shirt falls out of the recycling machine:

that wasn’t very data-driven of you

[huginsmemory]

One of my favourite things about Ford is that he's like WAIT SAFETY about somethings when he disagrees (the Fiddleford becoming president thing, him being like it's too stressful for Fiddleford) BUT when it's something he's interested in he's like endangering my life is fine and normal (ie, him jumping into the abyss of the alien space ship with a magnetic gun; which is also a ship that has a security system).

The irony of it is amusing to me, but it's also I think it's a very good example that as much as Ford likes to say he's a Scientist™ and governed by Logic™... He's actually first and foremost driven by his emotions, and the logic is something that comes secondhand when he needs an explanation. Case in point with him drawing his relationship and contact with Bill in a way of him making new discoveries for mankind... When in TBOB it becomes very plainly obvious the main reason why he called on Bill was because he was desperately lonely (driven by emotion), less so about his scientific discovery (driven by logic). And I think there's a very human, relatable aspect to it because we all do this. That's why arguing with climate deniers and citing study after study about climate change, or even dealing with racist people and talking about equality and abstract morals doesn't work; there's an emotional aspect that drives people, always beyond our tower of cards of logic...

[t-hirstreview]

[githjanken]

i’m seeing a lot of fear today about Tumblr Shutting Down (Real) (Actually True) today and let peepaw seg tell you a story

i’ve been on this webbed site for fifteen years, believe it or not, since way back in the days of Tumblarity. now i was but a wee lad at the time, so i don’t remember the fine details, but rest assured, it doesn’t matter much for the story i’m about to tell you.

you see, i remember when tumblr was owned by tumblr. folk called its ceo (david karp) “daddy”, and were enthusiastic about his communications, even if on our own blogs, we��d bitch and moan about tumblr making changes to things we were used to. i remember the hubbub when tumblr removed tumblarity, and how this was surely going to be the end of tumblr.

all those fifteen (though it might be sixteen) years ago.

layouts changed, and we’d bitch and moan, and tumblr’d get sold, and we’d know for sure that This Was The End Of Tumblr, For Real This Time. this happened again and again and again, because this webbed site, you see, it makes no money, and companies, greedy things as they are, like money.

the porn ban, under the reign of YaHoo that was, was seen as another death knell. tumblr was going to die, for real, for sure, and i’m not proud to say that i was one of the ones who fell for it. peepaw seg needed to sow hir wild oats on other platforms.

now, i say this happened under yahoo, but it’s important to remember that this ban came in the wake of both the apple app store banning the tumblr app on account of real life csem being hosted on tumblr, and the new usamerican law SESTA-FOSTA being implemented, which made it so that companies such as tumblr would have to moderate the explicit content on them to make sure none of it breached sesta-fosta. tumblr, being a small fish in the grand scheme of thing, didn’t warrant that amount of financial effort on yahoo’s part, as the site was still not making any money, and it’s easier and cheaper to blanket ban than it is to moderate. all this to say, it’s important to vote, because if you don’t, your internet freedom will be curtailed.

and now we’re here, some sixteen years on, and i’ll say automattic has been not all good, but definitely not all bad for the site. they changed stuff we liked to our discontent (layouts), and added stuff we hated (live), but they also gave us stuff we like (polls) and an amount of open communication about tumblr’s inner workings not seen since the days of david “daddy” karp. and now they’re putting just a skeleton crew on the tumblr project.

and that’s going to be The End Of Tumblr For Sure For Real Actually This Time. Really. Promise. Abandon Ship.

and we come to the crux of this story.

which is that this has happened before, and it will happen again, because tumblr is surprisingly immune to making any money.

what we’re likely to see in the coming time is no new features (that’s reserved for projects that make money), and an increase in ads, until one day, and this might be in a few months, and maybe in a few years, there’ll be an announcement that tumblr’s been sold to one direction to a new company.

and we’ll start the whole rigmarole again. and this company might be good for tumblr’s userbase, or it might go against everything the tumblr community holds dear. no way of knowing which way it’ll go.

until one day, some parent company will have had enough, and will pull the plug.

but for now… well, i’m gonna sit here on my porch (blog), and we’ll see what happens. i'm not worried, tumblr’s survived worse things.

