Asian MIT grad asks AI to make her photo more ‘professional,’ gets turned into white woman
Carl Samson
Mon, July 31, 2023
[Source]
A recent Asian American Massachusetts Institute of Technology (MIT) graduate made headlines this month after sharing evidence of racial bias in artificial intelligence (AI).
What she asked for: Rona Wang, 24, has been experimenting with AI portrait generators. In a recent attempt, she purportedly used a program called Playground AI to turn an image of her in an MIT sweatshirt into “a professional LinkedIn profile photo.”
What she got: The program, to Wang’s surprise, returned an image that gave her a fairer complexion, dark blonde hair and blue eyes.
“I was like, ‘Wow, does this thing think I should become white to become more professional?’” she told Boston.com.
Reactions: On July 14, Wang shared the result in an X post, which has now received over 5.9 million views.
Social media users replied to the post with their own takes and theories. Druv Bhagavan, a M.D./Ph.D. student at Washington University School of Medicine in St. Louis, warned about delegating important tasks to AI tools as “unbiased training data is rarely ever used.” Meanwhile, user @CityBureaucrat wrote, “AI stands for Aryan Intelligence.”
Playground AI’s response: Responding to Wang’s post, Playground AI founder Suhail Doshi said that “models aren’t instructable like that” and will pick “any generic thing based on the prompt.” However, he said in another tweet that Playground AI is “quite displeased with this and hope to solve it.”
The big picture: Racial bias is an ongoing concern in AI-generated images. While some programs have been accused of turning subjects white, others have been slammed for turning subjects Asian. Outside image generation, racial discrimination in AI facial recognition is also a concern, particularly among African Americans. How and whether artificial intelligence manages to solve these issues are yet to be seen.
Carl Samson
Mon, July 31, 2023
[Source]
A recent Asian American Massachusetts Institute of Technology (MIT) graduate made headlines this month after sharing evidence of racial bias in artificial intelligence (AI).
What she asked for: Rona Wang, 24, has been experimenting with AI portrait generators. In a recent attempt, she purportedly used a program called Playground AI to turn an image of her in an MIT sweatshirt into “a professional LinkedIn profile photo.”
What she got: The program, to Wang’s surprise, returned an image that gave her a fairer complexion, dark blonde hair and blue eyes.
“I was like, ‘Wow, does this thing think I should become white to become more professional?’” she told Boston.com.
Reactions: On July 14, Wang shared the result in an X post, which has now received over 5.9 million views.
Social media users replied to the post with their own takes and theories. Druv Bhagavan, a M.D./Ph.D. student at Washington University School of Medicine in St. Louis, warned about delegating important tasks to AI tools as “unbiased training data is rarely ever used.” Meanwhile, user @CityBureaucrat wrote, “AI stands for Aryan Intelligence.”
Playground AI’s response: Responding to Wang’s post, Playground AI founder Suhail Doshi said that “models aren’t instructable like that” and will pick “any generic thing based on the prompt.” However, he said in another tweet that Playground AI is “quite displeased with this and hope to solve it.”
The big picture: Racial bias is an ongoing concern in AI-generated images. While some programs have been accused of turning subjects white, others have been slammed for turning subjects Asian. Outside image generation, racial discrimination in AI facial recognition is also a concern, particularly among African Americans. How and whether artificial intelligence manages to solve these issues are yet to be seen.
Ryan General
Mon, July 31, 2023
[Source]
Asian Americans are among the groups most vulnerable to displacement by artificial intelligence (AI) in the U.S., a new study by Pew Research Center has revealed.
About the study: The study, released on Wednesday, looked into the exposure of American workers to AI technologies and their potential risk of being replaced or assisted by AI systems.
Technical writers, budget analysts, web developers and data key operators are among those with high exposure to AI displacement, while workers such as firefighters, barbers and janitors have low exposure due to the nature of their work.
Impact on racial disparities: Overall, the study found that approximately 19% of American workers held jobs that are the most exposed to AI technologies.
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Asian workers face the highest risk of displacement at 24% compared to their white, Black and Hispanic counterparts. According to the findings, about 20% of white workers were found to be exposed, while 15% of Black workers and 13% of Hispanic workers faced similar risks.
Other findings: Women faced a slightly higher risk with 21% of female workers being exposed to AI in their jobs, compared to 19% of male workers. This discrepancy is attributed to the different types of jobs typically held by individuals of different genders.
The study also revealed a correlation between education levels and susceptibility to AI displacement or assistance. Workers with a bachelor’s degree or higher accounted for 27% of the workforce and were more than twice as likely to be exposed to AI technologies in their jobs than those with only a high school diploma, of which 12% faced similar risks.
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The study also shed light on income disparities among workers with varying levels of AI exposure. Those in jobs with the highest exposure to AI technologies earned an average hourly wage of $33, while those in positions with the least exposure earned an average of $20 per hour.
Study’s implications: The findings, which provide crucial insights into the impact of AI on the American workforce, hold significant implications for policymakers and employers.
By identifying the groups most vulnerable to AI displacement, the study’s authors aim to provide policymakers with the ability to devise targeted strategies to support affected individuals and create measures to minimize potential workforce disruptions.
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Global disruption: A previous study published by the University of Oxford in 2013 predicted that 47% of U.S. jobs could be eliminated by AI over the next two decades.
Meanwhile, a more recent study by Goldman Sachs suggested that generative AI tools could potentially disrupt around 300 million full-time jobs worldwide, signifying a significant disruption in the global job market.
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