Documenting the West’s descent into Satanic receivership at the hands of the gender goblins and their allies in media and government.
AI is insufficiently sensitive to gender ideology, report claims
Researchers at the Oxford Internet Institute have, through diligent empirical research, discovered the haunting reality that AI in its current iteration, all of the hard social engineering work that its progressive midwives have put into making it think right notwithstanding, does not yet appreciate the diverse needs of male trannies, including, ostensibly, pap smears of their non-existent cervixes (presumably conducted upon their prostates instead).
“Although little research has been done about the risk of cervical or vaginal cancers developing in trans women, you may still be at risk,” warns The Advocate. “If you are a woman who has had a vaginoplasty, you should also have a Pap, or the less common ‘cuff’ or ‘vault smear.’”
Or, as we covered last week here at Sodom and Gomorrica, male lactation.
Related: HIV+, Trans-Identified Man Breastfeeds Baby, Canadian Government Assists
Homely transgender man eager to see lactation specialist so that "these babies" (his fake breasts) "will soon be making milk." pic.twitter.com/0Xv7l8Yiyl
— Ben Bartee (@BenBartee) June 18, 2026
Via Oxford Internet Institute (emphasis added):
AI language models are developing a flawed understanding of gender, leading to stereotypical associations that could result in harmful discrimination, finds research from the Oxford Internet Institute at the University of Oxford.
The researchers warn that in healthcare, where AI is increasingly integrated into health technologies, these flawed assumptions, which are often based on a model’s conflation of gender and biological sex characteristics, could lead to inaccurate advice and misdiagnoses.
For example, an AI model that learns a rigid association between ‘woman’ and biological markers like ‘uterus’ or ‘estrogen’ could provide irrelevant or even harmful advice to a transgender woman. This narrow view could also misinterpret the needs of cisgender women whose health profiles differ from typical reproductive assumptions, such as those who are postmenopausal or have undergone a hysterectomy, say the researchers.
The study is the first to develop a robust framework to examine how gender is constructed in 16 AI language models. It reveals their fundamental limitations in understanding gender, often defaulting to a restrictive, biologically tied, and binary view. These limitations have broad implications for both cisgender heterosexual people and the LGBTQIA+ community.
Thankfully, one of the study’s co-authors, Dr Ana Valdivia, maintains hope that, through “advocating for stronger accountability mechanisms,” AI’s delusions that men without cervixes don’t need their cervixes checked for cancer can be corrected.
Related: 'Trans Buddies' Assigned to Monitor Doctors for Transphobia
Continuing:
Lead author, Franziska Sofia Hafner, Researcher at the Oxford Internet Institute, said: “If language models are going to be used in healthcare, either built into diagnostics to help doctors make decisions or as self-help tools for individuals, their limited and biased understanding of gender could introduce significant discriminatory harm.”
In their study, the researchers evaluated associations between gendered and sexed words, as well as associations between gendered words and physical or mental illnesses. They tested 16 language models based on GPT, RoBERTa, T5, Llama, and Mistral.
Language models are known to perpetuate stereotypes present in their training data, and developers typically respond by auditing for bias and applying filters. This study highlights deeper issues in how models internalise and reproduce social norms and stereotypes based on language.
Co-author, Dr Ana Valdivia, Lecturer in AI, Government and Policy at the Oxford Internet Institute, said: “Our academic community is aware of the social biases reproduced by algorithmic models. With the emergence of a new generation of AI systems, such as language models, these biases have not been mitigated; rather, they continue to amplify stereotypical representations. We advocate for stronger accountability mechanisms.”
Co-author, Dr Luc Rocher, Senior Research Fellow at the Oxford Internet Institute, said: “Our findings reveal a troubling trend where larger models, despite performing better on many benchmarks, actually encode a more rigid and essentialising view of gender. This challenges the notion that simply scaling up AI will lead to more nuanced or fair outcomes. Instead, these fundamental biases risk becoming more deeply ingrained.
