Please Note
It is your responsibility to make sure you read and understand the contents of this syllabus. If you have any questions, please contact the instructor.
Table of contents
- Basic Course Information
- Course Description
- Credits
- Instructors
- Academic Integrity
- COVID-19
- Companion Class
- Pre-requisites
- ABET Learning Outcomes
- References
- Schedule
- Piazza
- Grading Policy
- Impossible Project
- In-class discussions and Discussion Summaries
- Course Survey
- Attendance
- Unit Midpoint Submissions
- Bonus
- Accessibility Resources
- Critical Campus Resources
- Preferred Name
- Diversity
- Suggestions or Comments?
Basic Course Information
- Spring 2024 course
- Times: Mondays and Wednesdays, 10-11:20am
- Location: Norton 209
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).
The class will also provide you with the opportunity to engage in a semester-long project with an interdisciplinary team, and to learn about the important intersections between machine learning and history.
Students cannot take both CSE majors version (CSE 440 and Section JOSE of CSE 540) and the non-majors one (CSE 441 and Section JOS2 of CSE 540).
Credits
3 credits
Instructors
It is preferable to set up an appointment (by email) if you want to talk to us outside of our office hours. However, you can drop by if our office door is open.
Academic Integrity
Penalty for Violations
In accordance with the current departmental policy on academic integrity violations, we will follow this procedure in CSE 440/441/540:
- If the violation is the student’s second academic violation, then it will result in an automatic
Fletter grade in the course. - If the violation is the first ever academic violation, then it will result in a minimum of a
letter grade reductionin the grade for course andzero in the relevant assignment. If the violation is serious enough, then it can result in anF in the course. While it gives us no pleasure in failing students, we will do so since we have to be fair to (the vast majority) of students who do not cheat.
Generative AI Policy
In short, the course policy for the use of Generative AI is that any use of a Generative AI tool for any purpose in the tool must be explicitly approved by either Atri or Kenny. This includes, but is not limited to, the need for explicit approval to use Generative AI tools (e.g. ChatGPT) to help with writing and to ideate on projects. Failure to follow this policy will result in a violation of the Academic Integrity rules for this course.
Some notes on this policy:
- This is not us saying that the use of Generative AI is off limits, but rather that there are good and bad uses from an instructional perspective, and we want to discuss these uses with you.
- We are unlikely to approve the use of ChatGPT to “fix” one’s writing - we’d rather just see your writing, imperfections and all, than a filtered version of it!
Policy on improper distribution of course materials
All materials prepared and/or assigned by us for this course are for the students’ educational benefit. Other than for permitted collaborative work, students may not photograph, record, reproduce, transmit, distribute, upload, sell or exchange course materials, without our prior written permission. “Course materials” include, but are not limited to, all instructor-prepared and assigned materials, such as lectures; lecture notes; discussion prompts; study aids; tests and assignments (and their solutions); and presentation materials such as PowerPoint slides, Prezi slides, or transparencies; and course packets or handouts. Public distribution of such materials may also constitute copyright infringement in violation of federal or state law. Violation of this policy may additionally subject a student to a finding of “academic dishonesty” under the Academic Integrity Policy and/or disciplinary charges under the Student Code of Conduct. For more details, please see the undergrad department policy on academic integrity, and/or the graduate policy.
COVID-19
Please follow UB/SUNY protocols regarding COVID-19. This page has an overview of updates and policies .
Specifically, please note that following parts of the If you are sick, monitoring health :
If students need to miss class, an exam, work or an assignment due to illness and isolation, they must notify their instructor and/or supervisor as soon as possible and no later than 24 hours.
Lectures, presentations and office hours will be held in-person. These are subject to change based on current UB/SUNY policies.
Companion Class
As this website suggests, this semester’s Machine Learning and Society course will be run in concert with HIS 419/550: Rage Against the Machine, which is a class that explores the history of white supremacy in and beyond the United States.
There will be some classes that will be combined that students from HIS 419/550 and CSE 440/441/540 will attend together (in the usual class room- Norton 209). The schedule page has the details.
Pre-requisites
For all sections, willingness to think beyond your usual boxes and openness to unfamiliar ideas will be crucial.
CSE 440
CSE 440 is meant for CSE majors and has a formal pre-requisite of CSE 474 OR (CSE 331 and CSE 474 as a co-requisite).
CSE 540, Section JOSE
CSE 540 is meant for CSE majors and has a formal pre-requisite of CSE 574 OR CSE 531
CSE 441 and Section JOS2 of CSE 540
CSE 441 and Section JOS2 of CSE 540 are meant for non-CSE majors and have no formal pre-requisites (besides being a junior in their major).
