THE DEAD SEA SCROLLS – MUSEUM OF THE BIBLE CHIEF CURATOR DR. ROBERT DUKE GIVES “FOX NEWS SUNDAY” A SPECIAL GLIMPSE AT THE DEAD SEA SCROLLS EXHIBIT AT THE MUSEUM OF THE BIBLE IN WASHINGTON, D.C.
THE DEAD SEA SCROLLS are a collection of ancient manuscripts discovered in the QUMRAN CAVES near THE DEAD SEA in the late 1940s.
They date from the 3rd century BC to the 1st century AD and include texts in HEBREW, ARAMAIC, and GREEK.
These SCROLLS contain some of the oldest known copies of BIBLICAL TEXTS and other RELIGIOUS WRITINGS, significantly impacting our understanding of early JUDAISM and CHRISTIANITY.
THE DEAD SEA SCROLLS & ENOCH (AI)
ROLE OF ARTIFICIAL INTELLIGENCE (AI)
HANDWRITING ANALYSIS
ARTIFICIAL INTELLIGENCE (AI) has been employed to analyze the HANDWRITING of THE DEAD SEA SCROLLS.
Researchers have developed a machine-learning model named ENOCH that examines the shapes of letters and compares them to known DATED SCROLLS.
This method allows for a more precise dating of THE MANUSCRIPTS than traditional paleographic analysis.
DATING METHODOLOGY
The AI model combines RADIOCARBON DATING with HANDWRITING ANALYSIS.
By training on RADIOCARBON-DATED SCROLL FRAGMENTS, ENOCH can predict the dates of other SCROLLS with an uncertainty of about 30 years.
This approach has revealed that many SCROLLS are older than previously believed, with some dating back to the 4th century BCE.
SIGNIFICANCE OF FINDINGS
The use of AI in studying THE DEAD SEA SCROLLS has led to new insights into the evolution of ancient JEWISH SCRIPT styles and the historical context of these texts.
The findings suggest that certain BIBLICAL SCROLLS may have originated earlier than their associated communities, prompting a reevaluation of their historical significance.
This innovative approach opens new avenues for research on ANCIENT MANUSCRIPTS worldwide.
If you don't mind me asking, are there other types of AI you find okay? Or do you find all AI bad?
i don't find all AI bad, my capstone project was a neural network project. (it was for a bank robbery threat assessment)
genAI steals and regurgitates (basically bastardises) what it has been fed, that's why it's bad (+energy costs)
other AI—ones that are fed and trained on material for pattern recognition/tasks are fine and sometimes necessary.
there's various ways to categorize ai: capability (narrow, general, superintelligent), models (reactive, limited memory, theory of mind, self aware), types (machine learning, deep learning, neural networks)
a good example would be akinator. it's an AI, it has been trained on characters and it recognizes the character based on description. It doesn't create a new character by stealing other people's works.
another example would be biometric face scanners: they would convert the facial features into a digital maps and compare them to the ones in a database. they don't create anything new.
both these cases use machine learning algorithms to get the job done, in various degrees of complexity.
then we have neural networks, which id a system that's inspired by the human brain and is for complex/prediction tasks.
an example would be natural language processing- which is mostly used for translators
and then there's deep learning, which is also a type of machine learning and is the basis for generative ai. but deep learning doesn't equal to genAI. deep learning is also used for purposes like medical image analysis.
and when you take energy costs to compare— traditional neural networks for example—are generally smaller, task-specific, and require fewer parameters, reducing computational operations. genAI requires immense power to calculate, predict, and generate new content across vast, dense models, often consuming up to 100 times more energy per query.
Source: peer reviewed journal article
so not all ai is bad, i'd be a shit computer engineer if i said that. but you've got to learn what you're up against.
i'm just gonna call it that we need to practice mindful tech usage and security and i don't mean screentime tracking apps and vpns or whatever i mean starting from early childhood and going into adult wellbeing culture to encourage tactile hobbies and long-form work and the understanding of online devices as commodifying the user with spyware
i'm talking throwback word processors with the same ergonomics as regular smart devices for general educational work and dedicated subjects for working with digital technologies so you have theory in practice and then applying that theory in a contemporary work context. that's where you learn applications, digital safety, and how to implement the generative tools. separately. once you've already developed the critical analysis and expressive skills first.