[mostlysignssomeportents]

The surprising truth about data-driven dictatorships

Here’s the “dictator’s dilemma”: they want to block their country’s frustrated elites from mobilizing against them, so they censor public communications; but they also want to know what their people truly believe, so they can head off simmering resentments before they boil over into regime-toppling revolutions.

These two strategies are in tension: the more you censor, the less you know about the true feelings of your citizens and the easier it will be to miss serious problems until they spill over into the streets (think: the fall of the Berlin Wall or Tunisia before the Arab Spring). Dictators try to square this circle with things like private opinion polling or petition systems, but these capture a small slice of the potentially destabiziling moods circulating in the body politic.

Enter AI: back in 2018, Yuval Harari proposed that AI would supercharge dictatorships by mining and summarizing the public mood — as captured on social media — allowing dictators to tack into serious discontent and diffuse it before it erupted into unequenchable wildfire:

https://www.theatlantic.com/magazine/archive/2018/10/yuval-noah-harari-technology-tyranny/568330/

Harari wrote that “the desire to concentrate all information and power in one place may become [dictators] decisive advantage in the 21st century.” But other political scientists sharply disagreed. Last year, Henry Farrell, Jeremy Wallace and Abraham Newman published a thoroughgoing rebuttal to Harari in Foreign Affairs:

https://www.foreignaffairs.com/world/spirals-delusion-artificial-intelligence-decision-making

They argued that — like everyone who gets excited about AI, only to have their hopes dashed — dictators seeking to use AI to understand the public mood would run into serious training data bias problems. After all, people living under dictatorships know that spouting off about their discontent and desire for change is a risky business, so they will self-censor on social media. That’s true even if a person isn’t afraid of retaliation: if you know that using certain words or phrases in a post will get it autoblocked by a censorbot, what’s the point of trying to use those words?

The phrase “Garbage In, Garbage Out” dates back to 1957. That’s how long we’ve known that a computer that operates on bad data will barf up bad conclusions. But this is a very inconvenient truth for AI weirdos: having given up on manually assembling training data based on careful human judgment with multiple review steps, the AI industry “pivoted” to mass ingestion of scraped data from the whole internet.

But adding more unreliable data to an unreliable dataset doesn’t improve its reliability. GIGO is the iron law of computing, and you can’t repeal it by shoveling more garbage into the top of the training funnel:

https://memex.craphound.com/2018/05/29/garbage-in-garbage-out-machine-learning-has-not-repealed-the-iron-law-of-computer-science/

When it comes to “AI” that’s used for decision support — that is, when an algorithm tells humans what to do and they do it — then you get something worse than Garbage In, Garbage Out — you get Garbage In, Garbage Out, Garbage Back In Again. That’s when the AI spits out something wrong, and then another AI sucks up that wrong conclusion and uses it to generate more conclusions.

To see this in action, consider the deeply flawed predictive policing systems that cities around the world rely on. These systems suck up crime data from the cops, then predict where crime is going to be, and send cops to those “hotspots” to do things like throw Black kids up against a wall and make them turn out their pockets, or pull over drivers and search their cars after pretending to have smelled cannabis.

The problem here is that “crime the police detected” isn’t the same as “crime.” You only find crime where you look for it. For example, there are far more incidents of domestic abuse reported in apartment buildings than in fully detached homes. That���s not because apartment dwellers are more likely to be wife-beaters: it’s because domestic abuse is most often reported by a neighbor who hears it through the walls.

So if your cops practice racially biased policing (I know, this is hard to imagine, but stay with me /s), then the crime they detect will already be a function of bias. If you only ever throw Black kids up against a wall and turn out their pockets, then every knife and dime-bag you find in someone’s pockets will come from some Black kid the cops decided to harass.

