Goals and Expectations#
Goals#
Our goal is that at the end of this course, you will be able to:
Formalize assumptions about an observed data-set into a probabilistic model.
Perform statistical inference for statistical models in a probabilistic programming language.
Evaluate models in the context of their downstream task by relating human-useful properties to metrics (and understanding their strengths/shortcomings).
Abstractly reason/intuit about properties of models and different types of inference methods.
Evaluate ML systems in their sociotechnical context.
Apply critical lenses to the development and applications of current ML systems.
What You Should Know About the Course Staff#
We’re here because we care about your experiences as students and as individuals. So what does that mean? It means that…
We want you to come to our office hours. We want to get to know you all, both in the context of the class and as individuals; we want to know what you find most challenging and what you find most rewarding in the class and in the CS program. Come chat with us!
We want to see you even more when you’re struggling, lost, or down. You may be surprised to know that as course staff, we still vividly remember our struggle learning the material covered by this course. We recognize that there are “constructive” types of struggle—struggle that builds you up and helps you grow—as well as “destructive” types of struggle—struggle that tears you down, that leads you to question your self-worth, and that makes you want to give up. When things get hard, the worst thing you can do is isolate yourself, and the best thing you can do is to come talk to us. Together, we can celebrate your growth and productively overcome the setbacks.
We have high expectations for you to be thoughtful and engaged. We expect you to be thoughtful in your engagement with the course materials and in your interaction with your peers. Substantial amounts of research have shown that Computer Science programs can create cultures of isolation and impostorism, in which students feel judged for common struggles many experience, instead of coming together to support one another. We ask you to be thoughtful in how you validate your peer’s identities and create a safe and supportive space for everyone.
We want you to find meaning in the course, and we want you to succeed. As in the liberal arts tradition, in addition to providing you with practical skills, we want this course to offer you new lenses with which to engage with the world; we want this course to be personally meaningful to you, to shape the way you think and engage with societal issues you see around you.
We designed this course especially for the Wellesley context. We therefore designed the course based on several guiding principles.
Math, statistics, and computer science can all be intimidating, and they shouldn’t be. In fact, in recent years, math anxiety has gained attention as a phenomenon that needs to be understood and addressed in STEM education. It is important for us to challenge exclusionary definitions of what science is and who can practice it to create a supportive space for learning. None of these subjects require inborn abilities to succeed. We will therefore normalize the (very normal) struggles of learning this material in class.
Math, statistics, and computer science were invented by humans and are therefore shaped by human values. We encourage you to question all course content, its history, its implicit values, its benefit to society, and more. We will create dedicated time and space for doing exactly this.
We tend to remember things we experience. We believe people learn best by hands on practice, and by trial and error. We have therefore designed the class to be interactive. Further, we believe that knowledge is best learned with peers in societally meaningful contexts; we therefore incorporate lots of opportunities to engage with your peers in the class and to think about the techniques we introduce in a real-like context.
All math and theory we introduce will be practically useful. We designed the course so it is always clear why math/theory is introduced, and how it is practically relevant.
We want to know about your experience in the course. We always strive to improve the course for future generations of students. We therefore value your feedback.
Classroom Environment#
Diversity, Equity, and Inclusion (DEI): It is the mission of the teaching staff that students from all diverse backgrounds and perspectives be well served by this course, that students’ learning needs be addressed both in and out of class, and that the diversity that students bring to this class be viewed as a resource, strength, and benefit. We aim to create a learning environment that is inclusive and respectful of diversity: gender, sexuality, disability, age, socioeconomic status, ethnicity, race, and culture. Your suggestions for how to better our classroom community are always encouraged and appreciated.
Since a large part of this course requires students to work in groups, in alignment with our teaching mission, we ask that students explicitly reflect on and implement practices for building teams that are diverse along many axes. The teaching staff is happy to help you brainstorm how to create an inclusive and productive working culture for your team.
Mental Health: We value your mental health more than anything else. If you’re finding yourself facing mental health challenges, please come talk to us. As instructors, we have had our own fair share of mental health challenges. We are happy to help you find the support you need, whether on- or off-campus—our door is always open!