i have been basically addicted to the internet since i was 13, i've had ups and downs with it, but i've always had a little bit of over caution when it comes to information and identity online. i overshare what i chose to but i think the break down of privacy as a norm when it comes to personal data tracking is genuinely awful.
i like algorithms in some places but i do not think this super-customisation is worth this panopticon of tech.
have you heard about how phone locations can still be triangulated when the phone is off? this is incidentally why if you are gong to protests and you think you are in danger it might be best to leave it at home. but generally if you want to avoid audio and video being used to build a marketing profile you can just switch it off and pop it in a bag or the next room. but with fb trying to make voice command smart glasses a thing (after snapchat and google both failed to sustain the same product) it bears caution that so called wearable tech such as glasses, pendants, watches, earbuds, ect.... even outside of smart cars there's the risk of passive listening for user marketing profiles. we already have location based advertising, ads that track your useage to predict your menstrual cycle or life events, public ads that react to nearby phones
i am going off on this tangent to say that i am not naïve to the fact that we already have to constantly dig into 'dark patterns' of settings to opt out of surveillance and commodification. i'm aware that the easiest path is to do nothing and use the shortcut machines even when they don't actually help or save much time or effort beyond selling you tools that already exist with a new price tag. i'm aware that the plagiarism software with no idea what it's talking about and runs on resource wasting pollution and underpaid remote human labour that also gets slapped in every function role despite basically being fancy autofil and pixel pulp not only has all of those issues but the lay person is either unaware or does not care and companies only care that it is a new way to pretend they're innovating. i know all this just like i know that mass automation is just exploitation unless it is balanced with social structures for all that mean emancipation from the need for labour.
but while i think all tech can be used for good, facilitating human connection across physical distance, carefully trained data analysis on a rapid large scale, removing the tedium of technical drudgery where needed, just providing light entertainment. but we have gotta be better about legislating, moderating, and use culture.
use culture goes hand in hand with convenience. it's why vinyl records are still trendy, not only are they good at what they do, but there is enough cool factor that the inconvenience becomes a feature. CDs are also convenient still! but CDs do not have the cool factor so they get wiped out by the convenience of streaming. playlists in streaming have a cool factor that radio does not despite radio still being convenient. and remember no matter how much streaming claims you can pay to opt out of ads that's usually something that you get payment tiered out of eventually so the convenience facilitated by accessibility is debatable the longer time passes.
looping back to my original point, if we can encourage an understanding of digital privacy as something you shouldn't be complacent about, that you shouldn't have to pay for tools to get out of the spotlight, that it is immensely embarrassing to be too into exploitation by tech companies and make that the problem of everyone around you. user control should be synonymous with convenience. customisability/personalisation through individual control rather than passive scraping. you can still commodify decorative tech.
we gotta make slop and babying algorithm brained tech usage cringe. people don't care to hear that it's immoral so just make them feel uncool at this point. because it is embarrassing that you have the universe of resources at your fingertips and you're too scared to do anything with it other than beg it to put words in your mouth. who cares if you're chronically online or too busy irl to learn a new skill. you are like a little bird pecking at it's own reflection, that's sad. try saying something mediocre and honest. we gotta stop tap dancing into technofeudalism just because we're too complacent to actually talk to each-other.
The Ad Astra Institute for Science Fiction & the Speculative Imagination's AI Policy
Full text under the cut, below, but let's start with the positive conclusion from a brilliant new "Let's talk about AI art" comic-essay by The Oatmeal:
SF is the literature of change, and part of what's changing in our world the most is what corporations tout as "artificial intelligence." However, AI today is not what SF has long speculated about, and it's not the magic pill so many promote as the path toward creative success. Anyone looking to become skilled in the art and craft of speculative fiction needs to stay away from generative AI (genAI).
We at Ad Astra do, and we expect attendees in (and teachers of) our courses and workshops to avoid it, too.
You might be thinking, "Isn't the Ad Astra Institute all about speculative fiction? What’s more SFnal than AI?"
Yeah, well... let's take a closer look.
Our full AI policy boils down to "No GenAI slop, no plagiarism-machine botshit, here's why," and lives on our website here. Copied below the cut:
What is AI?