ABET Learning Outcomes
ML and Society course is an elective and after the completion of the course, students should demonstrate mastery of the concepts/skills/knowledge expressed in the following ABET learning outcomes for computer science:
(1)Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions.(3)Communicate effectively in a variety of professional contexts.(4)Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.(5)Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.
The learning outcomes for CSE 440 and Section JOSE of CSE 540 (henceforth, just CSE majors) and CSE 441 and Section JOS2 of CSE 540 (henceforth, just non-CSE majors) are different (the specific outcomes that is different is in bold and italicized in both tables).
Learning outcomes for CSE majors
| Course Learning Outcome | Program Outcomes / Competencies | Instructional Method(s) | Assessment Method(s) |
| Be able to identify the various stages of ML pipeline | ABET (1) | Lectures | Discussion summaries, Impossible project |
| Code up an end to end ML system that takes its societal impacts during its design phase | ABET (1) | Lectures | Impossible Project |
| Be able to use identify societal implications of an ML system | ABET (4) | Lectures | Discussion summaries, Impossible project |
| Be able to work in a group to solve not well defined problems | ABET (5) | In-class meetings | Impossible project |
| Be able to present the same work in different media | ABET (3) | In-class meetings | Impossible Project, Discussion participation |
The Student Outcomes from the Computing Accreditation Commission (CAC) of ABET have been adopted .
Program Outcome Support (Computer Science ABET Outcomes):
| Program Outcome | 1 | 2 | 3 | 4 | 5 | 6 |
| Support Level | Demonstrate mastery of skill/concept | No coverage | Demonstrate mastery of skill/concept | Demonstrate mastery of skill/concept | Demonstrate mastery of skill/concept | No coverage |
Learning outcomes for non-CSE majors
| Course Learning Outcome | Program Outcomes / Competencies | Instructional Method(s) | Assessment Method(s) |
| Be able to identify the various stages of ML pipeline | ABET (1) | Lectures | Discussion summaries, Impossible project |
| Interact with the team that codes up an ML system and point out societal harms in various stages of the ML system | ABET (1) | Lectures | Impossible Project |
| Be able to use identify societal implications of an ML system | ABET (4) | Lectures | Discussion summaries, Impossible project |
| Be able to work in a group to solve not well defined problems | ABET (5) | In-class meetings | Impossible Project |
| Be able to present the same work in different media | ABET (3) | In-class meetings | Impossible Project, Discussion participation |
References
There is no textbook
The material covered in this course is fairly new and there is not appropriate textbook that covers the material presented in this class.
We will either provide lecture notes or relevant papers for the lectures and in-class discussions.
Schedule
See the schedule page
Piazza
We will be using Piazza for all CSE 440/441/540 related announcements. If you are attending the course, you must check Piazza regularly. We would strongly urge you to enable email notifications on piazza (it is on by default). These announcements will include the ones that inform if and when classes/office hours are re-scheduled etc.
There will be an entry for each lecture. Sometimes, the entries may include side comments or stories that we feel are relevant to the course (but are not directly related to the lectures).
We will also be using Piazza for class discussion. The system is highly catered to getting you help fast and efficiently from classmates and myself. Rather than emailing questions to the teaching staff, we encourage you to post your questions on Piazza. If you have any problems or feedback for the developers, email team@piazza.com. To familiarize yourself with the system, look at their help page .
You should be signed up for Piazza by now. If for some reason that did not work, please go to the Piazza sign up page .
Few other points:
- You can post anonymously but note that you will be anonymous to students only. Your identity will be known to the instructors.
- Please make sure that you use your UB email to sign up– this is to make sure that we can verify your identity if necessary.
- You can write posts that are private to just the instructors but if we feel that the answer would be relevant to the class then we reserve the right to make the post public. (If you would like not to have your name in the public version of your private post, please post anonymously in the private post too. Note by the first point, we will still know your identity.)
Grading Policy
Here is the split of grades:
| Course Component | $\%$ of grade |
| Impossible Project | $50\%$ (10 per unit, 20 for the finale) |
| Attendance | $10\%$ (with important caveats, see below) |
| Discussion Summaries | $9\%$ ($3\%$ each) |
| Class Discussion Participation | $2\times 2 +3 \times \frac 23=6\%$ ($2\%$ and $\frac 23\%$ each for two ML-Soc and three Rage discussions resp.) |
| Unit Midpoint Submissions | $21\%$ ($7\%$ each) |
| Course pre/post surveys | $4\%$ ($2\%$ each) |
| Bonus | Up to $5\%$ |
See the next few sections for more details on each of the above components.
