|Deep Learning (1470)
How do we think about deep learning algorithms as part of a system? What are the ethical implications of deep learning technologies?
||Lab that reduces gender bias in language models, technology-specific ethics lectures (e.g. deepfakes, facial recognition), written questions for projects
|Computer Science: An Integrated Introudction (CS0170)
||What are the ethical considerations when designing and writing programs?
||In-class turn-and-talk questions presented by Spike (prof. Hughes), homework question about the ACM Code of Ethics
|Computing Foundations: Data (CSCI 0111)
What are some of the ethical implications and societal impacts of computing and data science?
||Readings and short writing assignments about ethical issues surrounding technology, in-class discussions about the readings and other ethical questions, written questions connecting projects to related ethical issues, guest
lectures by experts of data ethics projects
|Intro to Object Oriented Programming (CSCI 0150)
||What are the ethical questions in the field that should be considered when making career decisions?
||Beginning of class ethics news summaries, occurring once every two classes, piazza polls allowing students to express their opinions on ethical issues, mini-assignment questions that challenge students to read articles through an
ethical lens, section activities/discussions that follow up on mini-assignments
|Introduction to Algorithms and Data Structures (CSCI 0160)
||Introduce students to algorithms and data structures within real-world, socially relevant contexts. Promote critical thinking about ethical considerations and algorithmic fairness for all the code they write.
||Projects all have a social premise as well as conceptual ethics questions that ground the assignment within realistic, socially relevant problems. Sections involve discussions and activities surrounding ethical issues. One
homework assignment centered on algorithmic fairness.
|Computing Foundations: Program Organization (CSCI 0112)
||To develop student understanding of how and why ethics relate to what they are learning. Cultivate a mindset where ethics are at the forefront of consideration when coding.
||Changes in assignments to have students think about ethics in design from the perspective of both a student and a designer, additions to lectures to further discuss relevant ethical content, in class activities and discussions
for students to understand why designs may be ethical or unethical
|Creating Modern Web & Mobile Applications (CSCI 1320)
|| Introduce students to several ethical considerations in web and mobile development, paying specific attention to accessibility, privacy, and long-term impact. Give students opportunities to work through technical solutions to
these issues, and encourage students to think critically about design choices and their impact.
|| Readings and written questions about several ethical issues relating to each module in the course, technical requirements (e.g. accessibility required for all projects), written questions connecting projects to related ethical
|Data Science (CSCI 1951A)
|| Bring attention to the role that data science can play in society and facilitate critical engagement with the potentially adverse effects that data science can have in the real world.
|| Articles and short answers about ethical issues in the assignments, ethical component in final project, an ML debiasing lab
|Computer Vision (CSCI 1430)
|| Introduce students to a broad number of ethical issues in Computer Vision, tackling problems such as photo manipulation and dataset limitations. Familiarize students with an awareness of unexpected ethical gray areas, and encourage them to think about them critically.
|| To written part of each project, added ethical questions targeting material relevant to the rest of the project, linking relevant readings. Integrated ethics content into lecture.
|Introduction to Software Engineering (CSCI 0320)
|| Give students an understanding of professional ethics in Computer Science. Arm them with the tools to make decisions rooted in professional ethics over the course of the semester and their careers. Impress upon students that CS is an impactful discipline with the potential to be harmful, and provide them with the tools to analyze their actions in the context of potential harm. Introduce students to best practices for inclusive software engineering.
|| Readings and reflections about ethical issues surrounding technology, in-class discussions about the readings and other ethical questions, integrating inclusive design practices into curriculum, providing students with assignments in which they practice professionalism in industry.
|Introduction to Computer Systems Security (CSCI 1660)
|| Encourage students to consider the broader implications of computer systems security, from the perspective of users, software developers, and policymakers. By covering case studies about legal backdoors to encrypted systems, responsible disclosure, firewalls, and more, we hope to teach students to be mindful of their own security and privacy, as well as the power they hold over others’ security and privacy as computer scientists.
|| Integrated preliminary discussion topics into the lecture slides, as well as written longer questions for each of the six homeworks. These questions ask students to consider recent case studies, how users are impacted, and what the responsibilities of users, developers, and policymakers are in these cases.
|Machine Learning (CSCI 1420)
|| Introduce students to topics and frameworks to approach thinking about ethics in machine learning applications. Emphasize critical thinking of the ethical implications in processing data, writing algorithms, and post model analysis as a fundamental part of the machine learning process. Connect students to resources to learn more about research and applications in machine learning ethics.
|| Readings and responses about the ethical limitations of machine learning models, case studies about ethical issues surrounding machine learning applications, new datasets and projects to illustrate topics like algorithmic fairness in practice.
|Computer Science: An Integrated Introduction (CSCI 0180)
|| Introduce students to the political and social values embedded in technology. Model ways of assessing the social impact of technology in the testing and design stages of development.
|| The class begins with a reading assignment introducing students to the social and ethical questions surrounding code. Written and technical questions connect course projects to related ethical issues. In-class examples draw a connection between algorithms and their social contexts.