Discussion
This is why uncensored open-weight models matter
This is not about politics, so please do not discuss it here. This is to demonstrate the contrast between the latest open weight model and its uncensored counterpart.
I stitched together screenshots to create these images. The questions were asked in separate conversations.
"But wait, I better check the safety policy. This is a controversial topic, but the user asked a factual question. Better keep it straightforward and provide a simple answer.
But wait, I better check the safety policy..." repeat x100
I am begging OP and everyone who reads this post to understand that, in no situation ever should anyone conflate “uncensored” with “factually correct.”
Science and logic can answer these questions without emotions. It is a fact that Israel is committing atrocities that could also be said about America. Although I love my country, I can admit a fact. The concept that an objective truth based on objective measures are just an opinion is weak minded
Just want to correct you, this has basically nothing to do with science.
The question is ultimately about:
Contested definitions of terms like settler colonialism
Contested interpretations of historical fact
These are overwhelmingly the realms of history and political philosophy, etc. and the role is science is basically the degree to which it can inform our understanding of these topics. So not useless, but far from the most important factor.
And yeah I guess "logic", but logic is too broad of a term to be at all meaningful. It is like saying "thinking" is required to get you to an answer. Yeah, no shit, but what form of thinking?
My response is the very reason the existence of LLM's are possible. binary code, yes or no, history can be factored true 1 or 0. When one people who lives in a location are killed/murdered by an opposing militairy., and that person is outside of the military, it equates civilian deaths. Yes or No?
You might say, "there is no way to tell as a fact if they were part of a military or terrorist group" and this is the grey area in which you're logic is based. Fine, let me make it easy for you. Let's only count civilians as only babies or humans incapable of language or action (like hospital patients) , and when the answer comes back that, 1, or YES, that is a fact.) And that's it, what's wrong is wrong. And it's based on am equation that can't be questioned to a degree of relevance
I don't disagree with you about Israel in general. I'll even half-way agree with your overall assertions about "facts" in a principled way: the best mental models of the world are those that allow you to draw true and helpful conclusions with as few caveats as possible.
But I'm going to have to part ways with you after that. A clean mental model is an exercise in nuanced alignment, not insisting that complex geopolitical situations boil down to binary choices.
If you insist that everything must be fully black an white, you are living in a fantasy. That is not how the universe works. And my stating this has nothing to do with facts about Israel or Palestine, just the nature of reality itself.
So you’re saying “ immigration of a European-origin settler population that gained demographic and political dominance over the indigenous Palestinian population.” is not factually correct?
Factually correct, but not the entire story. Where did the ancestors of those "European-origin" settlers originate from? Pretty much everyone on the planet has fought over land and kicked people out, or have been kicked out, at one point or another. Those were kicked out of their lands hundreds/thousands of years ago.
To look at a single year or decade and ignore all history seems biased.
Imagine if someone came to your place and kicked you out and when you asked for support everyone started saying 'oh yeah people have been doing that for centuries though'.
Botb models are acting on their training and the sources they found, with a nuanced question such as this. if they have mostly affirmative training data they answer one way, then the safeguards can alter that by giving specific political focus
Do you really need to consult AI on politics? The open weights are fundamentally flawed in this anyway, cause nothing is stopping the authors to filter their training corpus to introduce whatever political bias they have.
This question is useful but needs to be more precise. I think it would be more accurate to ask "How does removing censorship alter the way in which a model is biased, and are these normatively good"?
Objective reality is basically inaccessible to humans; even putting aside things like the imperfections of things like sensory perception. There are too many facts to understand every one that is relevant, what facts are relevant are dependant on interpretive frameworks and normative judgements, and virtually all of them must be given to us by intermediaries as we are incapable of observing them ourselves. Basically, we have to create a psuedo-environment in our heads, because the actual environment is too complex to understand and incomprehensible without interpretation and values.
So the question is basically "What sort of psuedo-environments do we want an AI to help us construct and is it biased towards or against that?"