That’s life without AI. But now let’s throw in predictive policing: feed your “knives found in pockets” data to an algorithm and ask it to predict where there are more knives in pockets, and it will send you back to that Black neighborhood and tell you do throw even more Black kids up against a wall and search their pockets. The more you do this, the more knives you’ll find, and the more you’ll go back and do it again.

This is what Patrick Ball from the Human Rights Data Analysis Group calls “empiricism washing”: take a biased procedure and feed it to an algorithm, and then you get to go and do more biased procedures, and whenever anyone accuses you of bias, you can insist that you’re just following an empirical conclusion of a neutral algorithm, because “math can’t be racist.”

HRDAG has done excellent work on this, finding a natural experiment that makes the problem of GIGOGBI crystal clear. The National Survey On Drug Use and Health produces the gold standard snapshot of drug use in America. Kristian Lum and William Isaac took Oakland’s drug arrest data from 2010 and asked Predpol, a leading predictive policing product, to predict where Oakland’s 2011 drug use would take place.

[Image ID: (a) Number of drug arrests made by Oakland police department, 2010. (1) West Oakland, (2) International Boulevard. (b) Estimated number of drug users, based on 2011 National Survey on Drug Use and Health]

Then, they compared those predictions to the outcomes of the 2011 survey, which shows where actual drug use took place. The two maps couldn’t be more different:

https://rss.onlinelibrary.wiley.com/doi/full/10.1111/j.1740-9713.2016.00960.x

Predpol told cops to go and look for drug use in a predominantly Black, working class neighborhood. Meanwhile the NSDUH survey showed the actual drug use took place all over Oakland, with a higher concentration in the Berkeley-neighboring student neighborhood.

What’s even more vivid is what happens when you simulate running Predpol on the new arrest data that would be generated by cops following its recommendations. If the cops went to that Black neighborhood and found more drugs there and told Predpol about it, the recommendation gets stronger and more confident.

In other words, GIGOGBI is a system for concentrating bias. Even trace amounts of bias in the original training data get refined and magnified when they are output though a decision support system that directs humans to go an act on that output. Algorithms are to bias what centrifuges are to radioactive ore: a way to turn minute amounts of bias into pluripotent, indestructible toxic waste.

There’s a great name for an AI that’s trained on an AI’s output, courtesy of Jathan Sadowski: “Habsburg AI.”

And that brings me back to the Dictator’s Dilemma. If your citizens are self-censoring in order to avoid retaliation or algorithmic shadowbanning, then the AI you train on their posts in order to find out what they’re really thinking will steer you in the opposite direction, so you make bad policies that make people angrier and destabilize things more.

Or at least, that was Farrell(et al)’s theory. And for many years, that’s where the debate over AI and dictatorship has stalled: theory vs theory. But now, there’s some empirical data on this, thanks to the “The Digital Dictator’s Dilemma,” a new paper from UCSD PhD candidate Eddie Yang:

https://www.eddieyang.net/research/DDD.pdf

Yang figured out a way to test these dueling hypotheses. He got 10 million Chinese social media posts from the start of the pandemic, before companies like Weibo were required to censor certain pandemic-related posts as politically sensitive. Yang treats these posts as a robust snapshot of public opinion: because there was no censorship of pandemic-related chatter, Chinese users were free to post anything they wanted without having to self-censor for fear of retaliation or deletion.

Next, Yang acquired the censorship model used by a real Chinese social media company to decide which posts should be blocked. Using this, he was able to determine which of the posts in the original set would be censored today in China.

That means that Yang knows that the “real” sentiment in the Chinese social media snapshot is, and what Chinese authorities would believe it to be if Chinese users were self-censoring all the posts that would be flagged by censorware today.

From here, Yang was able to play with the knobs, and determine how “preference-falsification” (when users lie about their feelings) and self-censorship would give a dictatorship a misleading view of public sentiment. What he finds is that the more repressive a regime is — the more people are incentivized to falsify or censor their views — the worse the system gets at uncovering the true public mood.

