Course Description

This course is devoted to helping you understand contemporary changes to work and working. This is a survey course-a heads-in course-designed to provide you with a way of understanding and analyzing what it means to work -and to be a workeras the workplace changes in response to the globalization of market forces,the centrality of knowledge work (or cognitive labor) and the increasing prevalence of digital technologies to enable, augment and do work. These technologies span the range of office systems, enterprise systems, digital platforms, computing infrastructures, and involve both personal and institutional uses. And, more and more, these digital systems rely on large-scale data collection and uses of machine learning and artificial intelligence.



Professor of Record

Steven Sawyer


Undergraduate students.

Learning Objectives

After taking this course, students will be able to:

  • Characterize changes to work due to the forces such as:
    • increased reliance on knowledge-based(cognitively-demanding) work as one engine of the economy(relative to industrial or effort-based work)
    • increases in the uses of information and communication technology (ICT)-reliant systems that layer traditional systems with artificial intelligence, (AI), robotics, and/or social media,
    • changing relationships among workers and employers to be more market-based,shifting responsibility for risk from the employer to the worker, meaning that skill development, career planning and retirement are mostly the worker’s responsibility,
    • changing demographics of work towards a more diverse workforce comprising ever more of women, older workers, immigrants, and younger workers,
    • Increasingly global, and non-place-based,labor markets, 
    • New expectations of workplaces viz mobility, co-working, commuting, travel, hoteling, virtual interactions, work-at-home, etc.
  • Articulate expected and unexpected effects due in part to the automation of work, to include This requires applying concepts of automation to specific contemporary systems and technologies that showcase the trends of extensive data collection and uses to support machine learning, artificially-intelligent capacities, and both large-scale (platform-level)and firm-level (e.g.robotic process automation) use

Course Syllabus

IST 429 Spring 2022 Syllabus- Ingrid Erickson

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