ESE 359-Signals, Data, and Equity

Description

This course introduces the design of classification and estimation systems for equity, that is, with the goal of reducing the inequities of racism, sexism, xenophobia, ableism, and other systems of oppression. Systems which change the allocation of resources among people can increase inequity due to their inputs, the systems themselves, or how the systems interact in the context in which they are deployed. This course presents background in power and oppression, to help predict how new technological and societal systems might interact, and when they might confront or reinforce existing power systems. Measurement theory, the study of the mismatch between a system's intended measure and the data it actually uses, is covered. Multiple example sensing and classification systems which operate on people are covered by implementing algorithms and quantifying inequitable outputs.

The course has (loosely) three sections:

I. Space-shaping & context
II. Medical systems
III. Locality & indigeneity.

Timings

• Class: MW 10-11:20am in McDonnell 361.

• Office hours: Tu 4-5pm, W 11:30-12:30pm in Green 2155.

Resources

The course will draw from many resources listed on Canvas and (to a more limited extent) in the course schedule below.

Safe + Brave

This is a discussion-based course where we will all commit to cultivating a safe and brave environment for all students to participate in. We use the five pillars of Arao and Clemens to frame what such a space consists of:

• “Controversy with civility” where varying opinions are accepted,

• “Owning intentions and impacts” in which participants acknowledge and discuss instances where a dialogue has affected the emotional well-being of another person,

• “Challenge by choice” where participants have an option to step in and out of challenging conversations,

• “Respect” where students show respect for one another’s basic personhood,

• “No attacks” where students agree not to intentionally inflict harm on one another.

You can also feel very free to call me out on words or actions that hinder these aims. Here is an anonymous google form where you can let me know about any concerns.

Assessment

• Projects (60%)

  • • two "what could go wrong?" reports - due 9/22 and 10/13 (20%)

    • partly in-class lab - due 10/20 (20%)

    • wiki project - due 12/8, late due date 12/11 (20%)

• Participation (30%)

  • • preparing for and engaging in discussion (10%)

    • self-reflections (10%)

    • attendance (10%)

• Conversation / oral exam - during the week of 10/28 (10%)

Completion:

• Missing one reflection won't impact your grade. After this point, each missed reflection counts as -1% up to -10%.

• Five unexplained class absences won't impact your grade. After this point, each unexplained absence counts as -1% up to -10%. 

Virtual testing: I will offer a virtual option for attending class, assessed conversations, and other sharing moments in circumstances such as quarantine due to sickness or potential exposure to covid-19.

Late submission: Any deadlines are soft in the sense that work can still be submitted up to one hour after the deadline has passed but may receive a 10% scalar penalty (i.e. if you score 90% it may count as 81%).

Makeups: Because of the features above makeups are not be permitted under any circumstances.

Integrity

• Attempting to cheat in this course is unacceptable and will be strongly penalised. A first offense will be penalised with a zero grade on the relevant piece of assessment. A second offense will be penalised with an immediate fail grade.

• Collaboration is permitted (actually encouraged!) on homework assignments, however each student must write up solutions in their own words.  Please write the names of any other students you have collaborated with at the top of each assignment. Significant similarities between submissions from different students that fail to mention any collaboration counts as an act of cheating and will be penalised as such.

Syllabus