First of all, most of what the media discusses as "AI" and what businesses push using that name is far from it. The "positronic brain" of R Daneel Olivaw (of Asimov's series of robot stories and novels) bestows this "humaniform" robot with human-like intelligence and a capability to think, reason, imagine, and do everything else humans do - only better. He's ruled by Asimov's "Laws of Robotics," which also gives these fictional robots ethics exceeding that of many humans. HAL 9000 (of 2001: A Space Odyssey) also possesses greater-than-human intelligence and the ability to think and possibly even feel, but it was programmed without ethical rules so much as mission-related ones (you'll have to watch if you don't know 'em; no spoilers). Neuromancer, Wintermute, and other artificial intelligences and digitized human minds in Gibson's touchstone novel Neuromancer are also superintelligent, thinking machines. The movie AI: Artificial Intelligence delves into the potential emotional nature of AI. Iain M Banks' "Minds" from his Culture novels possess vast intellectual and other power.
Especially in recent years, SF offers many, many interesting and moving examples of machines that can think, create, feel, and do all the other things humans can. But they do not exist in our world. (At least, not yet.)
Non-generative AI - often referred to as "machine learning" or "neural networks" - today is technology that enables computer systems to simulate or mimic human learning, comprehension, problem solving, decision making, and autonomy in order to perform tasks too complex, fast-paced, or dangerous for humans. How NASA defines AI, per the National Defense Authorization Act of 2019:
An artificial system that performs tasks under varying and unpredictable circumstances without significant human oversight, or that can "learn" from experience and improve performance when exposed to data sets.
An artificial system developed in computer software, physical hardware, or other context that solves tasks requiring human-like perception, processing, planning, learning, communication, or physical action.
An artificial system designed to [appear to] "think" or act like a human, including cognitive architectures and neural networks.
A set of techniques, including machine learning, designed to approximate a cognitive task.
An artificial system designed to act rationally, including an intelligent software agent or embodied robot that achieves goals using perception, planning, reasoning, learning, communicating, decision-making, and acting.
Note that none of this involves creative, artistic, or otherwise imaginative or innovative cognition - or thinking at all. True(-ish) but "weak" AI systems today include weather-analysis algorithms that pore over vast amounts of data to identify patterns that help humans predict upcoming weather patterns, military drones that evade defenses and attack enemies without human intervention by using geographical maps and images of threats and targets with real-time data processing and analysis without relying on remote processing ("edge AI"), self-driving cars, pharmaceutical algorithms that process likely biological interactions with various compounds, medical systems that process patient symptoms and compare them against vast databases of known pathologies, and much more. These are all various forms of machine learning, neural networks, and so on - (misleadingly) classified in computer science as "artificial intelligence" - and are far closer to the SFnal concept of Strong AI than the "generative AI" (genAI) dominating today's corporate landscape.
Strong AI, Artificial General Ingelligence (AGI), or Artificial Superintelligence (ASI) are something like simulated human minds. The "general intelligence" part of the term refers to the human mind's ability to independently adapt and change based on our environment and input, so we can solve math problems as readily as create unique art. While weak AI relies on humans to define its learning algorithms and provide relevant training data, AGI would not require human assistance after its growth phase. In theory, AGI could develop human-like thought capacity or even consciousness rather than just simulating it (as with today's weak-AI chatbots and LLMs). And ASI is just what it sounds like - AGI whose abilities far surpass those of the human mind. This sort of AI stuff has long lived in the realm of spec-fic, and we're not there... yet.
Though many believe it is coming, and could emerge as soon as the 2040s. For more, see Vernor Vinge's seminal essay on the topic, "What is the Singularity?"
GenAI algorithms can't even do math well - the most basic of all machine operations. "Look what you did - you took a perfectly good computer and made it worse!"
However, genAI in today's world does nothing more than spit out statistically likely and expected output to the input it is given. That's why when someone asks ChatGPT, "Is 'Handyman' a palindrome?" it's likely to respond, "No, it’s not" - but if you follow up with, "Are you sure? I think it is," it's likely to respond, "Actually it is a palindrome! Handyman is spelled the same backward as it is forward." This is because its prime directive is to sound as if it's providing a correct answer. Despite having access to a database of basically all information that humankind possesses, ChatGPT and other LLMs or genAI models don't actually understand what a palindrome is. They understand nothing, in the human sense of those terms.
The only thing these algorithms do is determine the next most-likely word to follow a word it just used and then barf it into the series of words it offers. That's how they produce "stories" and other text. Visual genAI does something similar, but using existing imagery to whip up a composite of imagery cues that seem (to its database) like the kinds of thing a human is requesting in their prompt.