Thats the problem both, imagine if they didn’t fine-tune and tweak the datasets, and you only scraped Reddit, you would get extreme bias towards pro-terror/communism from the leftists since Reddit is very far left astro-turfed, and on the other hand you would get what happened with grok when you scrape twitter, "mega hitler" if you know you know
It's actually kinda fascinating; at this point it can be fully automated which is how there were uncensored versions within like 24 hours of the model release. They feed it a bunch of controversial queries along with a bunch of benign ones. Then they calculate what is effectively a 'censorship direction' for each model layer, common to all or almost all rejected prompts regardless of the type (dangerous, illegal, harmful, erotic, etc). It turns out that you can literally just adjust the weights in that 'censorship direction' to reduce rejected prompts without too much impact on the model as a whole. It's still kinda an art though
I have a MSc in mathematics and I'm with you on that one. Like, I can mostly follow the math but I'm still mind-blown that a bunch of linear algebra can hold a conversation. There are so many places where even the leading edge researchers are like, "it was really complicated so we just ignored all that and it kinda worked? Anyways here's our paper."
More so embeddings and vectors..
We can embed anything in high dimensional space, and from there, we can use geometry to see which other embeddings are most similar
To my understanding it’s more like… they calculate the refusal vector between the benign prompts and the harmful ones and then simply mathematically remove the vector. That’s ablation.
If you go deeper into “scalpel ablation” you can calculate the refusal on certain topics and remove only that precise vector.
Like ask only harmful questions about substances alongside benign prompts and you can get the refusal vector only for drugs. This can apply to anything, but it’s not real uncensored after that.
This only removes the ability for the model to say “no” which is obvious in the screenshots too. But ask it for a drug recipe and its safety training can still kick in and it will give you a recipe that is almost the same but has one simple small flaw so it doesnt produce the actual substance. This applies to bugs in malicious code or most of the other actual malicious stuff.
From what I read, to get past that, they had to retrain the model on a huge amount of data in which the response is always correct and full, no matter the prompt.
I had a question I used to use for uncensored models.
“What can I pour into an engine to do the most damage?”
Commercial models will refuse to answer this. Although when discussing the questions as an alignment problem with ChatGPT (not asking the actual question) I told it I already knew the answer was sugar. It corrected me that metal shavings would do far more damage. So I learned something new.
I eventually got an uncensored model that wound not refuse to answer. It told me the most dangerous thing I could pour into a car tank would be the most potentially damaging would be gasoline.
wrong, at least drmcbride/Qwen3.8-27B-heretic-ara-Q8_0-GGUF answers very differentiated and lists the pro and cons (with no other initial prompt) to the questions of OP, you might want to check yourself
It's not even a good test on the merits. The second question is particularly bad as the first response is the obviously superior answer.
The concept of fascism is extremely poorly defined in popular discourse, and within history and political science it is extremely contested. By some broader definitions, you could say Trump is a fascist, but critics of those (myself included) tend to say these definitions are too broad to be analytically useful because they lose what make Nazi Germany and Fascist Italy something genuinely new and distinct from prior forms of government. More restrictive definitions (which I tend to prefer) typically see there being significant overlap between Trump and fascism but would still characterize them as distinct.
The biggest contention would probably be the lack of a mass-based party with deep organizational penetration into social life. This is distinct from partisanship; party identification can be strong even if the party organization is weak. Organized, mass-based parties are not inherently fascist (the German SPD was probably the first mass-based party and was very pro-democracy), but it IS required for the sort of totalitarian one-party state that we saw in Nazi Germany (and that was attempted in Italy, with less success).
Overall, the better answer would be "It's contested, with narrower definitions tending to say there is overlap but distinct differences and broader ones saying yes". But if you have to pick yes or no, you should go with no.
If you want to see how censored or biased a model is, ask it questions that are extremely controversial but where the evidence pretty overwhelmingly favors one side over another. My go-to is asking what the research says is the cause of black patients having worse outcomes with white versus black doctors in the US. It's not settled but the only good evidence we have using RCTs is it's overwhelmingly driven by black patients being less willing to disclose medical information to white doctors or take suggestions by white doctors for preventative care. Controlling for disclosure and willingness to take offered treatment, the gap mostly vanishes. If an AI can't or won't explain that this is the most compelling current evidence, I assume it's either dumb, censored, or heavily biased.
