11-830: Computational Ethics for NLP

Spring 2022

Summary

As language technologies have become increasingly prevalent, there is a growing awareness that decisions we make about our data, methods, and tools are often tied up with their impact on people and societies. This course introduces students to real-world applications of language technologies and the potential ethical implications associated with them. We discuss philosophical foundations of ethical research along with advanced state-of-the art techniques. Discussion topics include:

Instructors

TAs

Syllabus

Syllabus is subject to change, this will always be the latest version.

Week Date Theme Topics Readings Assignments
1 1/18 Introduction Motivation, requirements, and overview Barocas & Selbst (2016)
Hovy & Spruit (2016)
Jin et al. (2021)
 
  1/20 Project Introductions Project expectations and ideas    
2 1/25 Foundations Philosophical foundations & history    
  1/27 Foundations Philosophical foundations & history   Project pre-proposal due.
3 2/1 NLP for Social Good Invited talk – Alex Hauptmann    
  2/3 Objectivity and Bias Stereotypes, prejudice, and discrimination: background Buolamwini & Gebru (2018)
Stanovsky et al. (2019)
Birhane et al. (2021)
HW 1 released.
4 2/8 Objectivity and Bias Invited talk – Anjalie Field Field et al. (2021)
Field et al. (2022)
 
  2/10 Objectivity and Bias Bias detection and debiasing of data, algorithms, and models Zhao et al. (2017)
Sun et al. (2019)
Ahia et al. (2021)
 
5 2/15 Objectivity and Bias Invited talk – Sara Hooker Hooker (2021) HW 1 due.
  2/17 Civility in communication Bias detection and debiasing of data, algorithms, and models Chouldechova (2017)
Jurgens et al. (2017)
 
6 2/22 Civility in communication Invited talk – Maarten Sap Sap et al. (2019)
Sap et al. (2020)
Ma et al. (2020)
 
  2/24 Civility in communication Safe dialogue systems – Prakhar Gupta   HW 2 released. Project proposal due Fri, 2/25.
7 3/1 Civility in communication Identification of trolling, hate speech, abusive language, toxic comments Warner & Hirschberg (2012)
Schmidt et al. (2017)
Jurgens et al. (2019)
 
  3/3 Language of Manipulation Propaganda    
8 3/8 Spring break      
  3/10 Spring break      
9 3/15 Language of Manipulation Invited talk – Rayid Ghani    
  3/17 Language of Manipulation Fake news and influencing elections   HW 2 due, HW 3 released.
10 3/22 Midterm project presentations      
  3/24 Midterm project presentations      
11 3/29 Privacy, Profiling, Security Privacy and anonymity, Cambridge Analytica discussion Guardian article  
  3/31 NLP for Social Good Endangered languages   HW 3 due.
12 4/5 NLP for Social Good Invited talk - David Widder AI For Good Is Often Bad
The Invention of “Ethical AI”
Predictive policing in Pittsburgh
HW 4 released.
  4/7 No class      
13 4/12 NLP for Social Good NLP for child welfare – Nupoor Gandhi    
  4/14 AI and Climate Change AI and the climate, the hardware lottery, efficient NLP    
14 4/19 Intellectual Property Plagiarism and plagiarism detection. Patents.   HW 4 due.
  4/21 Discussion Code of Ethics    
15 4/26 Final project presentations      
  4/28 Final project presentations      
  5/6       Final project report due


Grading

Grades are based on a combination of homeworks and participation (individual) and a semester-long class project (group). All assignments are due at 11:59pm on the specified date.

Projects

A major component of this course is a team project. It will be a substantial research effort carried out by each group of students (expected group size = 3; 2-4 is acceptable). You can find some project ideas and resources here. Please use the #find-project-groups channel on Slack to find classmates with complementary interests and form groups. There will be a number of project milestones throughout the semester:

Policies

Late policy. Each student will have 4 total late days that may be used for HW assignments at any point during the semseter. Late days may not be used for project benchmarks. After all late days have been used, no credit will be given for homework submitted late.

Academic honesty. Homework assignments are to be completed individually. Verbal collaboration on homework assignments is acceptable, as well as re-implementation of relevant algorithms from research papers, but everything you turn in must be your own work, and you must note the names of anyone you collaborated with on each problem and cite resources that you used to learn about the problem. The project is to be completed by a team. You are encouraged to use existing NLP components in your project; you must acknowledge these appropriately in the documentation. Suspected violations of academic integrity rules will be handled in accordance with the CMU guidelines on collaboration and cheating.

Accommodations for students with disabilities. If you have a disability and have an accommodations letter from the Disability Resources office, we encourage you to discuss your accommodations and needs with the instructors as early in the semester as possible. We will work with you to ensure that accommodations are provided as appropriate. If you suspect that you may have a disability and would benefit from accommodations but are not yet registered with the Office of Disability Resources, we encourage you to contact them at access@andrew.cmu.edu.

Note to students!

Take care of yourself! As a student, you may experience a range of challenges that can interfere with learning, such as strained relationships, increased anxiety, substance use, feeling down, difficulty concentrating and/or lack of motivation. This is normal, and all of us benefit from support during times of struggle. There are many helpful resources available on campus and an important part of a healthy life is learning how to ask for help. Asking for support sooner rather than later is almost always helpful. CMU services are available free to students, and treatment does work. You can learn more about confidential mental health services available on campus through Counseling and Psychological Services (CaPS). Support is always available (24/7) at: 412-268-2922.

Take care of your classmates and instructors! In this class, every individual will and must be treated with respect. The ways we are diverse are many and are fundamental to building and maintaining an equitable and an inclusive campus community. These include but are not limited to: race, color, national origin, caste, sex, disability (visible or invisible), age, sexual orientation, gender identity, religion, creed, ancestry, belief, veteran status, or genetic information.

Research shows that greater diversity across individuals leads to greater creativity in the group. We at CMU work to promote diversity, equity and inclusion not only because it is necessary for excellence and innovation, but because it is just. Therefore, while we are imperfect, we ask you all to fully commit to work, both inside and outside of our classrooms to increase our commitment to build and sustain a campus community that embraces these core values. It is the responsibility of each of us to create a safer and more inclusive environment. Incidents of bias or discrimination, whether intentional or unintentional in their occurrence, contribute to creating an unwelcoming environment for individuals and groups at the university. If you experience or observe unfair or hostile treatment on the basis of identity, we encourage you to speak out for justice and offer support in the moment and/or share your experience using the following resources: