{"id":34003,"date":"2022-11-15T12:25:37","date_gmt":"2022-11-15T12:25:37","guid":{"rendered":"https:\/\/digileaders.com\/?p=34003"},"modified":"2022-11-17T13:06:30","modified_gmt":"2022-11-17T13:06:30","slug":"how-the-feminization-of-ai-enforces-gender-stereotypes","status":"publish","type":"post","link":"https:\/\/digileaders.com\/how-the-feminization-of-ai-enforces-gender-stereotypes\/","title":{"rendered":"How the feminization of AI enforces gender stereotypes"},"content":{"rendered":"

If there\u2019s one element that seems to follow artificial intelligence (AI) wherever it goes, it\u2019s femininity. The <\/span>feminization of AI can be seen in pop culture<\/span><\/a>, science fiction tropes, voice assistants, chatbots, and robots \u2014 more often than we may realize.\u00a0<\/span><\/p>\n

Take a step back and ask yourself, \u201cHow often do I see masculine or genderless representation in AI versus feminine expression?\u201d<\/span><\/p>\n

As beneficial as feminization can be, it still raises some serious concerns for programmers, AI professionals, and people. This article will offer tips on how we can address the feminization of AI. But first, let\u2019s look at where this issue stems from.\u00a0<\/span><\/p>\n

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Where the feminization of AI stems from\u00a0<\/span><\/h3>\n

First, AI is a product of the people that program it. These systems are dependent on the data that\u2019s fed to them.\u00a0<\/span><\/p>\n

Biases in programming can be purposeful or accidental due to unconscious, preconceived notions. For example, say a programmer has a gender bias centered around women being in more service-oriented roles rather than in physical, traditionally male positions, like a farmer, landscaper, or plumber. These \u201cmasculine\u201d <\/span>jobs are less likely to be replaced by AI<\/span><\/a>.\u00a0<\/span><\/p>\n

More traditionally feminine roles, like secretaries, customer reps, or cleaners, are more likely to be filled by AI.\u00a0 In that case, the programmer will be more inclined to attribute feminine qualities to a service-oriented role for an AI tool, like a chatbot or voice assistant. Consciously or unconsciously, they don\u2019t picture men in these positions.<\/span><\/p>\n

Trying to get people not to be afraid of AI is hard enough. Femininity also helps in this respect because women are unfortunately considered more \u201chuman\u201d than men. They\u2019re more likely to be viewed as comforting, caring, and warm. Those characteristics are crucial in curbing fear in people. Although this is helpful for AI adoption, it\u2019s furthering the feminization of AI.<\/span><\/p>\n

The impact of gendering AI technologies can be dangerous because much of what\u2019s \u201cfeminine\u201d in these tools is based on harmful gender stereotypes. Therefore, we must address the feminization of AI to uproot its destructive aspects and reinforce the ones that enhance AI.<\/span><\/p>\n

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How to address the feminization of AI\u00a0<\/span><\/h3>\n

Now that we\u2019re a bit more familiar with where the feminization of AI stems from, let\u2019s look at how we can address it so that it can be beneficial rather than harmful.\u00a0<\/span><\/p>\n

Think more deeply about how we view gender\u00a0<\/strong><\/p>\n

Addressing the feminization of AI starts with a deeper understanding of how we view gender and the roles associated with gender. Do some research and ask yourself:\u00a0<\/span><\/p>\n

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