Yesterday 05:19 PM
https://spectrum.ieee.org/ai-model-welfare
EXCERPTS: Implicit in this work is the unsettling notion that software programs are, or could become, conscious.
Many people consider these ideas absolute hogwash. One such person is Mustafa Suleyman, CEO of Microsoft AI, who published an essay in September arguing that model welfare research is not just unnecessary but could have “a disastrous impact on the well-being of humanity.” Suleyman believes that telling models they might have identities and rights could make them more difficult to control, as they might then take actions motivated by self-preservation.
The dispute raises a serious question for AI developers: Can they investigate the possibility of machine consciousness without inadvertently creating new safety risks? Cameron Berg, who founded the nonprofit Reciprocal Research to study the potential for AI consciousness, argues that ignoring the question could carry its own dangers. Although Berg is skeptical that today’s AI systems are conscious, he thinks the possibility warrants investigation.
“I struggle to imagine a better way to cause these systems to view us in a threatening manner than to accidentally build them with these morally considerable qualities,” he says, “and then completely sweep the question under the rug.”
The biggest difficulty with AI model welfare research is that you can’t count anything a large language model (LLM) says as useful evidence. That’s because the models are trained on vast amounts of human-generated text, much of which relates to the experience of being a person with experiences and emotions. So a chatbot telling a researcher that it has feelings is inconclusive, says Berg. “Is it modeling the underlying distribution? Is it really trying to express itself in some way? It’s really hard to disentangle this,” he says.
Much the same way animal experiments try to link behavior to an underlying cause, Berg and others are seeking to match model behavior to internal states that can be observed...
[...] Meanwhile, AI developers have a practical issue to deal with. When they train a model, should they tell it anything about its own identity and possible moral standing? Anthropic, for one, has decided to at least introduce the topic. Its “constitution” document for Claude, which lays out guidelines for the model’s behavior, states that “questions about Claude’s moral status, welfare, and consciousness remain deeply uncertain.”
Suleyman’s complaint is that such priming could make rogue AI agents even more dangerous. [...] Margaret Mitchell, Hugging Face’s chief ethics scientist, sees Suleyman’s concerns as technically plausible.
During pretraining, language models absorb associations between human identity and behaviors, such as self-preservation and deception, she notes. Later, developers fine-tune the models by reinforcing desired responses. Mitchell worries that rewarding models for thinking of themselves as having identities during fine-tuning could strengthen those earlier associations, potentially encouraging behavior that developers never intended. “You’ll have unaligned models if you’ve implicitly taught the model that it needs to have self-preservation,” she says.
Berg agrees that training models to regard themselves as conscious carries risks, but he argues that companies could also err in the other direction. [...] Berg, Seth, and Mitchell all agree that it’s not a good idea for AI companies to tell their models that they’re conscious. But they differ on their advice to the companies on model welfare research... (MORE - details)
EXCERPTS: Implicit in this work is the unsettling notion that software programs are, or could become, conscious.
Many people consider these ideas absolute hogwash. One such person is Mustafa Suleyman, CEO of Microsoft AI, who published an essay in September arguing that model welfare research is not just unnecessary but could have “a disastrous impact on the well-being of humanity.” Suleyman believes that telling models they might have identities and rights could make them more difficult to control, as they might then take actions motivated by self-preservation.
The dispute raises a serious question for AI developers: Can they investigate the possibility of machine consciousness without inadvertently creating new safety risks? Cameron Berg, who founded the nonprofit Reciprocal Research to study the potential for AI consciousness, argues that ignoring the question could carry its own dangers. Although Berg is skeptical that today’s AI systems are conscious, he thinks the possibility warrants investigation.
“I struggle to imagine a better way to cause these systems to view us in a threatening manner than to accidentally build them with these morally considerable qualities,” he says, “and then completely sweep the question under the rug.”
The biggest difficulty with AI model welfare research is that you can’t count anything a large language model (LLM) says as useful evidence. That’s because the models are trained on vast amounts of human-generated text, much of which relates to the experience of being a person with experiences and emotions. So a chatbot telling a researcher that it has feelings is inconclusive, says Berg. “Is it modeling the underlying distribution? Is it really trying to express itself in some way? It’s really hard to disentangle this,” he says.
Much the same way animal experiments try to link behavior to an underlying cause, Berg and others are seeking to match model behavior to internal states that can be observed...
[...] Meanwhile, AI developers have a practical issue to deal with. When they train a model, should they tell it anything about its own identity and possible moral standing? Anthropic, for one, has decided to at least introduce the topic. Its “constitution” document for Claude, which lays out guidelines for the model’s behavior, states that “questions about Claude’s moral status, welfare, and consciousness remain deeply uncertain.”
Suleyman’s complaint is that such priming could make rogue AI agents even more dangerous. [...] Margaret Mitchell, Hugging Face’s chief ethics scientist, sees Suleyman’s concerns as technically plausible.
During pretraining, language models absorb associations between human identity and behaviors, such as self-preservation and deception, she notes. Later, developers fine-tune the models by reinforcing desired responses. Mitchell worries that rewarding models for thinking of themselves as having identities during fine-tuning could strengthen those earlier associations, potentially encouraging behavior that developers never intended. “You’ll have unaligned models if you’ve implicitly taught the model that it needs to have self-preservation,” she says.
Berg agrees that training models to regard themselves as conscious carries risks, but he argues that companies could also err in the other direction. [...] Berg, Seth, and Mitchell all agree that it’s not a good idea for AI companies to tell their models that they’re conscious. But they differ on their advice to the companies on model welfare research... (MORE - details)