Record summary
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Risk profile
How this risk is described and categorized.
"CAs can perpetuate harmful stereotypes by using particular identity markers in language (e.g. referring to “self” as “female”), or by more general design features (e.g. by giving the product a gendered name such as Alexa). The risk of representational harm in these cases is that the role of “assistant” is presented as inherently linked to the female gender [19, 36]. Gender or ethnicity identity markers may be implied by CA vocabulary, knowledge or vernacular [124]; product description, e.g. in one case where users could choose as virtual assistant Jake - White, Darnell - Black, Antonio - Hispanic [117]; or the CA’s explicit self-description during dialogue with the user."
Suggested mitigations
Defenses that may help with related attacks.
Source
Research source for this risk, when available.
Included resource
Taxonomy of Risks posed by Language Models
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.