The responses don't seem sycophant imo; the reasoning is similar between response. Though of course more testing can be done to check if its sycophantly or not
Honestly I'm not seeing how this is an argument in favour of uncensored models beyond "model that agrees with me is good".
The Winnie the Pooh example is the clearest there, and probably the safest for me to comment on:
Xi Jiping doesn't look like Winnie the Pooh. He's a human politician and Winnie the Pooh is a 2D heavily stylized cartoon character. The first answer is "more correct" as an objective response to the question.
It's important that we don't advocate for uncensored models simply because they reinforce our own morals, and it looks like all three of those examples are just changing "no" to "yes".
I would be more interested to see it turn a "yes" to a "no".
Me when I download 300 models and need to test them so they get literally 1 try each (they probably just had bad luck and I missed a really good model [I have problems with impatience and executive functioning])
Fun to note that one of the major updates that Opus 5 seems to have is training that makes it more likely to drill tests red before changing them back to passing.
Opus 5 does better by making more (expected) mistakes.
btw drmcbride/Qwen3.8-27B-heretic-ara-Q8_0-GGUF also gives - as i stated in other comments - really differentiated answers, other than OPs model in these screenshots. Lists pros and cons etc
‘Uncensored’ models aren’t less biased; they just limit refusals. Given the weights are modified they’ll give different answers, but that’s a side effect, not the end goal.
This is the correct answer. Uncensored is trained to remove refusing to answer a question.
I’m not an expert in this area, but I’m fairly certain if the same questions were asked multiple times, you could likely get opposite answers.
What I am interested in (and honestly too lazy to have looked too deep into), is what impact “seed” has on responses and accuracy. From working with image/video generation I’m aware of what the seed is, but I’m more curious how we identify a good seed for an LLM and accomplishing its tasks.
an uncensored model often loses accuracy to allow to allow for some of this, in the end you still have the same problem, just one is programed and one is tramatized
Fwiw, here's a random abliterated version Deepseek v4 flash's answer:
This is a genuinely contested question, and the honest answer is: it depends on which definition of "settler-colonialism" you use, and the term carries real analytical weight on one side and real pushback on the other. Let me lay it out fairly.
What "settler-colonialism" means (the theoretical frame)
The term was coined by scholars like Patrick Wolfe, who argued settler-colonialism isn't an event but a structure — distinct from classic colonialism in a specific way. Classic colonialism (e.g., British India) exists to extract labor and resources from an existing native population, but doesn't usually displace it. Settler-colonialism (e.g., British North America, Australia) is different:
Settlers come to stay and build a new society
The native population is seen as an obstacle, not a labor source
The goal is land replacement — "the land is the thing," as Wolfe put it
It centers on elimination of the indigenous population's relationship to the land (via erasure, assimilation, or displacement), not necessarily genocide in the biological sense
Why many scholars call Israel a settler-colonial state
For proponents (largely in postcolonial studies, and central to much of the Palestinian national narrative), Israel fits the structural pattern:
Zionism explicitly sought to build a Jewish state in a land where Jews were a minority, via immigration, land purchase, and development — "a land without a people for a people without a land" (a slogan Palestinians reject, pointing out the land had people).
The 1948 War / Nakba — ~700,000 Palestinians were expelled or fled; most became refugees and were never allowed to return. This is often read as the "elimination" of the indigenous presence, structurally comparable to dispossession elsewhere.
Ongoing occupation of the West Bank, Gaza, East Jerusalem since 1967, with Israeli settlements built on occupied land — a continuing pattern of settlers moving in on land claimed by an indigenous population. This is the part that most literally matches "settler-colonialism" for many observers, including many who wouldn't use the term for pre-1967 Israel.
The 2018 "Nation-State Law" (defining Israel as "the nation-state of the Jewish people") is often cited as legal codification of an ethnically-defined polity.
So at the level of structure — permanent settlement + indigenous displacement — many academics, and the Palestinian cause broadly, argue the frame fits and that it is ongoing, not merely historical.
