{"id":39160,"date":"2023-11-20T13:56:21","date_gmt":"2023-11-20T18:56:21","guid":{"rendered":"https:\/\/ourpublicservice.org\/?p=39160"},"modified":"2023-11-21T10:27:55","modified_gmt":"2023-11-21T15:27:55","slug":"preparing-for-a-future-with-ai","status":"publish","type":"post","link":"https:\/\/ourpublicservice.org\/blog\/preparing-for-a-future-with-ai\/","title":{"rendered":"Preparing for a future with artificial intelligence: The critical role of enterprise risk managers"},"content":{"rendered":"\n<p>On Sept. 26, in anticipation of President Biden\u2019s executive order on <a href=\"https:\/\/www.whitehouse.gov\/briefing-room\/presidential-actions\/2023\/10\/30\/executive-order-on-the-safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence\/\" target=\"_blank\" rel=\"noreferrer noopener\">the use of artificial intelligence<\/a> in government, the Partnership for Public Service and Deloitte held a virtual working session that examined how agencies can use enterprise risk management, or ERM, to safely and securely harness AI to work more effectively.&nbsp;&nbsp;&nbsp;<\/p>\n\n\n\n<p>The session featured panelists Taka Ariga, chief data scientist and director of the Innovation Lab at the Government Accountability Office, and Wayne Taylor, senior risk advisor at the IRS, with moderation by Deloitte &amp; Touche LLP Managing Directors Cynthia Vitters and John Basso.&nbsp;&nbsp;<\/p>\n\n\n\n<p>The discussion highlighted several frameworks that risk managers could consult to drive the responsible use of AI at their agencies. These frameworks touched on a range of issues, from balancing AI risk and opportunity to capturing and monitoring risks to fostering collaboration between technologists, humanists and others to form a dynamic AI risk team.&nbsp;&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-frameworks-for-ai-risk-management\"><strong>Frameworks for AI risk management<\/strong>&nbsp;<\/h3>\n\n\n\n<p>While AI has the potential to make government work more efficiently, implementing this new technology comes with a unique set of risks\u2014risks that will continue to grow as AI matures and evolves.&nbsp;&nbsp;<\/p>\n\n\n\n<p>The Government Accountability Office and the National Institute of Standards and Technology have released frameworks to serve as a foundation for responsible AI adoption and risk management.&nbsp;&nbsp;<\/p>\n\n\n\n<p>Published in 2021, GAO\u2019s <a href=\"https:\/\/www.gao.gov\/products\/gao-21-519sp\" target=\"_blank\" rel=\"noreferrer noopener\">AI Accountability Framework<\/a> outlines four key principles\u2014governance, data, performance and monitoring\u2014for the application and responsible implementation of AI systems.&nbsp;&nbsp;<\/p>\n\n\n\n<p><em>\u201c<\/em>This framework and ERM principles are complementary<em>,\u201d<\/em> Ariga noted, emphasizing that many practices in the GAO framework\u2014such as appropriate governance structures\u2014are already familiar to ERM practitioners.&nbsp;&nbsp;<\/p>\n\n\n\n<p>The NIST <a href=\"https:\/\/airc.nist.gov\/AI_RMF_Knowledge_Base\/AI_RMF\" target=\"_blank\" rel=\"noreferrer noopener\">AI Risk Management Framework<\/a> outlines four core functions\u2014govern, map, measure and manage\u2014of AI risk management that agencies may apply to their particular risk contexts.&nbsp;&nbsp;<\/p>\n\n\n\n<p>Taylor shared how the IRS has used NIST\u2019s framework and <a href=\"https:\/\/airc.nist.gov\/AI_RMF_Knowledge_Base\/AI_RMF\/Foundational_Information\/3-sec-characteristics\" target=\"_blank\" rel=\"noreferrer noopener\">guidance on trustworthy AI principles<\/a> to identify the types of AI risk that relate most to the agency\u2019s operations and mission. The IRS is now thinking about how to operationalize NIST\u2019s four core functions, building on the agency\u2019s existing risk management processes.&nbsp;&nbsp;<\/p>\n\n\n\n<p>\u201cI realized it\u2019s not entirely different from what we\u2019re already doing today,\u201d Taylor said of the NIST framework. \u201cIt just needed to be augmented for AI.\u201d&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Takeaways on AI risk management<\/strong>&nbsp;<\/h3>\n\n\n\n<p>How might the federal risk management community put these principles into practice? Our session offered three key recommendations:&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Get started.<\/strong> It\u2019s understandable, given the complex and rapidly evolving nature of AI, to want a more detailed roadmap for how to approach AI risk management before starting the process. Teams should begin AI risk management efforts using current resources and knowledge (e.g., an enterprise risk register), gauging what works and what needs to be adjusted as more is learned and as technology and regulations evolve. \u201cTrying something is how to get to what good looks like,\u201d Taylor said.&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Emphasize continuous monitoring in AI risk management plans.<\/strong> Active risk management is needed throughout the lifecycle of AI systems, as the performance and risks of the system often shift over time. This contrasts with many other tools that can be transitioned to incident management processes once they are operational. This continuous monitoring may assist in balancing AI risk and opportunity.&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Incorporate a wide variety of stakeholders.<\/strong> According to Ariga, responsibly implementing AI is a \u201cteam sport\u201d that should involve different perspectives from across an agency as well as end users who may be impacted. ERM practitioners are well positioned to facilitate this collaboration, building on their existing programs that collect risk information through both bottom-up and top-down processes. This approach incorporates a wide variety of viewpoints, which are crucial AI risk management.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>On Sept. 26, in anticipation of President Biden\u2019s executive order on the use of artificial intelligence in government, the Partnership for Public Service and Deloitte held a virtual working session that examined how agencies can use enterprise risk management, or ERM, to safely and securely harness AI to work more effectively.&nbsp;&nbsp;&nbsp; The session featured panelists&#8230;<\/p>\n","protected":false},"author":206,"featured_media":39165,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"sort-date":"","content-type":"","om_disable_all_campaigns":false,"_searchwp_excluded":"","footnotes":""},"categories":[7593],"tags":[9088,11938,10272],"class_list":["post-39160","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-innovation-tech","tag-artifical-intelligence","tag-enterprise-risk-management","tag-risk-management"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.2 (Yoast SEO v26.2) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Preparing for a future with AI: The critical role of enterprise risk managers<\/title>\n<meta name=\"description\" content=\"The Partnership for Public Service is a nonprofit, nonpartisan organization that strives for a more effective government for 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