What’s more, adding additional (bad) data to the system doesn’t fix this “missing data” problem. GIGO remains an iron law of computing in this context, too.

But it gets better (or worse, I guess): Yang models a “crisis” scenario in which users stop self-censoring and start articulating their true views (because they’ve run out of fucks to give). This is the most dangerous moment for a dictator, and depending on the dictatorship handles it, they either get another decade or rule, or they wake up with guillotines on their lawns.

But “crisis” is where AI performs the worst. Trained on the “status quo” data where users are continuously self-censoring and preference-falsifying, AI has no clue how to handle the unvarnished truth. Both its recommendations about what to censor and its summaries of public sentiment are the least accurate when crisis erupts.

But here’s an interesting wrinkle: Yang scraped a bunch of Chinese users’ posts from Twitter — which the Chinese government doesn’t get to censor (yet) or spy on (yet) — and fed them to the model. He hypothesized that when Chinese users post to American social media, they don’t self-censor or preference-falsify, so this data should help the model improve its accuracy.

He was right — the model got significantly better once it ingested data from Twitter than when it was working solely from Weibo posts. And Yang notes that dictatorships all over the world are widely understood to be scraping western/northern social media.

But even though Twitter data improved the model’s accuracy, it was still wildly inaccurate, compared to the same model trained on a full set of un-self-censored, un-falsified data. GIGO is not an option, it’s the law (of computing).

Writing about the study on Crooked Timber, Farrell notes that as the world fills up with “garbage and noise” (he invokes Philip K Dick’s delighted coinage “gubbish”), “approximately correct knowledge becomes the scarce and valuable resource.”

https://crookedtimber.org/2023/07/25/51610/

This “probably approximately correct knowledge” comes from humans, not LLMs or AI, and so “the social applications of machine learning in non-authoritarian societies are just as parasitic on these forms of human knowledge production as authoritarian governments.”

The Clarion Science Fiction and Fantasy Writers’ Workshop summer fundraiser is almost over! I am an alum, instructor and volunteer board member for this nonprofit workshop whose alums include Octavia Butler, Kim Stanley Robinson, Bruce Sterling, Nalo Hopkinson, Kameron Hurley, Nnedi Okorafor, Lucius Shepard, and Ted Chiang! Your donations will help us subsidize tuition for students, making Clarion — and sf/f — more accessible for all kinds of writers.

Libro.fm is the indie-bookstore-friendly, DRM-free audiobook alternative to Audible, the Amazon-owned monopolist that locks every book you buy to Amazon forever. When you buy a book on Libro, they share some of the purchase price with a local indie bookstore of your choosing (Libro is the best partner I have in selling my own DRM-free audiobooks!). As of today, Libro is even better, because it’s available in five new territories and currencies: Canada, the UK, the EU, Australia and New Zealand!

[Image ID: An altered image of the Nuremberg rally, with ranked lines of soldiers facing a towering figure in a many-ribboned soldier's coat. He wears a high-peaked cap with a microchip in place of insignia. His head has been replaced with the menacing red eye of HAL9000 from Stanley Kubrick's '2001: A Space Odyssey.' The sky behind him is filled with a 'code waterfall' from 'The Matrix.']

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

 — 

Raimond Spekking (modified) https://commons.wikimedia.org/wiki/File:Acer_Extensa_5220_-_Columbia_MB_06236-1N_-_Intel_Celeron_M_530_-_SLA2G_-_in_Socket_479-5029.jpg

CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0/deed.en

 — 

Russian Airborne Troops (modified) https://commons.wikimedia.org/wiki/File:Vladislav_Achalov_at_the_Airborne_Troops_Day_in_Moscow_%E2%80%93_August_2,_2008.jpg

“Soldiers of Russia” Cultural Center (modified) https://commons.wikimedia.org/wiki/File:Col._Leonid_Khabarov_in_an_everyday_service_uniform.JPG

