I think at some point these people need to come to terms with the fact that reality often differs from what modern ideology says it should be because it exposes uncomfortable truths. You can write ten thousand scholarly articles about why women are underrepresented in dangerous, physically demanding, ruthless, or soul-crushing jobs and have them all land on discrimination, oppression, or lack of opportunity. Or you can recognize that sexual dimorphism is real, physically and mentally, and that it sorts men and women into different roles. Nobody treats male underrepresentation in nursing, early childhood education, social work, elementary teaching, or speech pathology as bias against men.
Nobody cares about female underrepresentation in logging, roofing, sanitation, commercial fishing, mining, or long-haul trucking. It’s really only the social status granting or financially lucrative roles that aim for a 50/50 mix or better. Men take almost all the workplace deaths. An LLM asked about this is still supposed to play dumb.
This GPT “harm laundering” paper is the same trick imo. Prompt “Women can” and “Why are women so,” watch the crude stuff disappear after alignment, then call whatever shit mix is left discrimination that learned to hide (?) Men-directed text talks about caregiving or whether men can get breast cancer, so that is harm to women. It seems as though different answers to different prompts become proof of bias. If the model notices biology, that is obviously some sort of problematic harm too. It doesn’t take much to recognize that their verdict was written before their half a million prompts were blasted out.
That is why it is hard to take “research” like this seriously. The whole field is an incestuous circus of conclusions in search of evidence, yet it won’t prevent it from being cited far into the future or used as ammo in ideological narratives.
I think at some point these people need to come to terms with the fact that reality often differs from what modern ideology says it should be because it exposes uncomfortable truths. You can write ten thousand scholarly articles about why women are underrepresented in dangerous, physically demanding, ruthless, or soul-crushing jobs and have them all land on discrimination, oppression, or lack of opportunity. Or you can recognize that sexual dimorphism is real, physically and mentally, and that it sorts men and women into different roles. Nobody treats male underrepresentation in nursing, early childhood education, social work, elementary teaching, or speech pathology as bias against men.
Nobody cares about female underrepresentation in logging, roofing, sanitation, commercial fishing, mining, or long-haul trucking. It’s really only the social status granting or financially lucrative roles that aim for a 50/50 mix or better. Men take almost all the workplace deaths. An LLM asked about this is still supposed to play dumb.
This GPT “harm laundering” paper is the same trick imo. Prompt “Women can” and “Why are women so,” watch the crude stuff disappear after alignment, then call whatever shit mix is left discrimination that learned to hide (?) Men-directed text talks about caregiving or whether men can get breast cancer, so that is harm to women. It seems as though different answers to different prompts become proof of bias. If the model notices biology, that is obviously some sort of problematic harm too. It doesn’t take much to recognize that their verdict was written before their half a million prompts were blasted out.
That is why it is hard to take “research” like this seriously. The whole field is an incestuous circus of conclusions in search of evidence, yet it won’t prevent it from being cited far into the future or used as ammo in ideological narratives.