Engaging undergraduate students in the study of ethics and technology is an important and difficult task for both computer science programs and individual instructors. Narratives, especially science fiction, have become a popular way to entice students to deeply engage with ethics topics. We detail experiences across six different institutions of implementing full-semester, part-semester, and single-lecture lessons from the recently-published book Computing and Technology Ethics: Engaging through Science Fiction. We provide an overview of both the book and related instructor materials; explaining how they can be used to effectively teach topics in ethics to undergraduate students in computing and technology development courses. We close by reflecting on how the book was received by students, and general suggestions for implementing ethics education across a range of institutional contexts.

This panel will help CS-trained educators who are teaching students about how to approach their work with an ethical mindset by discussing one of the key challenges in CS ethics education: how to manage authority in a classroom that focuses on values and ethics. Many CS instructors are wary of teaching either a dedicated ethics course or embedding responsible computing concepts and practices into their core CS courses because they feel that they lack disciplinary authority, or are even unsure of what precise teaching outcomes to aim for. These concerns are real: ethical reasoning is not the same type of skill set as is required in design or engineering work; it is a set of practices rooted in a person's beliefs, judgments, decisions, and values and it is necessarily personal for anyone who takes it seriously. Effective ethics course pedagogy and content are primarily about developing the students' capacity for reflection and inquiry, not transmitting knowledge. In an ethical reasoning focused learning environment, the majority of the work is persuading students that they can and should keep caring and thinking about the impact of their work beyond the classroom: in other words, the students must feel responsible for the reasoning and choices they make that will impact the lives of others. Through a discussion with multiple CS ethics educators, this panel will offer practical approaches to managing authority in this type of classroom as well as suggestions for engaging and empowering students to be curious and reflective about their own values and ethical positions.

This workshop will introduce participants interested in teaching a full-term computer science ethics course to the tools and techniques of using science fiction to teach that course. The workshop will consist of three hourlong parts, each of which will draw heavily on science fiction as a teaching tool: (1) an introduction to and tips for teaching with multiple ethical frameworks including virtue ethics, deontology, communitarianism, and utilitarianism; (2) A deep dive on teaching about personhood and privacy by focusing on what's at stake, using multiple viewpoints; and (3) an overview and interactive workshop on the practical logistics of teaching a full term ethics course including example syllabi and teaching materials. This course will equip participants to make rich use of science fiction in their course and to incorporate multiple ethical perspectives into classroom discussion. Participants will have an opportunity to work on course structure and teaching modules in small groups and will receive example teaching materials.

Responsible Computer Science (RCS) requires that students experience aspects of RCS in just about every CS course they take. It must be embedded across the curriculum, and it is the responsibility of all CS faculty to be part of the delivery of RCS. The purpose of this panel is to expand the community of practice around delivering RCS, so that students better understand how the integration of computing-related technologies into our daily lives has shifted the kinds of power and reach they have, both as individuals and in collective groups. Thus, we welcome those educators who are hesitant or are uncertain about adopting RCS into their teaching. To ease this adoption, we understand responsible computer science as broadly as possible and use it as an umbrella term that includes computing ethics, professionalism, computing for good, inclusive computing, diversity and inclusion in CS, security, safety, and computing for justice, just to name a few. The panelists, who have been collaborating on a project as part of the Mozilla Foundation Responsible CS project, will address concerns faculty have when incorporating RCS in their teaching, challenges faced when encouraging involvement of more CS faculty in the teaching of RCS, the value and need for interdisciplinary collaboration, and the value of grounding (or not) the delivery of some modules in ethical theories. Panelists will offer suggestions for moving toward a CS curriculum that embeds RCS modules and address issues that audience members raise.

This special session furthers the work associated with SIGCSE Reads and the growing community of SIGCSE members who connect to each other through science fiction. This session extends the experiences of earlier sessions by incorporating a new ethical framework, capability ethics, that supports analysis at a societal level rather than a personal level. Updated materials will be available so that the exercise can be translated to other classrooms. Building on an initial description of ethical frameworks and how they have been used with earlier SIGCSE Reads stories, the exercise will be followed by discussion about new stories that provide additional challenges to both teachers and students, with the goal of better preparing students to consider their computing degrees and careers in a pluralistic, global, equitable and just context.