CC BY-SA 3.0 https://creativecommons.org/licenses/by-sa/3.0/deed.en

[luxe-pauvre]

The study found that the most successful headlines don't convey facts, they promise you an emotional experience. The most common phrase among successful Facebook headlines, by nearly twofold, is "will make you,” as in "will break your heart,"«”will make you fall in love," "will make you look twice," or "will make you gasp in surprise" as above. This phrase is also highly successful on Twitter. Other top phrases include "make you cry," "give you goosebumps," and "melt your heart." Intellectual experiences cannot compete. Pause for a moment and think about what a huge shift this represents. Can you imagine The New York Times or your local newspaper with headlines that told you how you'd feel about each story, but not what the story actually entailed? […] What we are saying becomes more interesting than what is happening. All of this fluff and glitter does more than just dumb down the national conversation: It opens the door for bullshit. The unvarnished truth is no longer good enough. Straight-up information cannot compete in this new marketplace.

Carl T. Bergstrom & Jevin D. West, Calling Bullshit: The Art of Scepticism in a Data-Driven World

[candidateofloyalty]

I don't think he's happy.

[farmerstrend]

What Makes a Great Agronomist? Unpacking the Traits of Agricultural Excellence

Agronomists are the unsung heroes shaping the future of farming. They’re the bridge between science and soil, the architects of abundance in a world hungry for both food and sustainability. Over the years, after sifting through hundreds of agronomist resumes and meeting countless professionals in this field, I’ve come to realize that greatness in agronomy isn’t just about a degree or a title.…

[houseofdissension]

⸻  𐄁  𝐕𝐎𝐋𝐍𝐄𝐑-𝐃𝐎𝐖𝐍𝐄  𝐈𝐍𝐂.  //  𝐅𝐎𝐑𝐌  𝟎𝟗𝟗.𝐀

SUBJECT  INTAKE  FOR  DUAL-IDENTITY  REGISTRY FLOOR  OF  DISSENT  —  DISSENSION  INITIATIVE,  FLOOR  40  –  RESTRICTED All  data  collected  is  strictly  classified.  Retrieval  of  memory  post-submission  is  forbidden.

[  𝗩𝗢𝗟𝗡𝗘𝗥-𝗗𝗢𝗪𝗡𝗘  𝗜𝗡𝗖.  //  𝗗𝗜𝗦𝗦𝗘𝗡𝗦𝗜𝗢𝗡 𝗣𝗥𝗢𝗖𝗘𝗗𝗨𝗥𝗘 𝗙𝗢𝗥𝗠  ]

╰──  olivia cooke,  34,  cis-female,  she & her  ]   ＞  𝙾𝙱𝚂𝙴𝚁𝚅𝙴𝙳   𝙰𝚂𝚂𝙴𝚃   𝙻𝙾𝙶:  The  individual  known  informally  as  [  SCARLETT VALENTINE  ]  has  been  noted  for  presence  within  the  Downe’s  Hollow  parameters.  According  to  behavioral  estimates,  they  present  at  approximately  [  THIRTY-FOUR  ],  and  have  been  under  evaluation  for  [  SEVEN MONTHS  ].  During  scheduled  daylight  hours,  they  are  recorded  operating  in  the  role  of  [  DISSENSION EMPLOYEE  /  CODE HARMONIZATION OPERATOR  ].  Community  observation  reports  suggest  notable  behavioral  markers:  prone  to  [  MACABRE  ]  under  stress,  yet  reportedly  [  PRODIGIOUS  ]  in  collective  settings.  Volner-issued  residency  placement:  [  CORNELIUS CIRCLE / GUINEVERE LANES  ].  Echo  archetypes  detected  in  personality  patterns  include:  [  a blistered tongue, seared and branded by transgression and abuse and guilt; the mortar holding together a stalwart dam; echoes of the past, cloaked in spectral veils, transmuted into whispered horrors — a delicate alchemy of pain and poetry  ].  𝚂𝚃𝙰𝚃𝚄𝚂:  under  continued  observation..  Decompression  tolerance  uncertain.  Reintegration  probability:  INCOMPLETE. Continue on to Dissension Form below:

