Generative AI: Shaping Work and Tasks
This course is part of Navigating Disruption: Generative AI in the Workplace.
This course examines the evolving impact of generative AI across various professional domains, providing a framework for understanding how artificial intelligence may reshape workplace tasks and job responsibilities. Through focused analysis of specific industries—journalism, education, and marketing—the course explores how different roles within these sectors may be augmented or altered by AI technologies. You'll learn to classify the various ways AI influences workplace tasks, understand its appropriate applications, and evaluate how it might redistribute responsibilities within jobs. The curriculum includes insights from industry experts who share professional perspectives on AI integration, helping you anticipate changes in your own field. Using a practical approach, you'll analyze your own workplace's exposure to AI technologies and develop strategies for adaptation. As the second course in the "Navigating Disruption" specialization, it builds on foundational knowledge to help you conceptualize and prepare for AI's implications in professional settings.
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What you'll learn
Classify the different ways generative AI influences workplace tasks
Evaluate specific job roles for their potential exposure to AI technologies
Analyze how AI affects journalism, education, and marketing differently
Identify which tasks within jobs are most likely to be augmented or altered by AI
Assess your own workplace for potential AI disruption or enhancement
Distinguish between appropriate and inappropriate applications of AI in professional contexts
Skills you'll gain
This course includes:
1.7 Hours PreRecorded video
1 assignment
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Subscription access
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There are 7 modules in this course
This course explores how generative AI is reshaping professional work environments across multiple industries. Structured across seven modules, the curriculum begins by establishing a framework for analyzing AI's impact on workplaces, jobs, and tasks. The core content examines three key industries in depth: journalism, education, and marketing. In each case, industry experts provide insights while the course analyzes how specific roles within these sectors face varying levels of AI exposure. For journalism, the course examines AI's application in investigative reporting, editing, and back-end operations. In education, it explores implications for teaching, curriculum development, and student learning. The marketing section covers market research, graphic design, and messaging campaigns. Later modules guide students through analyzing their own workplace's AI exposure and understanding appropriate applications in different contexts. The course concludes by examining economic implications and synthesizing knowledge about how AI reshapes relationships between workplaces, jobs, and individual tasks, preparing professionals to navigate ongoing technological disruption in their fields.
AI and the Workplace
Module 1 · 1 Hours to complete
AI & The Future of Journalism
Module 2 · 24 Minutes to complete
AI in Education
Module 3 · 1 Hours to complete
AI in Marketing
Module 4 · 56 Minutes to complete
AI in Your Workplace
Module 5 · 1 Hours to complete
AI Applications and Context
Module 6 · 22 Minutes to complete
Linking Workplaces, Jobs, and Tasks
Module 7 · 36 Minutes to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Navigating Disruption: Generative AI in the Workplace
Instructor
4 Courses
Leading Scholar in Political Communication and Public Opinion Research
Josh Pasek serves as Associate Professor of Communication & Media and Political Science at the University of Michigan, where he has established himself as an expert in political communication, public opinion, and survey methodology. His research focuses on how new media and psychological processes shape political attitudes and behaviors, as well as improving techniques for measuring public opinion. As a Faculty Associate in the Center for Political Studies and Core Faculty for the Michigan Institute for Data Science, he explores topics such as the impact of political information on public opinion, the changing political information environment due to social media, and methodological issues in survey research. His work has been published in top journals including Public Opinion Quarterly, Political Communication, and Communication Research. Pasek has developed two widely-used R packages for survey analysis: anesrake for producing survey weights and weights for analyzing weighted survey data. His academic journey includes a Ph.D. from Stanford University and previous positions at the University of Pennsylvania and University of Vienna before joining the University of Michigan in 2011.
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