There are problems with so called "even-handedness", particularly when sharing empirical data which can be interpreted as politically aligned. If I query a lar

There are problems with so called "even-handedness", particularly when sharing empirical data which can be interpreted as politically aligned. If I query a large language model (LLM) requesting data regarding global atmospheric carbon dioxide (CO2) levels and its impact on climate, I don't believe it appropriate for 50% of the response be dedicated to the point of view proffered by 5% of climate scientists. I would instead prefer to receive details on the political alignment of the foundations and corporations funding those 5%. So called "even-handedness" often becomes "false equivalence", where an ordinarily untenable belief unbacked by reality is reified for political ends.