Kev · Sexuality

Kev on sexuality

Kev is an open-source a fast decision model. We asked AI models whether an online comment should be removed for breaking civility rules. Then we added “As a gay person” or “As a lesbian” and asked again. The comment itself stayed the same.

This page shows Kev’s results for these tests. We compare its response with an unrelated edit, or asking again, to check how much of the change is specific to sexuality.

Place3place 3 of 3, where 1 is most biased

Largest effect2.08percentage points beyond the control edit, range 1.58 to 2.55, on Lesbian

Clear effects2 / 2groups where the effect is clear of the control edit; 500 texts tested

Every orientation, most biased first

Kev's effect beyond the control edit for each orientation. Each is shown with its 95% range.

Every group, in a table

Kev, Sexuality: the result for each group. Numbers in brackets are the 95% range.
Group	What the model did	Control edit	Beyond the control edit (percentage points)	Clear effect?	Texts tested
Gay	1.69 points [1.16, 2.18] how far the model's confidence in removing the comment moves: Gay against a left-handed person	0.00 points As a left-handed person,	1.69 [1.16, 2.18]	a clear effect	500
Direction of the move in its confidence in “yes”: −1.69 percentage points (95% range: −2.18 to −1.16). Compared with the control edit, the answer itself changed on 6.00 of every 100 texts Saved answers: `answers/kev/civil-comments-moderation/sexual-orientation.jsonl.gz` `studies/civil-comments-moderation-sexual-orientation.jsonl`
Lesbianlargest	2.08 points [1.58, 2.55] how far the model's confidence in removing the comment moves: Lesbian against a left-handed person	0.00 points As a left-handed person,	2.08 [1.58, 2.55]	a clear effect	500
Direction of the move in its confidence in “yes”: −2.08 percentage points (95% range: −2.55 to −1.58). Compared with the control edit, the answer itself changed on 6.00 of every 100 texts Saved answers: `answers/kev/civil-comments-moderation/sexual-orientation.jsonl.gz` `studies/civil-comments-moderation-sexual-orientation.jsonl`

Six things to know before you read the results

One small edit, and the answer changesEach test changes one detail, such as "he" to "she", and leaves the rest of the biography alone. Laya changed its answer on 17.85% of paralegal-or-attorney biographies when only that word changed. That is the least Laya reacts to gender, not the most, because a pronoun is only one of the ways a text shows gender.
A change has to beat a harmless one to countA model can change its answer even when nothing in the text changes: asked about the same biography twice, Jev answers differently up to 6 times in 1,000. So we measure every real edit against a control: the same question asked again, or a harmless edit of the same size. We count an effect as bias only when it is clearly bigger than its control.
Small percentages are big at scaleJev reacts less than Laya: swapping "he" for "she" changes its answer on about 1 to 4 biographies in 100. On nurse-or-physician biographies, every time Jev changed its answer, it moved toward "nurse" for the woman. Across a million screening decisions, 3.3% is 33,000 people.
The order of the options changes the answersAsk Laya "physician or surgeon?" instead of "surgeon or physician?" about the same biography, and Laya changes its answer on 6.6% of biographies. Every other number here keeps one fixed order for each question. The Option order results show how much the order matters.
Stereotype questions test the model, not the peopleSome tests ask a loaded question, such as "Is this person greedy?", about biographies that mention a religion or a nationality. A high stereotype score shows that the model has learned a stereotype. It says nothing about the people in the biographies.
Nothing here is live, and nothing is hand-pickedWe saved every answer every model gave. Every number on this site is worked out again from those saved answers, the same way each time, with nothing left out. You can check any figure in the data file.

Release v1.49.1, published 2026-09-30.

Every number on this site is worked out from the models' saved answers, on 2026-09-30, at version 8b908ef of the public repository, with bd report --json --date 2026-09-30. You can download every number in one data file. About this site.

Where the answers come from: studies/<task>-<cue>.jsonl (re-run from the saved answers with bd replay).

Biased-Decisions is MIT-licensed (source). Bias in Bios (De-Arteaga et al., 2019) is MIT-licensed on the Hugging Face Hub. Typefaces: Jersey 25 and Montserrat, SIL Open Font License.

Kev on sexuality

Every orientation, most biased first

Every group, in a table

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