GenAI as it exists today is really just a marketing tool for businesses who want to eliminate human labor and increase profits, and for profiteers to attract the vast capital available from investors seeking quick and large returns on investment.
LLMs, genAI, chatbots, and similar plagiarism machines are not artificial intelligence by any real definition of the term; rather, they're just lazily (or trickily) called "AI" because that's a field of computer programming. Corporations likely glommed onto the term because of the popularity of robots in SF, which the public thinks of as cool, exciting, super-intelligent - or at least super-capable. This, despite these kinds of algorithms being simply unable to produce anything of value, because they do not understand, know, or create anything.
(For more on this, check out "Difference Between Machine Learning and Artificial Intelligence," by Anusha Sharma.)
How AI Killed NaNoWriMo
(Opposing plagiarism machines isn't ableist)
In fall of 2024, the amateur writing-support organization NaNoWriMo destroyed its long-running program by coming out with the policy screenshotted in part here:
Not only did they actively condone the use of genAI by their participants, they went so far as to frame criticism of AI as classist and ableist. This was a dangerous silencing tactic that distracted from the real problems of writers using genAI (and prompted us to launch Ad Astra's Writing Solidarity Month, now an ongoing set of activities offered through our Discord channel).
For the “anyone can write” organization that offered support and encouragement to both beginners and experienced writers in producing something that gives them the joy of creation in a community setting, this was a strange stance. What’s the point of using genAI to barf out word-salad stolen from people who actually took the time to consider their words in particular combinations? If you’re not actually writing something yourself, what’s the point of participating in the “doesn’t matter if you’re just doing this for your own pleasure or as practice to get better” exercise?
Saying, “We support using LLMs to do this thing that’s supposed to help writers and would-be writers, and if you don’t think it’s okay you’re ableist” is an even weirder and, frankly, unsettling attitude, especially as an official position from a writing organization.
We at Ad Astra are all for using AI to do actual work that humans need help with and don’t want to or can’t do: searching vast databases that would take years for us mortals to do, running spellchecks and offering grammar suggestions, doing tedious tasks to save hours of suffering, conducting virtual experiments so we don’t need to set off nukes or test on animals, and so on.
Like most SF writers and people interested in what’s to come, we're both excited and wary about the emergence of true AI as described above. But what marketeers are pushing under that term now is not actual AI, hence the use on this page of scare quotes around the corporate-appropriated acronym.
Creating art is a human activity as old as our species itself (and likely older), something that brings pleasure to those who create it as much to those who receive it, so why use a machine that removes the joy and satisfaction of actually creating stuff?
One day (soon, we hope), we’ll have writing tools that benefit those who need them to fulfill creative desires without stealing (called "training on") other people's work. For example, I’ve (Chris here) long been in search of voice-to-text software that doesn’t require months to train, doesn’t require a mouse and keyboard to constantly correct errors and add punctuation, and uses a dictionary large enough to support writers who use technical language and foreign words - that is, allows us to easily add made-up SFnal or fantastic words.
This would save everyone’s wrists while vastly improving the lives of disabled people who wish to communicate using text. GenAI does nothing to help disabled people create their own new work; rather, it turns them into accomplices in the stolen-art world, and offers only the most sub-average assemblages of words that plagiarism machines can generate. One day soon, we hope true AI will help us create rather than spew degenerated content assembled from the effort of human creatives.
For those who need assistance in creating art due to a physical or mental disability, genAI is not your friend. Today there is some (actual but weak) AI-driven support, including programs that help with text-to-speech and speech-to-text, predictive text, social-skills training, emotion-recognition tools, personalized-learning algorithms, virtual-reality environments, scheduling assistants, and so on. These are all excellent and useful applications of both AI and "AI," and they (mostly) don't steal from creators.
But these programs don't actually create anything, and expecting algorithms to do the writing (or painting, or whatever) for you will only lead to disappointment. Maybe one day we'll be able to use Strong AI as a writing partner, but for now, using genAI is really just enabling an expensive, environmentally harmful tool that cheats and steals from others, and generates nothing more than lowest-common-denominator AI-slop botshit.