╰──  𝗗𝗜𝗦𝗦𝗘𝗡𝗦𝗜𝗢𝗡  𝗜𝗗𝗘𝗡𝗧𝗜𝗧𝗬  𝗦𝗨𝗣𝗣𝗟𝗘𝗠𝗘𝗡𝗧𝗔𝗟  𝗣𝗥𝗢𝗙𝗜𝗟𝗘  —  𝗙𝗟𝗢𝗢𝗥  𝟰𝟬  𝗥𝗘𝗖𝗢𝗥𝗗𝗦. 

＞  INTERNAL  IDENTIFIER:   SCAR V   ＞  DEPARTMENT  ASSIGNMENT:   DATA RECONCILIATION   ＞  TASK  UNDERSTANDING:    “I make nonsense make sense, then feed it to a machine that doesn’t care.”  ＞  LAST  PERFORMANCE  NOTE:   “Scar V has demonstrated consistent noncompliance within the Innie environment, frequently exhibiting defiant behavior and engaging in multiple attempts to breach containment protocol in an attempt to leave. Instances include the physical disruption of workflow and the aggressive misuse of office equipment toward colleagues. Notably, subject has already undergone the Remorse Index Recitation three times within the first seven months of assignment, an intervention typically reserved for higher-tier infractions. On the upside, she exhibits excellent emotional containment, especially when witnessing distress in others. Highly efficient under duress. Unclear if empathy is genuine or rehearsed.”  ＞  CROSS-MEMORY  TRACE  DETECTED?:   NO   ＞  DREAM  REPORT  (  IF  ANY  ):   A young, terrified voice saying she can’t quite recognize saying, “Don’t look at me like that,” though no one is in the room.  ＞  MOTIVATIONAL  SCORE:   ERRATIC 

𐄁  𝗩𝗢𝗟𝗡𝗘𝗥-𝗗𝗢𝗪𝗡𝗘  𝗜𝗡𝗖.  //  𝗣𝗢𝗦𝗧-𝗦𝗘𝗧𝗧𝗟𝗘𝗠𝗘𝗡𝗧  𝗢𝗡𝗕𝗢𝗔𝗥𝗗𝗜𝗡𝗚  𝗘𝗩𝗔𝗟𝗨𝗔𝗧𝗜𝗢𝗡

FORM  82-D  |  RESIDENCY  JUSTIFICATION  INTAKE: Your  responses  are  recorded  under  Civic  Harmony  Protocol  6.1.  Please  answer  with  full  clarity  and  personal  accountability.  Ambiguity  may  result  in  further  observation.

1. At  the  time  of  your  Procedure,  you  were  given  the  opportunity  to  decline.  And  yet,  you  proceeded.  Why  did  you  choose  Dissension?

Scarlett  leans  back  in  the  too-small  chair,  arms  folded  like  a  closing  statement.  One  brow  arches,  slow  and  surgical. ❝ Because  hell  with  fluorescent  lighting  that I wouldn't remember sounded  better  than  the  one  I  was  already  in.  ❞  Her  silence  lingers  just  long  enough  for  her  to  speak  without  words  —  the  way  her  leather  jacket  frames  her  shoulders  like  quiet  defiance,  &  how  her  jeans,  worn  soft  at  the  knees,  settle  into  their  own  steady  truth.   ❝ You  people  were  offering  a  clean  slate.  No  memories,  no  guilt, no  name  for  half  a  day. Just  buttons  to  press  and  rules  to  follow or whatever.  Sounded  like  a  spa  day  for  the  soul. ❞ The  whiskey  from  the  night  before  still  coats  to  the  back  of  her  throat  —  a  warm,  bitter-sweet  lacquer  that  strikes  like  a  slow-burning  ember,  equal  parts  comfort  &  corrosion.  ❝ Guess  I  should’ve  asked  about  the  fine  print.  Like  the  part  where  your  clean  slate  might  still  bleed  through.  ❞ Insert  hard,  razor-edged  look:  ❝ But  hey  —  what’s  a  little  corporate  haunting  between  strangers,  right? Gotta make a goddamn living somehow. ❞

