{"id":1027280,"date":"2023-08-04T10:44:19","date_gmt":"2023-08-04T14:44:19","guid":{"rendered":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/uncategorized\/growing-concerns-over-bias-in-powerful-ai-and-machine-learning-fagen-wasanni.php"},"modified":"2023-08-04T10:44:19","modified_gmt":"2023-08-04T14:44:19","slug":"growing-concerns-over-bias-in-powerful-ai-and-machine-learning-fagen-wasanni","status":"publish","type":"post","link":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/machine-learning\/growing-concerns-over-bias-in-powerful-ai-and-machine-learning-fagen-wasanni.php","title":{"rendered":"Growing Concerns Over Bias in Powerful AI and Machine Learning &#8230; &#8211; Fagen wasanni"},"content":{"rendered":"<p><p>    The rise of powerful artificial intelligence (AI) and machine    learning (ML) tools has sparked concern about the presence of    bias in these technologies. Sam Altman, CEO of OpenAI,    acknowledges that there will never be a universally unbiased    version of AI. As these tools become more prevalent across    industries, bias has become a critical topic for lawmakers.    Some countries, like France, have even banned the use of AI    tools in certain sectors to prevent the commercialization of    tools that predict judicial decision-making patterns.  <\/p>\n<p>    One major concern with AI tools is the potential for biases to    undermine the neutrality of the legal system. The use of    predictive analysis tools that process vast amounts of data can    produce unsettlingly accurate results. This raises questions    about justice when an AI tool predicts guilt or innocence based    on the judge or magistrate handling the case, rendering    individual guilt irrelevant.  <\/p>\n<p>    The issue of bias extends beyond the legal system. Industries    such as healthcare and finance are increasingly embracing AI    technology. Pfizer, for example, experimented with IBM Watson    to accelerate drug discovery efforts in oncology. While IBM    Watson fell short of expectations, the emergence of more    powerful AI tools has renewed excitement in the industry.    However, biases introduced during the data collection and    algorithm development processes can lead to inequitable    outcomes in patient treatment or financial decision-making.  <\/p>\n<p>    Biases can enter datasets through factors like sampling bias,    confirmation bias, and historical bias. To address bias, Altman    highlights the importance of representative and diverse    datasets. The quality of data directly affects the potential    for bias in AI models.  <\/p>\n<p>    The responsibility for addressing bias falls on policymakers as    AI continues to impact society and individual lives. The    proliferation of AI systems holds a mirror to society,    revealing uncomfortable truths that might necessitate ethical    guidelines and frameworks to ensure fairness and accountability    in the use of AI technology.  <\/p>\n<p><!-- Auto Generated --><\/p>\n<p>More here: <\/p>\n<p><a target=\"_blank\" rel=\"nofollow noopener\" href=\"https:\/\/fagenwasanni.com\/news\/growing-concerns-over-bias-in-powerful-ai-and-machine-learning-tools\/106719\" title=\"Growing Concerns Over Bias in Powerful AI and Machine Learning ... - Fagen wasanni\">Growing Concerns Over Bias in Powerful AI and Machine Learning ... - Fagen wasanni<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p> The rise of powerful artificial intelligence (AI) and machine learning (ML) tools has sparked concern about the presence of bias in these technologies. Sam Altman, CEO of OpenAI, acknowledges that there will never be a universally unbiased version of AI. As these tools become more prevalent across industries, bias has become a critical topic for lawmakers.  <a href=\"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/machine-learning\/growing-concerns-over-bias-in-powerful-ai-and-machine-learning-fagen-wasanni.php\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"limit_modified_date":"","last_modified_date":"","_lmt_disableupdate":"","_lmt_disable":"","footnotes":""},"categories":[1231415],"tags":[],"class_list":["post-1027280","post","type-post","status-publish","format-standard","hentry","category-machine-learning"],"modified_by":null,"_links":{"self":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/1027280"}],"collection":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/comments?post=1027280"}],"version-history":[{"count":0,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/1027280\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/media?parent=1027280"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/categories?post=1027280"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/tags?post=1027280"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}