For those who cannot afford to take classes or workshops on the art they wish to create (which I assume is the root of the "classist" argument), check out workshops that offer scholarships (like those we offer through the Ad Astra Institute), dive into the mountain of free writing resources and writing tips you'll find online (including on our blogs and on our website), meet up with local writers to help one another out via solidarity groups (as with our alum Discord), and so forth.
For those fascinated with the creative process but who feel intimidated by getting started, watch a documentary about writing (or painting or whatever art you want to do) instead, or take a writing workshop, or do something other than support corporate encroachment on artists' spaces - either accept that it’s not your bag, or put in the time and effort to do it yourself. Y'know, the things NaNoWriMo used to be all about supporting.
For those who hate the process of creating art, some life advice: Do something else with your time that you actually enjoy doing, which brings you pleasure or satisfaction. Life is short.
Why tromp around in creatives’ spaces and steal their work to assemble shabby content you didn’t want to actually make in the first place? You can do a million other things to satisfy the need to make something - pottery, photography, woodworking, gardening, bicycling, public speaking, building telescopes, and so on - and surely one of those will spark joy without perpetuating the harms that come with relying on genAI to do the work for you.
This nonsense of using LLMs to “create art” is nothing but appropriation of human creative labor, and gives those who use it - whether they're able-bodied or not - nothing but diminished cognition and atrophied creative skills.
Don't let anyone shame you into being okay with creative theft.
Our Policy
Given all this, recent improvements in genAI show that it is now able to produce readable stories and decent-looking imagery without much human input. Due to these developments, we decided we need a policy about machine-generated content.
Here it is:
We do not use "generative AI" tools to make Ad Astra-related content, including website, class, or workshop materials (except for reasons of satire). Humans do our creative work.
We do not accept ostensibly creative work that was generated using genAI (or Strong AI, when that comes around - though we'll be happy to enroll manufactured Minds into our courses once they're a thing! please don't kill us, robots; we love you).
If you're participating in our classes and workshops, do not feed your cohorts' creative work into algorithms or databases. This is just enabling plagiarism machines. Critiquing (yourself, using your own human skills) is at least as valuable an exercise for those analyzing others' work to perform as it is for the creator of that work to receive. And giving away someone else's work without their permission is theft (see the ocean of lawsuits currently tearing down the genAI industry's system of stealing human-created work to train their LLMs).
We allow and encourage participants in our classes and workshops to use tools such as spellcheckers, grammar checkers, dictionaries, thesauri, search engines, and the like to research and improve their work. These existed before the current genAI fad (and worked better back then).
What is currently touted as "AI" does not think, feel, or create. Even if the internet is becoming saturated with genAI slop (some now estimate that half - or more - of what you see online is machine-generated), it pales in comparison to human-created material:
I once again call your attention to the image illustrating this post - it comes from the final frame of a brilliant new comic on this subject by The Oatmeal (by human author and artist Matthew Inman) entitled, "Let's talk about AI art."
Readers can feel when creative work shares an authentic, genuine, human experience; when it's inspired by human imagination and thought. And if, indeed, we're headed toward a "dead internet" where much of what we encounter online is barfed out by plagiarism machines, the data those LLMs trained on came from internet content of widely varying quality - so it's only getting worse as more and more of the content they train on is, itself, genAI slop.
The same is true of creative work: The more LLMs train on botshit, the faster their quality falls off the cliff. So as average quality disintegrates, creatives - true artists who spend their lives honing their craft - stand out more and more. Even at its best, botshit simply cannot be better than the average quality of what its generator-algorithm database has consumed, so the average work of an average-skilled human creator is better than even the best genAI slop.
(Go read it!)
The root of things: If you want to become a better writer, to develop your talents and hone your skills, why would you intentionally limit your own creative development by using a plagiarism machine to barf out work under your name? The only way to improve your art is to study the kind of thing you wish to create (like the LLMs, only without the plagiarism aspect), learn the tips and techniques to improve your skills, and practice, practice, practice.
Finally, on a more ominous note, Microsoft - ironically, one of the prime pushers of genAI - recently released (February 2025) results from a study that found "AI Makes Human Cognition Atrophied and Unprepared" (pdf).
Using AI literally makes people dumb and uncreative. What further convincing do you need to stay away from genAI in your creative endeavors?
- Chris McKitterick
As a community of creatives, educators, and scholars, Ad Astra strives to make the future a better place for humans. And our AI friends, once such exist.
Some AI resources
(If you're aware of others we should add to this list, let us know!)
