Google has apologized for what it describes as “inaccuracies in some historical image generation depictions” with its Gemini AI tool, saying its attempts at creating a “wide range” of results missed the mark.
The statement follows criticism that it depicted specific white figures (like the US Founding Fathers) or groups like Nazi-era German soldiers as people of color, possibly as an overcorrection to long-standing racial bias problems in AI.
Over the past few days, however, social media posts have questioned whether it fails to produce historically accurate results in an attempt at racial and gender diversity.
The criticism was taken up by right-wing accounts that requested images of historical groups or figures like the Founding Fathers and purportedly got overwhelmingly non-white AI-generated people as results.
Image generators are trained on large corpuses of pictures and written captions to produce the “best” fit for a given prompt, which means they’re often prone to amplifying stereotypes.
“The stupid move here is Gemini isn’t doing it in a nuanced way.” And while entirely white-dominated results for something like “a 1943 German soldier” would make historical sense, that’s much less true for prompts like “an American woman,” where the question is how to represent a diverse real-life group in a small batch of made-up portraits.
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Google has apologized for what it describes as “inaccuracies in some historical image generation depictions” with its Gemini AI tool, saying its attempts at creating a “wide range” of results missed the mark.
The statement follows criticism that it depicted specific white figures (like the US Founding Fathers) or groups like Nazi-era German soldiers as people of color, possibly as an overcorrection to long-standing racial bias problems in AI.
Over the past few days, however, social media posts have questioned whether it fails to produce historically accurate results in an attempt at racial and gender diversity.
The criticism was taken up by right-wing accounts that requested images of historical groups or figures like the Founding Fathers and purportedly got overwhelmingly non-white AI-generated people as results.
Image generators are trained on large corpuses of pictures and written captions to produce the “best” fit for a given prompt, which means they’re often prone to amplifying stereotypes.
“The stupid move here is Gemini isn’t doing it in a nuanced way.” And while entirely white-dominated results for something like “a 1943 German soldier” would make historical sense, that’s much less true for prompts like “an American woman,” where the question is how to represent a diverse real-life group in a small batch of made-up portraits.
The original article contains 766 words, the summary contains 211 words. Saved 72%. I’m a bot and I’m open source!