How to Succeed in CS 349?#
Come to class and participate. While thorough, the course materials is not a substitute for the classroom experience. We expect you to attend all classroom sessions (class is mandatory), and engage with the lecture components and with your peers in the in-class exercises.
Attending office hours is an expected and normal part of the learning experience. Moreover, office hours are an opportunity for you to take ownership of your own learning experience—to ask questions you that will help you better understand the material, connect it to topics you personally care about, etc. We expect to see you at office hours regularly, asking questions, engaging with the materials, and supporting your peers.
Embrace confusion. Confusion may be uncomfortable; it may cause us to doubt whether we have the skills necessary to make it through the course. It is, therefore, our mission to help you find ways to embrace confusion productively, because without it, there’s no learning.
Experiment and tinker. Learning requires that you form your own mental model of the material and your own intuition for how things work. One effective way to do this is through play—if you’re not sure what would happen if you tweak a piece of code, a parameter of an ML model, etc. try it!
Stay on top of the material. You will be given class time to start working on homework together with your peers. This is to ensure everyone can find their bearing—if there’s something that confuses you, this is a great time to ask! We recommend you finish working on the problems you started in class before the next class. Since every class builds on all previous classes, this will ensure you’re up to speed.
Ready to take CS 349? Fasten your seatbelts—it’s going to be an adventure!
Community Guidelines for Ethics Discussions#
Content Warnings. Some of the readings assigned in the ethics chapters use dated language and/or explicitly refer to racist, sexist language to justify white supremacy. We have labeled such readings with “content warnings.” If you anticipate any challenges with engaging with these readings, no problem—please reach out to the instructor so we can come up with a plan together. And if you ever feel like an additional content warning is needed, please don’t hesitate to let us know.
The Use of Problematic Language. Even when the readings use problematic language and terms, please don’t use such language yourself in class, even when referencing the readings or reading from them aloud. For example, if the “f-word” appears, just say “f-word” instead. Even though we can’t change the texts, we can still try to maintain an inclusive atmosphere for productive engagement with historical and current ethical issues in ML.
A Space for Growth. Each one of us comes from a different background, has different identities, and different lived experiences. It’s therefore important that we provide everyone with the benefit of the doubt, and to be generous to those who are thinking about these ideas for the first time. By this, we mean that we do not “call out” or “cancel” anyone; doing so deprives us of the opportunity to grow and build strong, resilient, and supportive communities that are capable of navigating multifaceted issues. Instead, let’s “call in:” invite others to understand our own perspectives, and strive to understand theirs. To do this, we can:
Ask. Instead of making assumptions about what someone else meant, why they might think a certain way, etc., we can ask them what they meant to say, and what led them to think this way. We can listen actively and try to summarize what they said to see if we understand.
Clarify. To ensure we don’t come across as if speaking for others, we can center our perspectives in our own experiences with language. For example, we can use “I” statements, and reference experiences/identities that we see as having shaped our perspectives. In doing this, we help others clarify where our perspectives come from.
Challenge. We may encounter ideas that challenge our values and current ways of thinking. It’s important that each of us approaches the material with an open mind and a willingness to consider new lenses. Similarly, when interacting with others, we can respectively challenge their ideas, but not their personhood. We are all bound to make mistakes, and it’s important we can constructively move forward.
Give Space. Thinking aloud is welcomed (and encouraged). Let’s give everyone the space they need to process.
Take Space. If you need to take a pause, feel free to step out—no need to ask for permission.
Your Feedback Matters to Us#
We deeply care about your experience in the course and therefore value your feedback. There are several ways to provide us with feedback:
Come talk to us! We know that no course caters perfectly for all students’ learning styles; we will therefore not be offended if something isn’t working for you. And if there’s something we can do to improve your experience, we’d love to know about it!
You can also provide us feedback via this anonymous form.
Lastly, we collect anonymous feedback from all students mid-way through the semester.
Acknowledgements#
This page draws on CS 240’s syllabus, and Evan Peck’s What I want you to know about me as your professor. The community guidlines for ethics discussions draw on those written by Professor Tavi Gonzalez.