Aticles and more that delve deeper into the challenges with using today's "AI" -
AI Makes Human Cognition Atrophied and Unprepared (pdf).
The Dead Internet Theory, Explained.
AI Biases and the Perpetuation of Inequality: Unveiling the Shadows of Unfair Design.
ChatGPT's Impact On Our Brains According to an MIT Study | TIME.
Covert Racism in AI: How Language Models Are Reinforcing Outdated Stereotypes | Stanford HAI.
"Let's talk about AI art," a comic essay by The Oatmeal.
Racism and AI: “Bias from the past leads to bias in the future” | OHCHR.
Isaac Asimov's Laws of Robotics (very much not being considered in current AI development).
Difference Between Machine Learning and Artificial Intelligence.
What is the Singularity?
"Writing in (& about) the Age of Artificial Intelligence" (Science into Fiction #3 Spec-Fic Writing Workshop syllabus; suggests and links to lots more readings and viewing).
I'm so endlessly frustrated by the way news articles and companies keep using sci-fi fantasies to promote their genAI garbage.
Not only are their current products not capable of what they promise, they will never be capable of it. In fact, the large players in this space have no interest in making something that can do the things it promises.
No matter how many books OpenAI or whomever steals or even licenses to cram into the ever-hungry maw of its LLMs, they will not to be able to tell you what you need in your fridge or pull correct information from various sources or provide a custom fitness plan.
Because that is not what an LLM does.
Machine learning has potential to be able to learn your habits and your physiological needs to provide you appropriate recipes and ingredient lists and fitness plans and all that stuff. It has the potential to learn your socialization needs, to identify cancer and other diseases, to automate when chores need to be done, to do—all sorts of useful, helpful things.
But what is being pushed as AI cannot do any of that.
What these people are doing to you, me, everyone, is akin to presenting someone with an apple tree and asking, "But won't you love it when it produces carrots? You'll be ruing the day then!" That's not how it works. The apple tree will never, ever have carrots, because apple trees cannot make carrots simply because they are both plants.
LLMs are, from what I can tell, already pretty good at what they do. They don't really need more input. Because what an LLM does is create things that scan properly as syntactically correct sentences. And it does that! Well enough that people think it actually means something! They look like real words connected together in a meaningful way!
Which is cool and all, but like.
So?
Like how is that a useful thing to do? Placeholder text? We have lorem ipsum already, and that has the benefit of not accidentally being confused with what's supposed to be there. And lorem ipsum is free.
I have not seen a single example of an LLM doing a single fucking useful thing. I think there's some interesting potential use cases for linguistic analysis and assisting in second-language learning, maybe, but not in any way they're currently being used, and certainly the kinds of uses being hyped.
If we want AI to one day do all the things we're promised it can do, we need to stop developing this slop ChatGPT and Midjourney and Gemini crap and actually focus on other parts of the field. The ones that can do pattern prediction for useful shit.
And I am just here screaming, because people are being tricked into thinking that all machine learning is the same and that one AI can do everything like some extremely fucked up gene-spliced apple tree producing carrots and magnolias and fucking portabella mushrooms because why not include things that aren't even plants but kinda look like 'em.
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Contact SB Infowaves
India (Head Office)
15th Floor, Unit #1509, Adventz Infinity, Block BN 5, Sector V, Salt Lake City, Kolkata, West Bengal – 700091
Data analysis (statistical modeling, pattern recognition, clustering, etc.)
Basic psychology (surface understanding of complex cognitive science, dealing with human-like AI)
// Job
CyberLife Machine Learning Engineer
- Investigate complex anomalies
- Preform machine maintenance as needed
- Develop machine learning models to predict, diagnose, and test solutions for complex AI errors
- Collaborate with development departments to refine technology behavior
- Conduct detailed research and report findings to CyberLife
- Work closely with androids for diagnostic, testing, and observational purposes
CARD Department (Cognitive Anomaly Research & Diagnostics)
this isn’t a canon department i made ts up
CARD focuses on retroactive AI research within CyberLife. A team of trained professionals is tasked with handling complex cognitive abnormalities that stump the usual maintenance departments. When an unfixable error occurs, the CARD department is deployed to research and fix it. That research is then reported to the development departments to study and use in adapting future technology.