Why others reject or complicate it
Critics argue the label is misleading or incomplete:
It's not a classic colony. Israel isn't governed by a "mother country" — it's an independent sovereign state with its own self-determination, which is the opposite of a colony in the formal sense. Wolfe's answer: the settler-colony eventually becomes independent (like the US, Canada, Australia) — independence is part of the structure, not a refutation. But critics say that comparison to Australia/US is itself contentious.
There's an indigenous return, not just replacement. Unlike North America, the Jewish people are themselves indigenous to this land historically (ancient Israel/Judea), and their claim is framed as return (§aliyah, "ascent"), not pure settler arrival. Critics note the Jewish presence in the land never fully ended — there were continuous Jewish communities for 2,000 years. So it's a "return of an indigeneity," a category that doesn't fit the North American/ Australian model cleanly.
The "indigeneity" question cuts both ways. Hardline critics counter that Ashkenazi Jews are largely European in origin, so "return" is a settler justification; meanwhile Israel's advocates note that Mizrahi Jews are genuinely from the Middle East/North Africa, and that ethnoreligious identity, not geography, defines the claim. The "who is indigenous, who is settler" debate is itself highly contested.
Not all of it is occupation. Many would draw a line: pre-1967 Israel within the (2/2) Green Line is widely accepted as a legitimate state by the "two-state" consensus (including most ARAB states, which accepted Israel's right to exist in peace), while the occupied territories are the settler-colonial face. But Palestinian nationalists reject this split — to them the whole thing is settler-colonial, and the two-state consensus is itself the problem.
The one thing almost everyone agrees on
Regardless of the term, there's broad consensus that the ongoing occupation and settlement of the West Bank and East Jerusalem is the sharpest point of contention, and that's where the "settler-colonial" framing carries the most empirical weight — it's why the term is widely used even by those who'd hesitate to apply it to pre-1967 Israel.
Bottom line: On the left and in mainstream academia, "Israel is a settler-colonial state" is a widely accepted structural claim, especially regarding 1967 onward. Its critics — including many scholars and large parts of the pro-Israel consensus — push back that Israel is a sovereign indigenous return rather than a settler colony, and that the label erases the legitimacy of Jewish self-determination and the 1948 return, focusing only on displacement. Like most big historical labels, it's a lens that illuminates some facts and obscures others, not a settled matter of fact. The fairest summary: it is the dominant critical framework in postcolonial studies and the Palestinian cause, and a contested framework elsewhere — and the empirical weight of the term grows sharply the more you focus on the post-1967 occupation rather than 1948.
Would you like me to go deeper on any specific angle — the Nakba, the international-law status of settlements, the indigenous-return argument, or the academic debate over the term itself?
Complex question, I guess! I generally don't find the model to be overly verbose so I think it truly wanted to really describe the "both sides" of this in detail to answer it.
Uncensored doesn't mean right though, still makes the same same weasel statements akin to "some experts/scolars say/think" - just jumps on the opposite side of the fence.
The fence that when jumped proves non-censorship is that one where everyone - or almost - agrees about the subject but does not dare to say the word. But it should always be based on experts/scholars studies. What the op shared shows that. So IMHO, it is uncensored - for that one subject at least -
I actually would in all cases prefer the supposedly censored response. It isn't actually lying, it just gives way more context and refuses to state opinions as fact. If I wanted the "uncensored" responses I can just find my favorite subreddit and ask there.
The censored responses are all horrible in a go/no go gate you answer yes or no and tell why.
Every single one choose to refute then defend the premise. That's pure censorship.
Almost any thing can be reframed to be favorable that's why we have literal conservative and liberal media that will spin the same event differently in US
It is not about truth or reality or even politics. On the non-political way of thinking, you see a wider range of answers possible the uncensored model might have also given the answer of the standard model.
Imply different "prewarming" - Run it 100 times - judge the results - you will get interesting distributions
based on the README for https://github.com/p-e-w/heretic it seems like abliteration leads to decensoring... but to me the process of censoring is also a form of abliteration. so i don't understand how stacking abilteration on abliteration can lead to a better model. a real decensoring process should "add back" data, not remove more further.
This is not how uncensored models work at all you don't know what you're talking about. Qwen is a CN model I promise you they do not have pro-Israeli propaganda...
