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University at Buffalo

UB Graduate Academic Schedule: Spring 2023


This information is updated nightly. Additional information about this course, including real-time course data, prerequisite and corequisite information, is available to current students via the HUB Student Center, which is accessible via MyUB.


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CSE 540LEC - Machine Learning And Society
Lecture
Machine Learning And Society JOS2 Enrollment Information (not real time - data refreshed nightly)
Class #:   22310   Enrollment Capacity:   6
Section:   JOS2   Enrollment Total:   6
Credits:   3.00 credits   Seats Available:   0
Dates:   01/30/2023 - 05/12/2023   Status:   CLOSED
Days, Time:   M W , 10:00 AM - 11:20 AM
Room:   Obrian 209 view map
Location:   North Campus      
Reserve Capacities
Description Enrollment Capacity Enrollment Total  
Eng Sci MS: AI Seats Reserved 6 6  
Comments
Non CSE majors
Enrollment Requirements
Prerequisites: Pre-Requisite: CSE 531 or CSE 574
  Course Description
Machine Learning (ML) systems make decisions in all parts of our lives, starting from the mundane (e.g. Netflix recommending us movies/TV shows), to the somewhat more relevant (e.g. algorithms deciding which ads Google shows you) to the downright worrisome (e.g. algorithms deciding the risk of a person who is arrested committing a crime in the future). Whether we like it or not, ML systems are here to stay: the economic benefit of automation provided by ML systems means companies and even governments will continue to use algorithms to make decisions that shape our lives. While the benefits of using algorithms to make such decisions can be obvious, these algorithms sometimes have unintended/unforeseen harmful effects. This class will look into various ML systems in use in real life and go into depth of both the societal as well as technical issues. For students who are more technologically inclined, this course will open their eyes to societal implications of technology that such students might create in the future (and at the very least see why claiming ¿But algorithms/math cannot be biased¿ is at best a cop-out). For students who are more interested in the societal implications of algorithms, this class will give them a better understanding of the technical/mathematical underpinnings of these algorithms (because if you do not understand, at some non-trivial level, how these algorithms work you cannot accurately judge the societal impacts of an algorithm).
  Instructor(s)
             Rudra look up    
             Joseph look up    
  On-line Resources
Other Courses Taught By: Rudra
Other Courses Taught By: Joseph