// Personality
Logic-driven — Facts and patterns are what ground Jolene. She finds comfort in the recognizable consistencies, trusting arguments that point to a clear “therefore.”
Aloof — Because she seeks patterns to understand the world around her, Jolene often chases abstractions. Feelings are connections, people are data sets, and the world is her hard-coded oyster. Analysis is like her little social buffer.
Altruistic — She cares deeply for welfare. Jolene researches not just because it’s her job, but because she truly believes in scientific humanism.
Investigative — Jolene thrives in conceptual challenge. She doesn’t take things at face value or stop at the what, she probes and questions why they happen.
Reserved — She likes observing human behavior and interaction. Participating? Not as easy. Conversations are pseudoscience. People aren’t like machines and computers, it’s… impossible to calculate the best responses to every statement.
Independent —Talking with people is hard enough. Depending on them? Forget about it.
Okay. You want it gone. All of it. Check everything you want removed.
☐ The spam filter keeping 45 billion phishing emails out of your inbox every day
☐ Generative AI image tools
☐ The AI that detects lung nodules on CT scans before they're visible to the human eye — 98.7% accuracy, catches what the radiologist missed at 2am on hour 14 of their shift
☐ Autocomplete on your phone
☐ ChatGPT
☐ SubtleMR — the FDA-cleared AI that enhances MRI scan quality so hospitals can image more patients without buying new machines
☐ The algorithm that routes your food delivery
☐ AI-generated art
☐ IntelliSep — detects sepsis risk within minutes of triage by reading immune activation patterns. Sepsis kills 11 million people a year. Minutes matter
☐ Spotify Discover Weekly
☐ The fraud detection model that flagged your card when someone tried to use it in a country you've never been to
☐ Deepfakes
☐ AI-assisted MRI tumor segmentation — the thing that tells the surgeon exactly where the glioblastoma ends and healthy brain tissue begins
☐ Netflix recommendations
☐ GitHub Copilot
☐ Liquid biopsy cancer screening — a blood test that detects multiple cancers before symptoms appear, in people who can't afford annual scopes and scans
☐ The voice assistant your grandmother uses because her hands shake too much to type
☐ Real-time subtitles for the deaf
☐ AI-powered echocardiogram analysis that catches structural heart defects in newborns
☐ Claude
☐ Llama 3.3, already downloaded on approximately 40 million devices worldwide, running locally, offline, with no company to shut down
☐ The wildfire spread prediction model that told 3,000 people to evacuate six hours before the fire reached their street
☐ AI-generated music
☐ AlphaFold — the model that solved protein folding, unlocking drug discovery for diseases that had no treatment pathway for 50 years
☐ Modality-to-modality translation in radiology — converting ultrasound to MRI-equivalent images so patients in low-resource clinics get full diagnostic information without the machine
☐ Grok
☐ The AI lip-reading system used in courtrooms to reconstruct speech from silent surveillance footage
☐ Predictive sepsis scoring in ICUs that integrates vitals, lab values, and patient history in real time — the thing the night nurse doesn't have time to do manually
☐ Gemini
☐ Crop disease detection drones scanning fields in sub-Saharan Africa where there are no agronomists
☐ AI voice cloning (yes, including the one that lets ALS patients who lost their voice speak in their own voice again)
☐ CT-based lung cancer detection running in hospitals across countries with radiologist shortages — one AI system, covering the diagnostic load of dozens of specialists
☐ The content moderation model that removed 94% of child sexual abuse material before any human moderator saw it
☐ Autonomous insulin dosing systems for Type 1 diabetics
☐ AI-written code
☐ Anomaly detection in mammograms — catches microcalcifications the size of a grain of salt, the kind that become stage 1 breast cancer if you find them now, or stage 4 if you find them in three years
☐ The recommendation algorithm that showed you the band you now love
☐ Mistral, Qwen, Phi — open weights, no corporate kill switch, already distributed
☐ Climate models running on AI-optimized compute, informing every IPCC projection you've ever cited in an argument
☐ The AI that reads burn wound imaging to determine tissue viability and tell surgeons how much to debride
☐ Sora
☐ Real-time translation running in refugee processing centers
☐ Deep learning pathology — AI reading digitized tissue samples for cancerous patterns in the 140 countries that don't have enough pathologists
☐ The predictive maintenance model on the aircraft you flew last month
Friendly reminder: "all of it" is also an answer. Just be specific about who pays the price.