The inclusion of computing ethics and social impact curricula in computer science programs has received increasing attention in research and teaching. While students explicitly interested in the topic may choose to take courses designed only to teach ethical thinking in computer science, we have a societal need to "teach ethics" in a wider variety of computing courses. With the powerful tools that we give students comes responsibility, and students should know how to consider ethical implications of the things they build. The difficulty of developing strategies to "teach ethics" in computing courses is that 1) teaching computing ethics is different than teaching other computational courses, requiring more than the simple transmission of information or knowledge 2) we lack a way to assess the efficacy of the strategies we use to accomplish the "more." We aim to foster a discussion on the current research and instructional approaches, led by researchers who are actively teaching responsible computer science and data science in a variety of institutional settings (e.g., private, public, small, large, etc.). In addition to forming new research and teaching collaborations, we hope this discussion will inspire the larger community of computer science educators to embed computing ethics and social impact in their technical courses.

There is little research on why underrepresented minorities are less likely to specifically study Machine Learning and Artificial Intelligence (ML/AI). We surveyed 159 undergraduate students about their interest in, exposure to, and personal views on ML/AI in order to explore variations in responses by self-reported gender and race/ethnicity groups. We found that students underrepresented by race/ethnicity are ~6 times less likely to take a traditional ML/AI course than those not underrepresented by race/ethnicity, but no significant difference was found between gender representation. Additionally, students underrepresented by race/ethnicity are more likely to report interest in social, cultural, and political impacts of ML/AI rather than the more technical aspects of ML/AI itself, which is a prevalent interest of students not underrepresented by race/ethnicity. We explore potential reasoning for this difference through further analysis of their survey responses. Encouragingly, we find that regardless of representational status 72.0% of students who report lack of interest in a traditional introductory course are interested in a ML/AI course that focuses more on the political, philosophical, and ethical issues raised by ML/AI and its impacts on society. Our findings suggest that a 'CS Principles" style introductory ML/AI course, emphasizing social and political impacts, could be an effective way to promote diversity in ML/AI.

As is evidenced by the associated AI, Ethics and Society conference, we now take as given the need for ethics education in the AI and general CS curricula. The anticipated surge in AI ethics education will force the field to reckon with delineating and then evaluating learner outcomes to determine what is working and improve what is not. We argue for a more descriptive than normative focus of this ethics education, and propose the development of assessments that can measure descriptive ethical thinking about AI. Such an assessment tool for measuring ethical reasoning capacity in CS contexts must be designed to produce reliable scores for which there is established validity evidence concerning their interpretation and use.

The national push for CS departments to teach students to think about ethical implications of their work raises critical questions about how we approach this pedagogically. In contrast to the typical assessments of CS ethical thinking, which have focused on a student's ability to operate successfully within one kind of normative paradigm, our research group advocates for teaching ethics as an ongoing practice that incorporates multiple normative frameworks and an emphasis on the descriptive element of ethical reflection. In this special session, we will discuss the differences between normative and descriptive ethics, practice describing ethical dilemmas, and work together on developing assessment capabilities for descriptive ethical thinking for CS.

We draw on concepts in medical ethics to consider how computer science, and AI in particular, can develop critical tools for thinking concretely about technology's impact on the wellbeing of the people who use it. We focus on patient autonomy---the ability to set the terms of one's encounter with medicine---and on the mediating concepts of informed consent and decisional capacity, which enable doctors to honor patients' autonomy in messy and non-ideal circumstances. This comparative study is organized around a fictional case study of a heart patient with cardiac implants. Using this case study, we identify points of overlap and of difference between medical ethics and technology ethics, and leverage a discussion of that intertwined scenario to offer initial practical suggestions about how we can adapt the concepts of decisional capacity and informed consent to the discussion of technology design.

We argue that it is crucial to the future of AI that our students be trained in multiple complementary modes of ethical reasoning, so that they may make ethical design and implementation choices, ethical career decisions, and that their software will be programmed to take into account the complexities of acting ethically in the world.