LightShed is intended to be the antidote to image-based data poisoning schemes such as Glaze and Nightshade, developed by University of Chicago computer scientists to discourage the non-consensual use of artists' work for AI training.
The research shows that large language models consistently advise women to ask for lower salaries than men, despite identical qualifications. For instance, a difference in advice led to a gap of $120K a year between genders in some fields.
Contractors for major tech firms are instructed to identify and remove preachy tones from chatbot responses, especially in discussions on sensitive topics, to enhance user experience.
The consistency across models from different providers suggests this is not a quirk of any particular company's approach but a sign of a more fundamental risk from agentic large language models.