University Honors College - The Honorable mention

CSE 440/540 Machine Learning and Society Open to All Majors-Get Honors Experience Credit!

Posted by Tim on November 24, 2020 in Academics, Honors Experiences

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).

Pre-Reqs –
Section JOSE: (CSE Majors) CSE 474 (or CSE 331 and taking 474 at the same time)
Section JOS1: (non-CSE Majors): Permission of the instructor

The class is based off of Atri Rudra’s course from last semester, here’s his syllabus: I’ve also attached an initial version of the syllabus I’ll be using, although it definitely will change over the next few months.

Professor Kenny Joseph: