{"id":168003,"date":"2023-12-18T02:38:54","date_gmt":"2023-12-18T07:38:54","guid":{"rendered":"https:\/\/www.immortalitymedicine.tv\/artificial-intelligence-in-natural-hazard-modeling-severe-storms-hurricanes-floods-and-wildfires-government-accountability-office\/"},"modified":"2024-08-18T12:47:03","modified_gmt":"2024-08-18T16:47:03","slug":"artificial-intelligence-in-natural-hazard-modeling-severe-storms-hurricanes-floods-and-wildfires-government-accountability-office","status":"publish","type":"post","link":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/artificial-intelligence\/artificial-intelligence-in-natural-hazard-modeling-severe-storms-hurricanes-floods-and-wildfires-government-accountability-office.php","title":{"rendered":"Artificial Intelligence in Natural Hazard Modeling: Severe Storms, Hurricanes, Floods, and Wildfires &#8211; Government Accountability Office"},"content":{"rendered":"<p><p>What GAO Found    <\/p>\n<p>    GAO found that machine learning, a type of artificial    intelligence (AI) that uses algorithms to identify patterns in    information, is being applied to forecasting models for natural    hazards such as severe storms, hurricanes, floods, and    wildfires, which can lead to natural disasters. A few machine    learning models are used operationallyin routine    forecastingsuch as one that may improve the warning time for    severe storms. Some uses of machine learning are considered    close to operational, while others require years of development    and testing.  <\/p>\n<p>    GAO identified potential benefits of applying machine learning    to this field, including:  <\/p>\n<p>    Forecasting natural disasters using machine    learning  <\/p>\n<\/p>\n<p>    GAO also identified challenges to the use of machine learning.    For example:  <\/p>\n<p>    GAO identified five policy options that could help address    these challenges. These options are intended to inform    policymakers, including Congress, federal and state agencies,    academic and research institutions, and industry of potential    policy implementations. The status quo option illustrates a    scenario in which government policymakers take no additional    actions beyond current ongoing efforts.  <\/p>\n<p>    Policy Options to Help Address Challenges to the Use of    Machine Learning in Natural Hazard Modeling  <\/p>\n<p>            Government policymakers could expand use of existing            observational data and infrastructure to close gaps,            expand access to certain data, and (in conjunction with            other policymakers) establish guidelines for making            data AI-ready.          <\/p>\n<p>            Government policymakers could update education            requirements to include machine learning-related            coursework and expand learning and support centers,            while academic policymakers could adjust physical            science curricula to include more machine learning            coursework.          <\/p>\n<p>            Government policymakers could address pay scale            limitations for positions that include machine learning            expertise and work with private sector policymakers to            expand the use of public-private partnerships (PPP).          <\/p>\n<p>            Policymakers could establish efforts to better            understand and mitigate various forms of bias, support            inclusion of diverse stakeholders for machine learning            models, and develop guidelines or best practices for            reporting methodological choices.          <\/p>\n<p>            Government policymakers could maintain existing policy            efforts and organizational structures, along with            existing strategic plans and agency commitments.          <\/p>\n<p>    Source: GAO. | GAO-24-106213  <\/p>\n<p>    Natural disasters cause on average hundreds of deaths and    billions of dollars in damage in the U.S. each year.    Forecasting natural disasters relies on computer modeling and    is important for preparedness and response, which can in turn    save lives and protect property. AI is a powerful tool that can    automate processes, rapidly analyze massive data sets, enable    modelers to gain new insights, and boost efficiency.  <\/p>\n<p>    This report on the use of machine learning in natural hazard    modeling discusses (1) the emerging and current use of machine    learning for modeling severe storms, hurricanes, floods, and    wildfires, and the potential benefits of this use; (2)    challenges surrounding the use of machine learning; and (3)    policy options to address challenges or enhance benefits of the    use of machine learning.  <\/p>\n<p>    GAO reviewed the use of machine learning to model severe    storms, hurricanes, floods, and wildfires across development    and operational stages; interviewed a range of stakeholder    groups, including government, industry, academia, and    professional organizations; convened a meeting of experts in    conjunction with the National Academies; and reviewed key    reports and scientific literature. GAO is identifying policy    options in this report.  <\/p>\n<p>    For more information, contact Brian Bothwell at (202) 512-6888    or <a href=\"mailto:bothwellb@gao.gov\">bothwellb@gao.gov<\/a>.  <\/p>\n<p><!-- Auto Generated --><\/p>\n<p>See the article here:<\/p>\n<p><a target=\"_blank\" rel=\"nofollow noopener\" href=\"https:\/\/www.gao.gov\/products\/gao-24-106213\" title=\"Artificial Intelligence in Natural Hazard Modeling: Severe Storms, Hurricanes, Floods, and Wildfires - Government Accountability Office\">Artificial Intelligence in Natural Hazard Modeling: Severe Storms, Hurricanes, Floods, and Wildfires - Government Accountability Office<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p> What GAO Found GAO found that machine learning, a type of artificial intelligence (AI) that uses algorithms to identify patterns in information, is being applied to forecasting models for natural hazards such as severe storms, hurricanes, floods, and wildfires, which can lead to natural disasters.  <a href=\"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/artificial-intelligence\/artificial-intelligence-in-natural-hazard-modeling-severe-storms-hurricanes-floods-and-wildfires-government-accountability-office.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":[13],"tags":[],"class_list":["post-168003","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence"],"modified_by":null,"_links":{"self":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/168003"}],"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=168003"}],"version-history":[{"count":0,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/168003\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/media?parent=168003"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/categories?post=168003"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/tags?post=168003"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}