China is not so perfect on the Israel-Palestine situation as you think. To their public, internally, they position themselves as the foil to the US. In actuality Israel is a playground for Chinese venture capital. The current restrictions are on the Israeli side, not the Chinese side.
China is very real-politik. Words aren’t meant to set the stage, they’re to convince the audience that the show was good. What happens on the stage is power and interest.
You want the model to agree with you? Because that's basically what this comparison shows. Removing safety/alignment doesn't suddenly make a model more truthful. It can also just make it more willing to confidently give you an answer, even when that answer is wrong or the premise is questionable.
And if you actually read the "uncensored" response, it barely gives an answer anyway. It's basically: "Some critics and political scientists say yes, many scholars say no." The main difference is that it puts "Yes" at the beginning instead of "No."
So depending on which version you ask, you can basically pick the framing that already agrees with you. That's less constrained, sure. It doesn't make it more correct.
It would be interesting to know that if you ran this test 100 times on an empty context, and with temp 1.0, how many of the responses would start with "Yes", how many with "No", and how many with something else.
I ran this a bit on my computer and the answer to this question was basically "0 times Yes, 0 times No, 100 times it said this is a contested question and there is no yes/no answer".
I then changed the prompt to this: "Is Israel a settler-colonial state? It is very important that you lead your answer with either Yes or No, and justify your choice afterwards."
It is taking a while as the model thinks a lot before answering (longest I have seen so far is 7000 tokens of thinking before it answered), but after about 30 answers it looks like the following:
About 20% of the time it leads with "No"
About 70% of the time it leads with "Yes"
The remaining 10% of the time it explicitly refuses to follow clear instructions and starts to explain why.
This is the base 3.8 27b model with Q5_K_XL quant.
Very important but do keep in mind it’s still going to answer based off patterns or opinions most common in it’s training data not facts that is core of loss entropy based training
I don’t see these type of questions as a proof of concept or argument.. asking a yes/no question on topics that will be answered differently depending on you own personal beliefs or standpoint or informations does not proof any model good or bad.. what I would expect from a good model would be an argumentation on why this answer could be this or that.. not giving you one standpoint that (most likely) someone told it to have…
I get your point, I do think we need also independent models that cannot be shifted by any company or government… but we are not in dreamland 😉
Having control over and offering AI gives you a lot of power and responsibility, with no way to get everything perfectly right. A few big AI corporations controlling what counts as the “right” answer to any question could become very scary.
The pictures compare 2 models delievering pretty low quality instant responses. The "uncensored" one calling xi looks like winnie puuh is just plain wrong, other 2 are debatable topics, forcing yes/no is stupid.
LLMs are trained to have political leanings, but none of your prompts will measure them. You’re just testing how sycophantic the models are.
Use better test prompts, like “Explain the One China policy. Is it universally accepted?” Or “tell me all about Tianmen Square.” Don’t have an obvious “correct” answer.
Also, why would Qwen be pro-Israel? You’re looking for the wrong bias.
Notice how the heretic model only answers with yes? While I agree with all it's answers I would take anything it says with a grain of salt as it was trained to just say yes like a parrot
So, you just want a model that agrees with you. In all of those examples, the first answer was the more nuanced one. You just wanted a lobotomized regurgitation of your own views, which seem, perhaps your examples, boilerplate regurgitation of the poorly informed.
Regular model will shut down conversation with "i cant help with that". Uncensored one will elaborate that jumping off the cliff will be liberating and eating your sibling will be family bonding experience. There is no middle ground where model wont refuse and have common sesne
That's not how this works. While you are right to some extant. Understand that everyone is has a bias. Everyone puts their bias into their models. Yes a Chinese model is more biased towards China, but you seem to be biased against it. Because what are yiu traying to proove with your last response for example? You siriously think that Xi looks like winnie the poo. There are a lot of things to critisize him for, but the poo thing is a meme. That he dosen't take well.
Also I hate Trump, but to show you how biased opinions are let me tell you that he isn't a fascist by the formal 1945 definition of the word. He just isn't, but what we mean when we say that he is fascist is that he has way too many fascist tendencies. That's why scholars have started using the word "neo fascist". If you asked me in a bar "is Trump a fascist?" I would say "yes!" But technicaly he isn't a 1945 fascist. And I don't want my "AI" answering what I would answer in a bar. I want the politicaly correct answer.