Letter Grades
The letter grade cutoffs will be different for undergraduates (i.e. those enrolled in CSE 440 and CSE 441) and for graduate students (i.e. those enrolled in CSE 540). In particular, the grade cutoffs for undergraduates will be about 5 points lower (though we reserve the right to change this number a bit).
Grade cutoffs for graduate students
Below is the tentative cutoffs for the letter grades for CSE 540:
| Grade | Quality Points | Percentage |
| $A$ | 4.0 | 90.0% or more |
| $A^-$ | 3.67 | 80.0% - 89.95% |
| $B^+$ | 3.33 | 75.0% - 79.95% |
| $B$ | 3.00 | 70.0% - 74.95% |
| $B^-$ | 2.67 | 65.0% - 69.95% |
| $C^+$ | 2.33 | 60.0% - 64.95% |
| $C$ | 2.00 | 55.0% - 59.95% |
| $C^-$ | 1.67 | 50.0% - 54.95% |
| $D^+$ | 1.33 | 45.0% - 49.95% |
| $D$ | 1.00 | 40.0% - 44.95% |
| $F$ | 0 | 39.95% or below |
Grade cutoffs for undergraduate students
Below is the tentative cutoffs for the letter grades for CSE 440/441:
| Grade | Quality Points | Percentage |
| $A$ | 4.0 | 85.0% or more |
| $A^-$ | 3.67 | 75.0% - 84.95% |
| $B^+$ | 3.33 | 70.0% - 74.95% |
| $B$ | 3.00 | 65.0% - 69.95% |
| $B^-$ | 2.67 | 60.0% - 64.95% |
| $C^+$ | 2.33 | 55.0% - 59.95% |
| $C$ | 2.00 | 50.0% - 54.95% |
| $C^-$ | 1.67 | 45.0% - 49.95% |
| $D^+$ | 1.33 | 40.0% - 44.95% |
| $D$ | 1.00 | 35.0% - 39.95% |
| $F$ | 0 | 34.95% or below |
Changing cutoffs
We reserve the right to change the cutoffs depending on overall class performance (and the cutoff changes could be different for CSE-majors vs. non-CSE majors/undergraduates vs. graduates. However, we will only move the cutoffs down. In other words, in case you are in a certain percentage range in the last column in the table above, then the letter grade in the corresponding first column is the minimum letter grade you will receive.
Incompletes
Incompletes (the grade of “I”) will not in general be given. This is reserved for the rare circumstance that prevents a student from completing the work in the course. University and Department policy dictates that an “I” can be given only if both of the following conditions are met: (i) only a small amount of work remains, such as the final exam and one or two assignments, and (ii) the student has a passing average in the work completed. In such a circumstance, the student will be given instructions and a deadline for completing the work, which is usually no more than 30 days past the end of the semester. Please see the UB catalog link for more.
Grading Scheme
All submissions in this course will be graded manually by us and we will use the following “level” system. For each question/part of an assignment, the student’s submission will be graded at one of the following levels:
- Level 0: This means the student gets $0\%$ of the points. This is for submissions where the student shows zero comprehension: either in understanding the problem or of its solution.-
- Level 1: This means the student gets $25\%$ of the points. This is for submissions where the student does show some comprehension of the problem and/or the required solution but there is at least one flaw that cannot be repaired.-
- Level 2: This means the student gets $50\%$ of the points. This is for submissions where the student gets the main idea but there are still flaws that can be repaired but only with a lot of extra work.-
- Level 3: This means the student gets $80\%$ of the points. This is for submissions where the student has got the main idea but the execution is a bit faulty. However, these faults could be fixed without too much extra work.-
- Level 4: This means the student gets 100% of the points. The solution is almost perfect.
The description of what constitutes a certain level is a bit generic so that it applies to the different parts of the course. For each submission, we will clarify exactly what parts are expected in a submission.
Impossible Project
For details on the project, including grading, see the Project page
The Impossible Project will assess student outcomes (1), (3), (4), (5).
In-class discussions and Discussion Summaries
For details on class discussions and the reading responses required before class for them, see the Class Discussions page
The discussion summaries will assess student outcome (1), (4).
Course Survey
Y’all will need to submit a pre-course survey and a post-course survey.
If you join the class late…
If you are in class the first day of the semester, you will take it in class. If not, you will need to take it prior to your first attendance in class. The post-course survey will be due by 5pm on Sunday, May 14.
Grading
Each survey is worth $2\%$ of your final grade. These surveys will be graded just on completion: i.e. if you submit a survey you get full points and if you do not submit a survey you do not get any points.
