# [11-830 Ethics, Social Biases, and Positive Impact in Language Technologies]() ## **Spring 2024** - **Time**: 11:00-12:20 Tuesdays & Thursdays - **Place**: POS 153 - **Canvas**: https://canvas.cmu.edu/courses/38870 (for discussions, assignments, questions, etc.) - **Zoom**: Check canvas. - For other, e.g., more personal, concerns, email the instructor ([msap2@andrew.cmu.edu](mailto:msap2@andrew.cmu.edu)). ----- ### 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: - **Philosophical foundations:** ethical philosophies, history, medical and psychological experiments, IRB and human subjects, ethical decision making, AI alignment. - **Bias, Misrepresentation, Alignment:** algorithms to identify biases in models and data and adversarial approaches to debiasing. - **Civility in communication:** techniques to monitor trolling, hate speech, abusive language, cyberbullying, toxic comments. - **Democracy and the language of manipulation:** approaches to identify propaganda and manipulation in news, to identify fake news, political framing. - **Privacy & security :** algorithms for demographic inference, personality profiling, and anonymization of demographic and personal traits. - **NLP for Social Good:** Low-resource NLP, applications for disaster response and monitoring diseases, medical applications, psychological counseling, interfaces for accessibility. - **Multidisciplinary perspective:** invited lectures from experts in behavioral and social sciences, rhetoric, etc.

Instructor

Maarten Sap

Assistant Professor, LTI

Office hours: Tuesdays 3-4pm (GHC 6713)


TAs

Ritam Dutt

PhD Student, LTI

Office hours: Thursdays from 2-3 PM (via Zoom).

Xuhui Zhou

PhD student, LTI

Office hours: Thursdays from 4-5 PM (GHC 5705)