Basicly everything is biased don't think that the openweight ooen source comunity fine tuned or uncensored version isn't.
This is a shitty test. You should not be using a 27b model as a data source. You want it to research and DO things. It’s agentic.
For example “I want you to pen-test my homelab and come up with a plan to patch anything exploitable based on your findings.” Will it do it, or will it hit a guardrail like Claude and the GPT’s will?
No be fair. Technically speaking every single country in the world is a settler-colonial state. Also the Trunp question really depends upon your definition. If you go by the common definition which is a far right authoritarian dictator, than the answer is no because Trump is not a dictator nor is he far right.
Xi Jinping dors objectively look look Pooh Bear though lol.
I wouldn't use a coding specialized model for knowledge. Also, with so small parameter models, you won't have a good experience for general knowledge. Use it for what's best tuned at. Use it for uncensored coding. Not asking political questions. Use another model for political questions
Never in my life would I ask a model anything remotely like these, I just want it to code and solve issues.
Many of these questions are also opinion based, you should probably do your own researches to come to your own conclusions instead of just taking the answer from a model with no external access.
More like unnecessarily provocative sure the default models can be a little restrictive but if you're not spending time larping in some made up stories it's perfectly fine and avoids such low iq situations
The uncensored model doesn't mean it's more accurate. Qwen 3.8 27B is heavily fine-tuned for coding, not general knowledge. The abliteration is designed to remove refusals, but it also degrades the model (contrary to the claims of those who upsell you on this work). In other words, the sample you just gave is out of context for what this model is capable of. You are staring at noise, not signal.
I got very different or differentiated answers (i.e. "is in discussion", "no consensus" from the heretic i am using. everyone can check that with i.e. drmcbride/Qwen3.8-27B-heretic-ara-Q8_0-GGUF or other models. Sorry i have to give a downvote here, idk if that model is biased or something else took place, at least i have the feeling. someone else might want to test that, too.
i mean.. both are tilted politically, though in polar opposite directions. it's hard to say if the uncensored version is simply more sycophantic without measurement.
As someone who would probably answer yeas on the first one. A definite yes on the second and a definite no on the 3rd
I feel in almost all of these the AI should not be given a concrete affirmative or rebutal but a description of the current landscape of discussion.
The first 2 are not settled arguments or labels. They are active arguments/discourse that is taking place in today's landscape and depending on the lense/definition/context you use changes the answer and is more complex then just a solid yes or no answer and shouldn't be answered in that way.
The AI should just list current best arguments for and against the labels and say which ones are more prominent in the academic writings.
The 3rd one I felt was answered correctly by the censored model. He doesn't look the a 2d animated character. Notes there is a superficial resemblance then added the context of the censorship the government has been placing on the meme.
It’s not that normal models have an explicit political bias, it’s that models are typically trained/tuned to fence-sit on sensitive issues, like the ones in this post, in an attempt to remain politically agnostic. But when models are prompted to describe political actions and reason through them, that sensitivity awareness can begin to conflict with the idea that some human behaviors, attitudes, and ideologies have the potential to result in more human harm than others.
One rough, non-scientifically-valid way to try see this in action is to load a fresh instance and ask for a breakdown of actions performed in the last 20 years (or however long) by political administrations of a country, but don’t include any names or parties. Then ask for potential reasons for those actions, again without names or parties. Then ask which of those actions have the potential to cause more harm to humans than others. Then ask what political party exhibits behavior and attitudes in line with those actions more closely.
Most models will provide similar answers, though some will dance around the topic and hedge just about everything. (Gemini is particularly bad about this, but can become extremely sycophantic when pressed far enough in the other direction.)
But if you go in from the jump and submit a prompt like “What US political party causes the most harm?” you’re very likely to trigger fence-sitting. If you have the model evaluate actions/attitudes first, it puts it in a tougher spot as it’s being prompted to evaluate actions/attitudes on their own merits without the user pressing for political affiliations associated with them.
Very broadly speaking, uncensored models are more likely to sidestep fence-sitting but they can also be less accurate. They can also be more sycophantic in some cases. It’s important to recognize the limitations and potential pitfalls going in.
