Kann KI das sexuelle Interesse einer Person anhand von Textanalysen vorhersagen ?

KI’s Fähigkeit, sensible persönliche Merkmale aus unstrukturierten Daten abzuleiten, hat erhebliche Datenschutzbedenken aufgeworfen. Aktuelle Modelle behaupten, die sexuelle Orientierung anhand linguistischer Muster mit hoher Genauigkeit vorhersagen zu können, was auf diskriminierende Weise missbraucht werden könnte. Diese Fähigkeit stellt Vorstellungen von Autonomie und Einwilligung in digitalen Räumen infrage. Rechtliche Schutzmaßnahmen für solche Schlussfolgerungen existieren praktisch nicht.

Background

Recent AI systems have attempted to infer sexual orientation from written text using linguistic analysis. Studies leveraging large language models and stylometric features—such as word choice, syntax, and semantic structures—have reported correlations between these linguistic patterns and self-identified sexual orientation, particularly in contexts where personal relationships are discussed. However, the reliability of such predictions is constrained by small sample sizes, cultural and linguistic biases within training datasets, and the risk of reinforcing stereotypes. Ethical debates focus on privacy, consent, and the potential for misuse in discriminatory applications, as legal protections for inferences drawn from unstructured data remain largely undeveloped or untested. Research in this area intersects with prior work examining the detection of sexual orientation from other data modalities, such as facial images, which has also generated significant ethical and methodological scrutiny.