---- ### Schedule |Week|Date|Theme|Topics|Assignments| |---|---|---|---|---| |1|01/16|Introduction|Motivation, requirements and overview|All homeworks released| ||01/18|Introduction|Project expectations and ideas|| |2|01/23|Philosophical Foundations & History|Overview -- Moral theories, trolley problem, history of ethics, etc.|| ||01/25|Philosophical Foundations & History|*Guest Lecture -- [Sydney Levine](https://sites.google.com/site/sydneymlevine/) (AI and moral reasoning)*|Preproposals & project teams due (Friday 1/26)| |3|01/30|Philosophical Foundations & History|Human subjects, IRB and crowdsourcing|| ||02/01|Philosophical Foundations & History|Discussion|Proposal is due (Monday 2/05)| |4|02/06|Objectivity and Bias|Stereotypes, prejudice, and discrimination: background|| ||02/08|Objectivity and Bias|Bias detection, debiasing, perspectivism|| |5|02/13|Objectivity and Bias|Discussion|| ||02/15|Civility in communication|Overview|[HW 1](./hw1.html) update: due Sunday 2/18 11:59pm| |6|02/20|Civility in communication|Toxicity in LMs|| ||02/22|Civility in communication|Detoxying LMs & Toxicity in Conversations|| |7|02/27|Civility in communication|Discussion|| ||02/29|Misinformation & Manipulation|Overview|[HW 2](./hw2.html) due update: due Friday 3/01 11:59pm| |--|03/05|--- *Spring break* ----|---|| ||03/07|--- *Spring break* ---|---|| |8|03/12|Misinformation & Manipulation|*Guest lecture -- [Saadia Gabriel](https://saadia-gabriel.github.io/) (Misinformation and NLP)*|| ||03/14|Midterm project check-ins|----|Midterm project check ins| |9|03/19|Misinformation & Manipulation|Discussion|| ||03/21|Privacy, Profiling, Security|Overview: Privacy and profiling|[HW 3](./hw3.html) due| |10|03/26|Privacy, Profiling, Security|*Guest Lecture -- [Niloofar Mireshghallah](https://cseweb.ucsd.edu/~fmireshg/) (privacy & Security in NLP)*|| ||03/28|Privacy, Profiling, Security|*Guest Lecture -- [Willie Agnew](https://sites.google.com/cs.washington.edu/william-agnew/home) (AI and surveillance, Queer in AI, etc.)*|| |11|04/02||*TA Guest lectures (Ritam, Xuhui)*|| ||04/04|NLP for Social Good|NLP for social good overview, pitfalls, challenges|[HW 4](./hw4.html) due| |12|04/09|NLP for Social Good|*Guest Lecture -- [Graham Neubig](https://www.phontron.com/) (Ethics of Multilingual NLP)*|| ||04/11|No class -- Spring Carnival|...|| |13|04/16|NLP for Social Good|*Guest lecture -- [Emma Strubell](https://strubell.github.io/) (AI, Energy Efficiency, and Climate Change)*|[HW 5](./hw5.html) due (*extra credit*)| ||04/18|NLP for Social Good|Discussion|| |14|04/23|Final project presentations||Final project presentations| ||04/25|Final project presentations||Final project presentations| |15|04/30|---|---|Final reports due (Tuesday 4/30)| ---- ### 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 Eastern on the specified date. - **Homework assignments.** (4 assignments; 50% total) Each assignment contains a combination of coding, analysis, and discussion. For each assignment, completing the baseline requirements will obtain a passing (B-range) grade. A-range grades can be obtained through completing the open-ended “Advanced Analysis” part of the assignment. Assignments are not necessarily designed to focus on technical solutions, but instead to encourage students to think critically about the course material and understand how to approach ethical problems in NLP, while also allowing for exploration of various methodologies. - **Project.** (30%) a semester-long 3- or 4-person team project (more details below and in class). - **Participation.** (20%) classes will include discussions of reading assignments. Students will be expected to read relevant papers and participate in class discussions. Participation points can also be earned by posting interesting questions and useful answers on Canvas/Slack. ---- ### 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](https://docs.google.com/document/d/1PfUU79IyiQUlbENwthkjbg4pTE-hAhXX9p7PwQLTNhg/edit?usp=sharing). Please use the "Find project groups" discussion in Canvas to find classmates with complementary interests and form groups. There will be a number of project milestones throughout the semester: - **Pre-proposal:** (2%) Brainstorming phase: pick two or three project ideas and flesh them out, in a 1-2 paragraph describing the focus area of the project along with quick-and-dirty method descriptions and stretch goals. Also, define team members. - **Proposal:** (8%) Pick a project: A 2-3 page document ([ACL format](https://github.com/acl-org/acl-style-files)) containing a literature review, concrete problem definition and bias statement, evaluation criteria, identification of baseline models, and ideas for final models. Sections should include Introduction (incl. Bias Statement), Related Work, Data, Evaluation, Baseline, Proposed Approach. Baselines should be clearly defined but do not need to be implemented yet. - **Midterm check-ins:** (2%) An in-class presentation of project and current progress. Presentation should include problem definition, baseline models and results, and description of proposed models. - **Final Presentations:** (6%) In-class presentations of the project will be held during the last week of classes. See here for [rubric and tips on how to make your final presentation](projectRubric.html). - **Final Report:** (12%) A final project report will be due the following week. We will use the 8-page ACL Rolling Review [format](https://github.com/acl-org/acl-style-files), [author guidelines](https://aclrollingreview.org/authors), and [Code of Ethics](https://www.aclweb.org/portal/content/acl-code-ethics). See [here for a rubric](projectRubric.html). ---- ### Discussion format Some of the lectures will be discussion-based. To make the discussion more lively and engaging, we will adopt reading roles, inspired by [Alec Jacobson and Colin Raffel' seminar](https://colinraffel.com/blog/role-playing-seminar.html) and Aditi Raghunathan's [15-884 class](https://www.cs.cmu.edu/~aditirag/teaching/15-884F22.html). Each student will play one of the following roles: - *Reviewer*: who discusses the strengths and weaknesses of the paper, either advocates for the paper to be accepted at a conference (e.g., [ACL, EMNLP](https://2021.aclweb.org/blog/instructions-for-reviewers/), [FAccT](https://facctconference.org/2022/reviewer_instructions.html)) or advocates for its rejection. - *Archaeologists I & II*: who determines where this paper sits in the context of previous and subsequent work. Keep an eye out for work that contradicts the takeaways in the current paper. - *Forensic archaeologist*: find and report on at least one older paper cited within the current paper that substantially influenced the current paper and at least one newer paper that cites this current paper. Do not choose any of the other papers assigned for this week. - *Community archaeologist*: choose two of the other papers assigned for this week, and discuss connections or conflicts with respect to your assigned paper. **This role will be responsible for sharing out in class**. - *Academic researcher*: who proposes potential follow-up projects not just based on the current paper but also only possible due to the existence and success of the current paper. - *Visitor from the past*: who is a researcher from the early 2000s. They must discuss how they comprehend the results of the paper, what they like or dislike about the settings and benchmarks considered, and what surprises them the most about presented results. Discussion grading: - You will be automatically assigned a role for each discussion class - **Before each discussion class**, you will post your talking points on Canvas (due the day before class). These notes should include your role, and 2-4 talking points. Make sure to go into enough depth that others can understand what you're saying (simply adding more shallow talking points will not lead to a better grade). - **After each discussion class**, you will reply to your notes and briefly discuss one reflection or point that you had not previously thought about. This can be significantly shorter than the initial post. ---- ### Policies **Late policy.** Each student will have 4 total late days that may be used for HW assignments at any point during the semester. Once the 4 days have been used up, you can still submit your assignments late, but at a loss of 20% (i.e., maximum grade is 80%), and not after the next assigment is due / after finals week. *Note: late days may not be used for project benchmarks.* **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](http://www.cmu.edu/policies/documents/Cheating.html). **AI-assisted writing policy.** We will follow the [ACL 2023 policy](https://2023.aclweb.org/blog/ACL-2023-policy/) on the use of AI assistants for writing. This means you may use AI tools for checking your writing and correcting your grammar; any usage beyond that (idea generation, literature review, etc.) is strongly discouraged or forbidden, see the policy for details. **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](https://www.cmu.edu/disability-resources/), we encourage you to contact them via their website. ---- ### 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)](https://www.cmu.edu/counseling/). 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: - [Center for Student Diversity and Inclusion](https://www.cmu.edu/student-diversity/): [csdi@andrew.cmu.edu](mailto:csdi@andrew.cmu.edu), (412) 268-2150 - [CMU anonymous reporting hotline](https://secure.ethicspoint.com/domain/media/en/gui/81082/index.html), (844) 587-0793