A starting point for discussion
The idea
For a robustness check, the researchers made Brazilian Portuguese prompts describing participant characteristics. The features included age (young or older/“third age”), political ideology (conservative, centrist, or left-wing), urban or rural zone, education (with or without higher education), sex (male or female), and city and state. One example described a 26-year-old liberal man with a master’s degree in Rio de Janeiro choosing a proposal to curb tax evasion over one to expand privatization of state-owned companies and infrastructure concessions.
Place in the reasoning
AI assessment · Connected to reasoning
Describes participant details and a policy choice in a Portuguese prompt robustness check. This is context for how a person is represented using limited personal information; the passage reports no result from the check and does not establish accountable representation.
Different prediction checks reveal different limits
The prompt example specifies inputs used in a robustness check of prediction; it is methodological context, not evidence that predictions were accurate or robust.
Good overall predictions can hide worse results for some groups
The listed demographic categories show which participant characteristics the prompt included in this check, without establishing that these categories capture all relevant differences or that groups were represented equally.
Matching views does not make AI representation accountable
The example makes concrete how limited participant details and a recorded policy choice were used to represent an individual in a prompt. It reports no check result and does not establish accountable representation.
What this means and why it matters
What this means
The researchers adapted their prompt format to Brazilian Portuguese and included participant characteristics and a choice between two proposals. The listed age categories were young and older, described as “third age.”
Why it matters
The passage documents the prompt design, but does not show whether predictions were robust across languages.
Conditions & assumptions
Source coverage: Full readable text of the retrieved 37-page research draft shared before formal publication, including references and appendices. Figures are not independently interpreted. Passages 41–42 describe the Portuguese prompts, list their demographic features and values, and give an example pairing participant details with two policy proposals. They do not report whether this adaptation improved predictions. Addresses: Portuguese prompt design