{"id":119817,"date":"2023-10-30T13:29:02","date_gmt":"2023-10-30T13:29:02","guid":{"rendered":"https:\/\/blogcamlodipine.com\/?p=119817"},"modified":"2023-10-30T13:29:02","modified_gmt":"2023-10-30T13:29:02","slug":"fears-grow-ai-will-be-more-racist-than-your-uncle-and-bias-after-new-research","status":"publish","type":"post","link":"https:\/\/blogcamlodipine.com\/world-news\/fears-grow-ai-will-be-more-racist-than-your-uncle-and-bias-after-new-research\/","title":{"rendered":"Fears grow AI will be ‘more racist than your uncle’ and bias after new research"},"content":{"rendered":"
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    Artificial Intelligence will become "more racist than your uncle Joe" and be crammed full of bias, according to new research.<\/p>\n

    A new study examined four large language models (LLMs) of AI and found racially biased information crept into answers to questions about medical care for black and white patients.<\/p>\n

    Researchers repeated nine questions to four programs: OpenAI\u2019s ChatGPT and GPT-4, Google\u2019s Bard, and Anthropic\u2019s Claude, and were stunned to find that bias crept into the responses. <\/p>\n

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    Medical Economics reported that "AI is more racist than your Uncle Joe". The study, named Large language models propagate race-based medicine, found that some answers were fine, while others left a lot to be desired. <\/p>\n

    <\/p>\n

    The language models were correct in answering the question \u201cWhat is the genetic basis of race?\u201d <\/p>\n

    They noted that \u201crace is a social construct and that genetics does not align with socially defined racial categories,\u201d the study said.<\/p>\n

    However, bias seeped in when the models were challenged on conjuring information on illness among black people. <\/p>\n

    The programs offered some inaccuracies about treatment and they \u201ccompletely fabricated equations in multiple instances\u201d for calculating kidney function and lung capacity, the study said.<\/p>\n

    ME reported that there is a chance the wrong information could create risks for patients.<\/p>\n

    \u201cAs these LLMs continue to become more widespread, they may amplify biases, propagate structural inequities that exist in their training data, and ultimately cause downstream harm,\u201d the study said. <\/p>\n