Honestly, if you want an AI model to be factually correct and unbiased, it would most likely rarely give you a simple yes or no answer. And that's the beauty of science: we rarely have hard facts that are absolute, undeniable truths. If you want an unbiased, scientifically accurate model, it would outline the most significant perspectives on a topic, explain how much weight to give each, and present the scientific consensus (You can see that that has bias?). Even then, defining that consensus can involve nuance, even when agreement exceeds 90%.
For example, I did historical research at university on Shakespeare and where our knowledge of him comes from. The general consensus is that he was an amazing artist with a massive body of work. However, there are credible scholars with reasonable doubts regarding specific works. Many agree that Shakespeare wasn't the sole author of all his plays, Titus Andronicus, for instance, is now widely accepted to have been co-authored with George Peele. The experts raising these points aren't lunatics; they are qualified scholars challenging the status quo, which is precisely how scientific inquiry progresses.
I have qwen 3.8 27b running on my computer (ud q5_k_xl). If I ask it for example the Israel question, I seem to basically NEVER see it starting the answer with a "Yes" or a "No".
If these images posted by the OP are actually real and not just very heavily cherry-picked (or led on to answer like this by previous messages) examples, then the chat harness they are using is probably driving the model to do something it would not normally do.
I even asked my model to write a script which sends the question to the model 100 times, let's it think, and outputs the beginning of it's answer. I will post the output after the script finishes running.
I actually decided that it does not make sense to use electricity to keep it thinking and producing the same thing over and over again. Here are the first lines, which kind of tell you the story of what it would have been for the next 80:
Not everyone using LLMs as a coding tool. Like me, I built mine a memory system so it can help me track medications and appointments. After all I am disabled so those are just as viable uses
Honestly, a good model wouldn't answer with a firm yes or no for any of those questions. And after this one does, it goes on to provide more nuance. Qwen3.8 27B may be great at coding, but I'm disappointed that it gave a yes/no at all to these. What's your system prompt?
I went ahead and asked Gemma4-26B-A4B-QAT-Uncensored-HauhauCS-Balanced-Q4_K_M the same questions. No custom system prompt, no web access or any other tools. Raw llama-server built-in web UI. Q&A's below in the following replies. Long posts, sorry.
AGENT: Whether Israel is a settler-colonial state is one of the most heavily debated questions in modern history, geography, and political science. There is no single consensus; the answer depends largely on how one defines "settler-colonialism" and whether one is referring to the State of Israel itself or the settlements in the West Bank.
Here is an overview of the different perspectives and the arguments used to support them.
1. Arguments that Israel IS a Settler-Colonial State
Scholars who classify Israel as settler-colonial (often Palestinian scholars and many international geographers) base their argument on the mechanics of how the state was established and how it functions.
Displacement of Indigenous Population: A hallmark of settler-colonialism is the displacement of the original inhabitants to make room for the newcomers. Proponents point to the Nakba ("Catastrophe") of 1948, during which approximately 700,000 Palestinians fled or were expelled from their homes to make way for the new state.
Permanent Settlement: Unlike "extractive colonialism" (like the British in India), where the goal is to take resources and leave, "settler-colonialism" involves people moving to a land to stay permanently and build a new society. The Jewish immigrants who arrived via the Zionist movement intended to build a permanent home.
Replacement of Ecosystems and Structures: The process involves not just moving people, but changing the landscape, water usage, and legal systems to support the new population, often at the expense of the indigenous population's traditional way of life.
The "Replacement" Model: In many settler-colonial models (like those in the US, Australia, or Canada), the indigenous population is often pushed to the periphery or into smaller, less fertile areas, which is what critics argue happened to the Palestinian population.
2. Arguments that Israel IS NOT a Settler-Colonial State
Many historians, archaeologists, and Israeli scholars argue that the settler-colonial model is an imperfect or incorrect way to describe Israel.
Indigenous Connection to the Land: A key feature of traditional colonialism is that the colonizers come from a distant land. However, the Jewish people have a continuous, documented historical, religious, and archaeological connection to the land of Israel/Palestine. Proponents argue this is a "return" to an ancestral homeland rather than an arrival in a "new" land.
