Could you be competing for a job–even after getting a college degree–with a robot or an AI-powered chatbot? As technologies advance, every few years, debates emerge: will this new kind of automation increase unemployment, or will it generate new kinds of jobs? Will these new jobs be more interesting and high-paying, or will they be boring and poorly paid? To think these questions through, in this course, we will study some key attempts to understand the socio-economic and political determinants as well as the repercussions of automation. We will look at historical examples of automation in the workplace as well as the most recent developments related to machine learning and AI. We will delve into the micro-level dynamics operating between machines and workers involved in concrete production processes. We will also explore the macro-level trends in national and global inequality that social scientists associate with automation. In our investigation of both macro- and micro-levels, we will focus on how the risks and benefits of automation get distributed unevenly along already existing axes of class, race, gender, etc.
Learning outcomes:
- Gain a familiarity with key social scientific theories about labor and automation
- Gain critical tools to study the impact of AI on different groups of workers
- Understand recent empirical research about automation and inequality in the workplace.
- Skills: critically reading sociological theories and empirical research; identifying and using scholarly sources; communicating social scientific research.
All materials will be posted on Canvas.
Assignments, Deadlines, and Grading:
Class participation (10% of the final grade)
While I will be lecturing in class, this is a discussion-based class. Regular class attendance is expected. Students will be expected to participate actively in class discussions, both individually and through group work. Writing and speaking in class are essential practices for learning new concepts. Hence, students are required to read the assigned readings before each class. As you read you should think about the following: (1) summarize the key arguments, key concepts, and the evidence provided, (2) evaluate the strengths and weaknesses of the evidence and argument, (3) reflect on how the reading relates to previous readings and class discussions, (4) things that are not clear to you about the argument, and (5) pose 1-2 questions about the readings. These elements will help you participate in class discussions the next day.
Mid-term Open Book In-class Exam (Mar 19; 30% of the final grade)
This exam is designed as a checkpoint for your learning, not a high-pressure test. It will give you an opportunity to reflect on and apply the ideas we’ve explored together.
- Format: You’ll answer three short-answer questions (300-500 words each) from a set of five.
- Content: All questions will come from the readings and discussions we’ve already covered in class. If you’ve been engaged and taken notes, you’re already well-prepared.
- Allowed reference materials: You may bring printouts of the course readings to class. Laptops or other devices are not allowed.
- Goal: The exam is about demonstrating your understanding of key concepts and making connections between readings—not memorizing details.
- Support: If you have questions or want to review strategies, please come to office hours.
Final Presentations (Apr 14, 16, 21, 23; in alphabetical order) (50% of the final grade)
Your final project is an 8-minute class presentation on AI as a form of labor automation and its impact on social inequality. You can choose a case of an occupation or industry as your focus. Regardless of the case you choose, your presentation must clearly demonstrate how you think AI impacts work and social inequality. You may choose to engage with one or more axes of inequality (class, gender, race, or Global North-South). You should find ONE academic book or TWO journal articles related to your case. You must also engage with LPT and SBTC concepts, as well as at least one other study covered in the class. You must also clearly engage with our discussions in the course as well as the course material. Note that this assignment is about showing that you have engaged with the course readings and can apply what you learned to a new situation.
Points to Grades:
A (90-100), B (80-89), C (<70-79), D (60-69), F (<60)
The policy for late assignments is that you will need a documented health, funeral, or university-sponsored excuse for turning in late assignments at full credit. Assignments turned in after their due dates without an excuse will receive a drop in letter grade every two days beyond their due date.
Accommodations
If you are a student with learning needs that require special accommodation, contact the Office of Disability Services at 404.894.2563 or their website as soon as possible to discuss your needs and to obtain an accommodations letter. Then, make an appointment with me as soon as possible to discuss your learning needs.
Attendance will be taken in every class period, and this will determine the classroom participation grade listed above. Class attendance is central to your learning in this course, and a lot of important material will be introduced during class that will go beyond the readings. Missing too many classes will impact your ability to follow subsequent classes and do your assignments.
But life happens! Excused and documented absences will not affect the participation grade, though. If you will be missing a class, please send a brief email in advance so that your class participation grade is not impacted. If you’re unwell, please get a doctor’s note. If you have a sports meeting, please get a letter from your coach. Prioritize your health and stay home if you’re unwell. If you are unable to attend class for three consecutive meetings due to a prolonged illness, please send along a doctor’s note and see the Accommodations section below. If you feel you are having trouble catching up, please set an appointment for office hours.
Students are expected to maintain the highest standards of academic integrity. All work submitted must be original and properly cited. Plagiarism, cheating, or any form of academic dishonesty will result in immediate consequences as outlined in the university's academic integrity policy.
Academic misconduct is described fully in two documents: the Student Code of Conduct and the Academic Honor Code. The Student Code of Conduct outlines the lnstitute’s expectations for academic and nonacademic conduct as well as students' rights and seeks to foster an environment conducive to academic excellence. The Code outlines nine charges that apply to academic misconduct. The Georgia Tech Academic Honor Code is a guide that articulates student and faculty expectations; it is designed to strengthen the level of academic integrity and trust within the Tech community. As described in the Academic Honor Code, faculty members are expected to create an environment where honesty flourishes.
This is a Core IMPACTS course that is part of the Social Sciences area.
Core IMPACTS refers to the core curriculum, which provides students with essential knowledge in foundational academic areas. This course will help master course content, and support students’ broad academic and career goals.
This course should direct students toward a broad Orienting Question:
• How do I understand human experiences and connections?
Completion of this course should enable students to meet the following Learning Outcome:
• Students will effectively analyze the complexity of human behavior, and how historical, economic, political, social, or geographic relationships develop, persist, or change.
Course content, activities and exercises in this course should help students develop the following Career-Ready Competencies:
- Intercultural Competence
- Perspective-Taking
- Persuasion