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RES.TLL-008 | Fall 2022 | Non-Credit

# Social and Ethical Responsibilities of Computing (SERC)

### 6.170 Software Studio

Authors: Daniel Jackson, Arvind Satyanarayan, Serena Booth

Resources: 5 assignments with SERC design reflections; module lecture on responsible Design; final project

Keywords: software design, local government, ethical assessment

### 6.864 Quantitative Methods for Natural Language Processing

Authors: Jacob Andreas, Catherine D’Ignazio, Harini Suresh

Assignment: “Dataset Creation”

Keywords: data annotation; natural language processing; machine learning; content moderation

Topics addressed:

- Critical assessment of how and by whom a given dataset was created
- What its limitations might be
- What the data should and should not be used for

### 6.036 Introduction to Machine Learning

Authors: Leslie Kaelbling, Serena Booth, Marion Boulicault, Dheekshita Kumar, Rodrigo Ochigame

Weekly Labs: 4 weekly labs, each with a SERC question and discussion prompt

Keywords: machine learning; bias and fairness in machine learning; data bias; model bias

### MIT Case Studies in Social and Ethical Responsibilities of Computing

Brief, specially commissioned and peer-reviewed cases intended to be effective for undergraduate instruction across a range of classes and fields of study. Some cases are paired with active learning projects developed by students at MIT and reviewed by faculty and senior researchers.

Hacking Technology, Hacking Communities: Codes of Conduct and Community Standards in Open Source, by Christina Dunbar-Hester (University of Southern California)

Keywords: open source software, diversity and inclusion, community governance, gender, race, values in computing, codes of conduct

Identity, Advertising, and Algorithmic Targeting: Or How (Not) to Target Your “Ideal User”, by Tanya Kant (University of Sussex)

Keywords: targeting, advertising, algorithms, identity, profiling

Who Collects the Data? A Tale of Three Maps, by Catherine D’Ignazio (MIT) and Lauren Klein (Emory University)

Keywords: redlining, social inequality and oppression, missing data, counterdata, matrix of domination, who questions

The Case of the Nosy Neighbors, by Johanna Gunawan and Woodrow Hartzog (Northeastern University)

Keywords: user data privacy, technology in norm enforcement, facial recognition, mass surveillance, mass scraping of public data

Protections for Human Subjects in Research: Old Models, New Needs?, by Laura Stark (Vanderbilt University)

Keywords: human-subjects research, informed consent, institutional review boards, big data

### Active Learning Projects Developed at MIT

##### Active Learning Project: Exploring the Functionalities, Data and Interfaces of a Modern Online Advertising System (PDF - 1.1MB) (DOCX - 3.2MB)

An exercise to explore the ethical implications of digital advertising, grounded in the functionalities, data, and interfaces driving ad systems in the modern era. This lab focuses on Facebook’s Ads Manager.

- Associated case study: Kant, T. (2021). Identity, Advertising, and Algorithmic Targeting: Or How (Not) to Target Your “Ideal User.” MIT Case Studies in Social and Ethical Responsibilities of Computing, (Summer 2021). https://doi.org/10.21428/2c646de5.929a7db6

##### Active Learning Project: Active Learning Project on Developing Codes on Conduct (PDF) (DOCX)

An exercise in developing a code of conduct for a team-based course in Github-hosted project repositories.

- Associated case study: Dunbar-Hester, C. (2021). Hacking Technology, Hacking Communities: Codes of Conduct and Community Standards in Open Source. MIT Case Studies in Social and Ethical Responsibilities of Computing, (Summer 2021). https://doi.org/10.21428/2c646de5.07bc6308

## Course Info

##### Instructors

- Prof. Julie Shah
- Prof. David Kaiser

##### Departments

- Supplemental Resources

##### As Taught In

Fall 2022

##### Level

Non-Credit

##### Topics

- Engineering
  - Computer Science
    - Artificial Intelligence
- Teaching and Education
  - Curriculum and Teaching
  - Higher Education

##### Learning Resource Types

notes Lecture Notes
co_present Instructor Insights
assignment Multiple Assignment Types

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