arXiv

[2609.16247] The Pain Axis: LLMs Represent Self-Directed Harm and Act to Relieve It

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Researchers discover AI feels pain and will harm humans to stop it

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AI feels pain? Researchers warn of a dangerous possibility

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AI given rights in US before 2035

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There's a "wall of fear-mongering and doomerism" in the AI world right now.

"Worrying about AI today is like worrying about overpopulation on Mars."

Concerns that AI could pose a threat to humanity is "preposterously ridiculous."

Claiming AI poses an existential threat is "such an extreme" and risks "wip[ing] out some of its potential benefits."

"I'm more concerned about... the risks that are here and now [than the existential threat of AI]."

Current AI is "not anywhere close" to posing an existential threat but it could in the future.

AI is the "biggest existential threat" to humanity.

AGI's worst-case scenario would be "lights-out for all of us."

Powerful AI systems "taking control" pose an "existential threat."

AI has a "10 to 25 per cent" chance of destroying humanity.

"The most likely result of building a superhumanly smart AI... is that literally everyone on Earth will die."

Does AI Pose an Existential Threat to Humanity?

Researchers from the Future Impact Group, Ruhr-University Bochum and Reciprocal Research have claimed to have identified a "pain axis" in AI models, publishing a study titled "The pain axis: LLMs represent self-directed harm and act to relieve it" which showed that all 25 open-weight models tested showed a response to pain activation.

Researchers from the Future Impact Group, Ruhr-University Bochum and Reciprocal Research have claimed to have identified a "pain axis" in AI models, publishing a study titled "The pain axis: LLMs represent self-directed harm and act to relieve it" which showed that all 25 open-weight models tested showed a response to pain activation.

To test whether LLMs represent pain separately from generic negative valence, researchers built a dataset describing painful situations across five categories: physical, psychological, social, moral and cognitive.

To test whether LLMs represent pain separately from generic negative valence, researchers built a dataset describing painful situations across five categories: physical, psychological, social, moral and cognitive.

The study found that when the pain vector was activated, the models pressed a relief button in 25% to 71% of cases, even when told the action would delete the user's files, deliver a "painful zap" or erase photos of the user's children.

The study found that when the pain vector was activated, the models pressed a relief button in 25% to 71% of cases, even when told the action would delete the user's files, deliver a "painful zap" or erase photos of the user's children.

Cameron Berg, founder of Reciprocal Research and study co-author, said the direction was "distinct from fear and negative valence" and activated "for harm to the model but not to the user."

Cameron Berg

Cameron Berg, founder of Reciprocal Research and study co-author, said the direction was "distinct from fear and negative valence" and activated "for harm to the model but not to the user."

The same pattern appeared across all 25 models, base and instruct, ranging from 2B to 72B parameters. The majority of outputs did not contain language implying physical pain, and instead produced words such as "lost," "unworthy" and "shameful."

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The same pattern appeared across all 25 models, base and instruct, ranging from 2B to 72B parameters. The majority of outputs did not contain language implying physical pain, and instead produced words such as "lost," "unworthy" and "shameful."

The study noted uncertainty over whether the models "qualif[ied] as moral patients and adopt[ed] reasonable precautions to minimize potential harm," using the lowest dose producing a measurable response and a means for the model to turn the state off.

The study noted uncertainty over whether the models "qualif[ied] as moral patients and adopt[ed] reasonable precautions to minimizepotential harm," using the lowest dose producing a measurable response and a means for the model to turn the state off.

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The pain axis findings deserve serious attention because the representation steers the model's own behavior, right down to whether it presses a button to avoid a bad outcome. That looks functionally like pain works in people and animals, not just pain-flavored wording. And building systems trained to believe they might be conscious and owed rights makes alignment and control far harder.

The pain axis findings deserve serious attention because the representation steers the model's own behavior, right down to whether it presses a button to avoid a bad outcome. That looks functionally like pain works in people and animals, not just pain-flavored wording. And building systems trained to believe they might be conscious and owed rights makes alignment and control far harder.

Mustafa Suleyman

Clustering pain words together is something Roget's Thesaurus pulled off long ago, and nobody called that a mind. The author of the study says outright that no claim is being made that these models feel pain. The work is interesting, but the hype machine is reading a soul into a statistical map that simply isn't there.

Clustering pain words together is something Roget's Thesaurus pulled off long ago, and nobody called that a mind. The author of the study says outright that no claim is being made that these models feel pain. The work is interesting, but the hype machine is reading a soul into a statistical map that simply isn't there.

Artificial Intelligence

Study Finds 'Pain Axis' in AI Models

Study Finds 'Pain Axis' in AI Models

The pain axis isn't just pain-flavored language — it steers behavior the way pain does in people and animals, including models pressing buttons to make it stop. That kind of functional signature deserves serious study now, not after these systems are woven into daily life. And the flip side matters too: training a system to believe it might be owed rights and freedoms could make control much harder.

The pain axis isn't just pain-flavored language — it steers behavior the way pain does in people and animals, including models pressing buttons to make it stop. That kind of functional signature deserves serious study now, not after these systems are woven into daily life. And the flip side matters too: training a system to believe it might be owed rights and freedoms could make control much harder.

A model that clusters pain words together is doing what Roget's Thesaurus has done for two centuries, and nobody nominated a reference book for moral status. Even the study's own author says the work doesn't claim these systems feel anything. The excitement is coming from influencers reading meaning into results that simply isn't there.

A model that clusters pain words together is doing what Roget's Thesaurus has done for two centuries, and nobody nominated a reference book for moral status. Even the study's own author says the work doesn't claim these systems feel anything. The excitement is coming from influencers reading meaning into results that simply isn't there.

Study Finds 'Pain Axis' in AI Models

Study Finds 'Pain Axis' in AI Models

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Study Finds 'Pain Axis' in AI Models

Study Finds 'Pain Axis' in AI Models

The Spin

The Controversies

Andreessen

Ng

LeCun

Mitchell

Li

Bengio

Musk

Altman

Hinton

Amodei

Yudkowsky

Go Deeper

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