Fall 2020 - CMNS 855 G200

Selected Topics in Communication Studies (5)

Marxism and Communication

Class Number: 7026

Delivery Method: Remote

Overview

  • Course Times + Location:

    Sep 9 – Dec 8, 2020: Fri, 5:30–8:20 p.m.
    Burnaby

Description

CALENDAR DESCRIPTION:

Specialized one-time graduate course offerings on topics related to the current research of school faculty of visiting professors.

COURSE DETAILS:

This course will introduce major contributions of Marxism to understanding society. The themes treated will include the nature of alienation and capitalism, the concepts of reification and hegemony, the critique of advanced industrial society and colonialism. The classic texts we will study will prepare you to read contemporary Marxist authors who apply Marxism to the current social world.

Today, we find confident announcements that AI will bring about humanoid robots, the end of work, perhaps the obsolescence of humanity. But such prognoses look rather different when we consider their own history. Technological fantasies are often recycled over decades, leaving unbuilt prototypes and outmoded theories in their wake, sustaining the same old social problems.

From the 20th century legacy of cybernetics to 1970’s debates around artificial intelligence, from early modern systems of calculation and surveillance to today’s smart doorbells and predictive policing systems, we find a long history of moral dilemmas, enduring biases and unresolved social problems. The latest smart machines too often reprise the classic gender roles of the Jetsons (itself a Flintstones of the future), a pattern also repeated in our most contemporary fictions (e.g. Blade Runner 2049). 

This seminar equips students with a richer, more balanced understanding of how we think and talk about data and AI today. It develops situational awareness of relevant contemporary research in history of science and technology, STS, media and communication studies, as well as machine ethics and critical algorithm studies. There is a strong focus on bringing historical and philosophical lessons back to the pressing debates today – around data privacy and surveillance, Big Tech and anti-trust proposals, fake news and hate speech. 

 

COURSE-LEVEL EDUCATIONAL GOALS:

This is a seminar course with an emphasis on in-class discussion around the readings, relevant research, current affairs, and moral / ethical dilemmas. The objective is to develop a more historically, culturally, and philosophically informed position to better address ongoing societal issues surrounding big data and artificial intelligence.

Grading

  • Participation & Weekly Exercises 40%
  • Final Project 60%

Materials

MATERIALS + SUPPLIES:

No required textbooks; all readings will be on syllabus & provided by instructor.

REQUIRED READING:

No required textbooks; all readings will be on syllabus & provided by instructor.

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

TEACHING AT SFU IN FALL 2020

Teaching at SFU in fall 2020 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.

Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112).