{"id":481,"date":"2024-10-12T00:29:56","date_gmt":"2024-10-12T00:29:56","guid":{"rendered":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/?post_type=chapter&#038;p=481"},"modified":"2024-10-21T05:58:16","modified_gmt":"2024-10-21T05:58:16","slug":"14-0","status":"publish","type":"chapter","link":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/chapter\/14-0\/","title":{"rendered":"14.0 Learning Objectives and Overview"},"content":{"raw":"<div class=\"textbox textbox--learning-objectives\"><header class=\"textbox__header\">\r\n<p class=\"textbox__title\">Learning Objectives<\/p>\r\n\r\n<\/header>\r\n<div class=\"textbox__content\">\r\n<ol>\r\n \t<li>Define the key concepts of Generative AI (GenAI) and its application in project management.<\/li>\r\n \t<li>Explain how GenAI models such as Large Language Models (LLMs), Transformer-based models, and Autoregressive models function in generating new data.<\/li>\r\n \t<li>Demonstrate how to effectively use GenAI tools to automate routine tasks, enhance decision-making, and provide real-time project insights.<\/li>\r\n \t<li>Identify potential challenges, such as data privacy concerns and AI hallucinations, and assess GenAI\u2019s impact on project workflows.<\/li>\r\n \t<li>Critically evaluate the ethical considerations and limitations of using GenAI in project management, including bias in AI-generated outputs.<\/li>\r\n \t<li>Develop strategies for integrating GenAI into project management workflows, including prompt engineering techniques, to improve efficiency and project outcomes.<\/li>\r\n<\/ol>\r\n<\/div>\r\n<\/div>\r\n<h2>Overview<\/h2>\r\n<div class=\"flex max-w-full flex-col flex-grow\">\r\n<div data-message-author-role=\"assistant\" data-message-id=\"62fc83f5-5e70-4854-a531-9b69f2176c86\" dir=\"auto\" class=\"min-h-8 text-message flex w-full flex-col items-end gap-2 whitespace-normal break-words [.text-message+&amp;]:mt-5\" data-message-model-slug=\"gpt-4o\">\r\n<div class=\"flex w-full flex-col gap-1 empty:hidden first:pt-[3px]\">\r\n<div class=\"markdown prose w-full break-words dark:prose-invert light\">\r\n\r\nThe introduction of GenAI in November 2022 by OpenAI has revolutionized the field of project management, transforming how tasks are automated, decisions are made, and data is processed. With the release of tools like ChatGPT, GenAI models have demonstrated remarkable advancements in natural language processing, enabling project managers to optimize workflows and make data-driven decisions. As businesses increasingly adopt AI technologies, project managers must understand the opportunities and challenges posed by GenAI, such as potential biases in AI outputs and the need for effective data governance. This chapter will explore the benefits of using GenAI, including improved efficiency, enhanced decision-making, real-time project insights, and strategies to mitigate challenges like AI hallucinations and over-reliance on automation.\r\n\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/div>","rendered":"<div class=\"textbox textbox--learning-objectives\">\n<header class=\"textbox__header\">\n<p class=\"textbox__title\">Learning Objectives<\/p>\n<\/header>\n<div class=\"textbox__content\">\n<ol>\n<li>Define the key concepts of Generative AI (GenAI) and its application in project management.<\/li>\n<li>Explain how GenAI models such as Large Language Models (LLMs), Transformer-based models, and Autoregressive models function in generating new data.<\/li>\n<li>Demonstrate how to effectively use GenAI tools to automate routine tasks, enhance decision-making, and provide real-time project insights.<\/li>\n<li>Identify potential challenges, such as data privacy concerns and AI hallucinations, and assess GenAI\u2019s impact on project workflows.<\/li>\n<li>Critically evaluate the ethical considerations and limitations of using GenAI in project management, including bias in AI-generated outputs.<\/li>\n<li>Develop strategies for integrating GenAI into project management workflows, including prompt engineering techniques, to improve efficiency and project outcomes.<\/li>\n<\/ol>\n<\/div>\n<\/div>\n<h2>Overview<\/h2>\n<div class=\"flex max-w-full flex-col flex-grow\">\n<div data-message-author-role=\"assistant\" data-message-id=\"62fc83f5-5e70-4854-a531-9b69f2176c86\" dir=\"auto\" class=\"min-h-8 text-message flex w-full flex-col items-end gap-2 whitespace-normal break-words [.text-message+&amp;]:mt-5\" data-message-model-slug=\"gpt-4o\">\n<div class=\"flex w-full flex-col gap-1 empty:hidden first:pt-[3px]\">\n<div class=\"markdown prose w-full break-words dark:prose-invert light\">\n<p>The introduction of GenAI in November 2022 by OpenAI has revolutionized the field of project management, transforming how tasks are automated, decisions are made, and data is processed. With the release of tools like ChatGPT, GenAI models have demonstrated remarkable advancements in natural language processing, enabling project managers to optimize workflows and make data-driven decisions. As businesses increasingly adopt AI technologies, project managers must understand the opportunities and challenges posed by GenAI, such as potential biases in AI outputs and the need for effective data governance. This chapter will explore the benefits of using GenAI, including improved efficiency, enhanced decision-making, real-time project insights, and strategies to mitigate challenges like AI hallucinations and over-reliance on automation.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"author":256,"menu_order":1,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-481","chapter","type-chapter","status-publish","hentry"],"part":478,"_links":{"self":[{"href":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/wp-json\/pressbooks\/v2\/chapters\/481","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/wp-json\/wp\/v2\/users\/256"}],"version-history":[{"count":4,"href":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/wp-json\/pressbooks\/v2\/chapters\/481\/revisions"}],"predecessor-version":[{"id":564,"href":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/wp-json\/pressbooks\/v2\/chapters\/481\/revisions\/564"}],"part":[{"href":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/wp-json\/pressbooks\/v2\/parts\/478"}],"metadata":[{"href":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/wp-json\/pressbooks\/v2\/chapters\/481\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/wp-json\/wp\/v2\/media?parent=481"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/wp-json\/pressbooks\/v2\/chapter-type?post=481"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/wp-json\/wp\/v2\/contributor?post=481"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/pressbooks.ulib.csuohio.edu\/projectmanagement2ndedition\/wp-json\/wp\/v2\/license?post=481"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}