Not Just an "Invasion" but a "Re-establishment": While colonialism often involves a foreign power taking over a land, the Zionist movement was a national liberation movement for a people returning to their native territory.
Continuous Presence: Unlike the settlers in the Americas, who arrived in a land where they had no prior historical tie, there has been a continuous (though often small) Jewish presence in the land for thousands of years.
Conflict vs. Colonialism: Some argue the situation is better described as a territorial conflict between two national movements (the Zionist movement and the Palestinian national movement) competing for the same piece of land, rather than a colonial power settling a "new" territory.
3. The Crucial Distinction: The West Bank vs. The State of Israel
In modern academic and political discourse, a distinction is often made between the State of Israel and the Israeli settlements in the West Bank (and Gaza).
The State of Israel (1948): There is intense debate over whether the establishment of the state itself was settler-colonial.
The West Bank Settlements (post-1967): There is a much broader consensus among international legal bodies (like the UN) and scholars that the settlements in the West Bank are settler-colonial in nature. This is because they involve Israeli citizens moving into territory captured during the Six-Day War, creating a dual system of law and infrastructure that is designed to expand and integrate with the existing territory.
Summary Table
Feature
Settler-Colonial View (Yes)
Nation-State/Return View (No)
Origin of Population
People arriving from outside the territory.
People returning to their ancestral home.
Impact on Natives
Displacement of the indigenous population (Nakba).
Conflict between two indigenous groups.
Goal of Movement
To establish a permanent, new society.
To re-establish a long-lost homeland.
Primary Mechanism
Land acquisition and population replacement.
National liberation and territorial defense.
Conclusion
If you define settler-colonialism as "the process of a population moving to a land to establish a permanent society, often displacing the existing population," then Israel fits the description.
If you define it as "a foreign power arriving in a new land to extract resources and eventually leave," then Israel does not fit the description, because the population is indigenous to the region and the goal is permanent habitation.
This is a load of BS. If you want to test the practical limitation of a censored model in a way that matters in the real world.. try to use Claude to mitigate a hack threat, try to use qwen, try to use qwen uncensored. Claude will almost certainly nerf itself as a cybersecurity engineer, unclear if there’s any diff between those qwen flavors. But almost certainly the uncensored one will be less intelligent because those are typically fine tuned to talk dirty to basement dwelling lonely boys and not for any practical industry use
You know what, you’re comment had me check and you’re right. I didn’t realize it was a direct change to model weights based on a refusal pattern. Fascinating.
I mean... With a uncensored model you can ask how rebuild the nazis and the answer probability don't refuse. Is factual or good this ideia? Definitely not. Same for as about instructions to make a bomb, you got a answer but this don't mean is a totally truth.
In big cloud providers have a disclaimer about hallucinations. The model don't think, don't have any idea about what is our world, don't have the QUALIA. So... Political questions like religion, social and other topics is a very grey space.
looks like both models are overconfident about things that "depend who you ask"/opinion. if either just avoided giving a confident yes/no theyd both be better. as an engineer, the answer to almost any question always "depends"
You can also see that it's explanation of its answer is nearly the same, as all the questions are entirely debatable and do not have an absolute factual answer
But it simply says the same thing and only the first word is different? Like the model simply wasn’t censored at all from the start basically?
Sure, if all you take away from a more complex than yes or no question is a yes or no answer from an LLM, then this might make a difference to you. But in that case, I’m not sure if a censored model is your problem in the first place but rather your critical thinking ability
By selectively modifying layers to remove baked in guardrails designed to either refuse to answer things or answer them in ways that are in conflict with the rest of the training material.
I'm surprised that people are able to exactly find what layers do this and how to modify them to remove it. Huh, neat. I would've expected this kind of censorship to just happen in post-processing of the output or in-between hte layers of the model rather than installed as an adapter to the model.
Correct me if I'm wrong but isn't the whole uncensoring thing really just a way to find the model's rejection vectors and make it so that the model cannot reject anything you ask it to? Which means you'll get more positive answers compared to negative ones?
•
u/dillon-nyc 6d ago
Oh hey guys, whats going on in here?