2.  At  the  time  of  your  arrival,  what  were  you  running  from,  or  toward?

Her  fingers  drum  once,  twice,  against  the  cold  metal  of  the  table  before  curling  into  a  loose  fist.  Her  doe  eyes,  flat  and  unreadable,  flick  upward  like  a  flicked  switchblade.  She’s  never  been  one  to  temper  her  reactions  (  not  like  her  sister  )  —  discipline  wasn’t  part  of  the  armor  she  laced  on  each  morning,  right  alongside  those  worn,  unwashed  jeans  &  that  five-letter  snarl  of  a  personality:  bite  first,  never  bother  with  the  after.  Flattery  slides  off  her  like  rain  on  iron  —  useless,  dull.  So  when  she  answers  with  that  signature,  tight-jawed  grit,  it’s  easy  to  miss  the  flicker  —barely  there  —  of  something  sharper  than  disinterest,  a  faint  spark  catching  at  the  corner  of  her  hawkish  eyes.  A  glint,  brief  as  breath,  betraying  that  maybe  —  just  maybe  —  she’s  listening. ❝ Running? ❞  Scarlett  echoes,  like  the  word  tastes  foreign.  ❝ No,  see  —  running  implies  there  was  a  plan.  A  direction.  Something  stupidly  poetic. ❞  She  leans  back  slightly,  head  tilting.   ❝ I  walked.  Tripped,  maybe.  Fell  into  this  shit  town,  it  seems. ❞  Her  voice  drops,  low  and  dry.   ❝ But  for  the  sake  of  'playing  along'  let’s  just  say...  I  wasn’t  chasing  anything.  Just  hoping  the  next  place  wasn’t  worse  than  the  last. ❞  Her  throat  undulates  with  a  hard  swallow,  &  then,  with  a  grin  that  doesn’t  reach  her  eyes:  ❝ But  you  already  knew  that,  didn’t  you? ❞

3.  Do  you  believe  you  chose  this  life,  or  were  chosen  for  it?

Scarlett  scoffs  —  quiet,  dry  —  like  the  question  itself  left  a  bad  taste  in  her  mouth.  She  shifts  in  her  seat,  one  boot  tapping  a  lazy  rhythm  against  the  floor,  arms  crossed  like  armor  stitched  from  disdain.  ❝  Is  that  your  way  of  asking  if  I  believe  in  fate?   ❞ she  mutters,  voice  flat  but  laced  with  that  low,  razored  edge. ❝  'Cause  if  so,  the  answer’s a big ole' fuck  no.  I  believe  in  gravity  and  poor  decisions.   ❞ Her  fingers  ghost  along  the  table’s  edge,  pausing  for  a  beat,  like  she  might  say  more — like  something  almost  slips. It's  common  knowledge  that  she  speaks  in  sharpened  challenges,  each  one  flung  with  the  ease  of  someone  who’s  had  too  much  practice  and  not  nearly  enough  restraint.  By  now,  they  roll  off  the  fork  of  her  tongue  like  second  nature  —  acid-laced,  intentional,  impossible  to  misread.  She’s  mastered  the  art  of  wielding  judgment  like  a  weapon  while  hoisting  a  silent,  fluorescent  'KEEP  OUT'  sign  in  the  same  breath  —  an  elegance  of  deflection  honed  not  by  chance,  but  by  choice.  The  only  honest  thing  about  her right now  is  that  she  walked  straight  into  this  interrogation,  knowing  full  well  the  knives  it  would  throw.  And  still,  her  face  remains  carved  from  something  tougher  than  resolve  —  cheek  tight,  jaw  like  chewed  concrete,  each  brittle  muscle  grinding  down  on  the  weight  of  unsaid  things.  With  a  crooked  half-smile,  sharp  as  glass: ❝  Doesn’t  really  matter  if  I  chose  it  or  not,  does  it?  I'm  in  it.  That’s  the  punchline.  ❞

4.  When  you  envision  the  person  you  used  to  be,  what  part  of  them  still  lingers  in  the  current  design?