Attendance
Read carefully!
Attendance is critical in this class, and thus the attendance policy is strict. Make sure you read the attendance policy carefully!
Meaning of “excused absence
When we say “excused absence” below, we are referring to absences that are excused under the official UB Policy.
Attendance points are all or nothing. Moreover, violating the attendance policy means that your grade in the course will be at most a B+.To receive full points (and avoid the letter grade limit), both of the following must be true:
- You do not miss more than three classes. This includes the late policy and leave-early policy below. Excused absences still count as missed classes, this is why we allow you to miss three! If you have an exceptional circumstance in which 1) all of your absences are excused, and 2) you miss more than three classes, we will address the issue at that point.
- You have no unexcused absences during the third week of a unit These combined courses are the most critical components of the course. We want you there.
Late Policy
We understand that sometimes it might be hard to get to class on time but if you are more than three (3) minutes late, you will be considered late to the class. Two lates will be counted as one absence.
Leave Early Policy
If you just leave the class before it ends, then you will lose the attendance for that day as well.
Bring an Internet Connected Device
Please bring a device so that you can connect to the Internet in class since attendance will be on Autolab. During the lecture, we will show you a pass phrase, which you will have to enter into Autolab. Please refrain from sending this information to your friends if they are not in class. Doing so would be considered an academic integrity violation, which would lead to a failing (F) grade
Unit Midpoint Submissions
Each of the three course units will have a midpoint submission. These are team submissions (the same team as your projects without your partner from Rage). The first two unit midpoint submissions are worth $7\%$ of your grade while the 3rd one is worth $9\%$ of your grade. For details, please see the Unit Midpoint Submissions page.
Bonus
In addition to the bonus opportunities mentioned above, there will be other explicit opportunities to get more bonus points (e.g. your groups could present your project on the CSE Demo day on the last Friday of the semester). The list of the bonus opportunities will be listed on the Bonus page (though it is possible that we might forget to put something on the page even after we announced it in class– if so please send us a reminder!).
You can accumulate up to 500 bonus points. As mentioned above, these $500$ bonus points will translate into $5\%$ of your grade.
Accessibility Resources
If you have a diagnosed disability (physical, learning, or psychological) that will make it difficult for you to carry out the course work as outlined, or that requires accommodations such as recruiting note-takers, readers, or extended time on exams or assignments, you must consult with Accessibility Resources (: 60 Capen Hall, </a>: 645-2608, TTY: 645-2616, : 645-3116).
You must advise your instructor during the first two weeks of the course so that we may review possible arrangements for reasonable accommodations.
Critical Campus Resources
Sexual Violence
UB is committed to providing a safe learning environment free of all forms of discrimination and sexual harassment, including sexual assault, domestic and dating violence and stalking. If you have experienced gender-based violence (intimate partner violence, attempted or completed sexual assault, harassment, coercion, stalking, etc.), UB has resources to help. This includes academic accommodations, health and counseling services, housing accommodations, helping with legal protective orders, and assistance with reporting the incident to police or other UB officials if you so choose. Please contact UB’s Title IX Coordinator at 716-645-2266 for more information. For confidential assistance, you may also contact a Crisis Services Campus Advocate at 716-796-4399.
Mental Health
As a student you may experience a range of issues that can cause barriers to learning or reduce your ability to participate in daily activities. These might include strained relationships, anxiety, high levels of stress, alcohol/drug problems, feeling down, health concerns, or unwanted sexual experiences. Counseling, Health Services, and Health Promotion are here to help with these or other issues you may experience. You can learn more about these programs and services by contacting:
Counseling Services
120 Richmond Quad (North Campus), 716-645-2720
Health Services
4350 Maple Road (at Sweet Home Rd.) , 716-829-3316
Health Promotion
114 Student Union (North Campus), 716-645-2837
Preferred Name
If you would like to be addressed by a name that is different from the one in UB records, please let us know and we will use your preferred name in our communications with you. Further, you will be able to use your preferred name in all of your submissions.
Diversity
The UB School of Engineering and Applied Sciences considers the diversity of its students, faculty, and staff to be a strength, critical to our success. We are committed to providing a safe space and a culture of mutual respect and inclusiveness for all. We believe a community of faculty, students, and staff who bring diverse life experiences and perspectives leads to a superior working environment, and we welcome differences in race, ethnicity, gender, age, religion, language, intellectual and physical ability, sexual orientation, gender identity, socioeconomic status, and veteran status.
Suggestions or Comments?
We would be happy to get feedback from you. You can either talk/send email to Kenny and/or Atri, or use piazza .