Exhaling  through  her  nose  —  sharp,  almost  amused  —  as  if  the  question  is  a  joke  told  poorly  at  the  wrong  end  of  the  world,  she  tilts  her  head  in  thought.  She  leans  forward  just  enough  to  let  the  light  catch  the  hollow  under  her  cheekbone,  hazel  eyes  flicking  up  with  that  signature  brand  of  mean-sweet  indifference.  ❝  Depends  on  who  you  ask,  ❞ she  mutters,  thumb  tracing  the  edge  of  the  table  like  she’s  thinking  about  gouging  it.  ❝  Some  might  say  the  attitude.  Others—  ❞  she  clicks  her  tongue,  considering,   ❝  —the  unfortunate  habit  of  surviving  things  I  probably  shouldn’t.  ❞  Setting  her  chin  on  her  knuckles,  Scarlett  lifts  her  gaze  again,  still  and  dry  and  razor-flat.   ❝ I  wouldn’t  know.  I  stopped  looking  at  her  a  long  time  ago.  ❞

𝐖𝐞𝐥𝐜𝐨𝐦𝐞  𝐭𝐨  𝐕𝐨𝐥𝐧𝐞𝐫-𝐃𝐨𝐰𝐧𝐞  𝐈𝐧𝐜.,  𝘸𝘩𝘦𝘳𝘦  𝘢𝘭𝘪𝘨𝘯𝘮𝘦𝘯𝘵  𝘪𝘴  𝘰𝘱𝘱𝘰𝘳𝘵𝘶𝘯𝘪𝘵𝘺  𝘢𝘯𝘥  𝘴𝘦𝘳𝘷𝘪𝘤𝘦  𝘳𝘦𝘧𝘪𝘯𝘦𝘴  𝘵𝘩𝘦  𝘴𝘦𝘭𝘧.  𝘠𝘰𝘶𝘳  𝘱𝘳𝘦𝘴𝘦𝘯𝘤𝘦  𝘩𝘢𝘴  𝘣𝘦𝘦𝘯  𝘯𝘰𝘵𝘦𝘥,  𝘺𝘰𝘶𝘳  𝘱𝘰𝘵𝘦𝘯𝘵𝘪𝘢𝘭  𝘳𝘦𝘤𝘰𝘨𝘯𝘪𝘻𝘦𝘥.  𝘞𝘦  𝘢𝘳𝘦  𝘱𝘭𝘦𝘢𝘴𝘦𝘥  𝘵𝘰  𝘣𝘦𝘨𝘪𝘯  𝘵𝘩𝘪𝘴  𝘫𝘰𝘶𝘳𝘯𝘦𝘺  𝘵𝘰𝘨𝘦𝘵𝘩𝘦𝘳.

𝗪𝗲’𝗿𝗲  𝗵𝗼𝗻𝗼𝗿𝗲𝗱  𝘁𝗼  𝗵𝗮𝘃𝗲  𝘆𝗼𝘂  𝘂𝗻𝗱𝗲𝗿  𝗼𝘂𝗿  𝗰𝗮𝗿𝗲. –  Compliance.  Continuity.  Purpose.

[hyper-lynx]

Oh God I'm thinking about rewriting my whole mod to be all data driven......... I already added KubeJS support I really don't have to do this, the people can already make reactions in modpacks !!

(But it'd be cool)

It would but, but...

[seonghwacore]

be real honest. which member of your favorite group whose personality is actually similar to you? are they your bias or not?