The rapid evolution of artificial intelligence technologies, with the corresponding impact on human well-being, calls for an increase in ethical awareness to influence the computer science students who will be creating the future.Interdisciplinary teams of scholars are attempting to build frameworks for explaining appropriate ethical considerations for responsible computing.Although professional computing codes of ethics are intended for managing ethical dilemmas in computing, there are no single fixed solutions to all possible challenges which computer scientists face in their professional work.The use of narratives is one way to engage computer science (CS) students as they explore the ethical implications of their work and critically examine the implications of decisions that are made as part of professional practice.This experience report shares the story of a team of faculty (Computer Science and Applied Philosophy) working to integrate computing ethics into their undergraduate CS programs in different instructional contexts; a liberal arts college in the USA and a technology and research university in Nigeria.This collaborative work in progress shares examples of modules and assessments refined over time based on evolving student interests and curriculum needs that are responsive to rapid advances in computing technologies.Contributions of this report include: 1) documentation of the origins of this interdisciplinary partnership, 2) a rationale for a narrative-based approach for fostering responsible computing principles and practices, and 3) preliminary data the impact of this approach within international computing environments.

While there is no replacement for the learned expertise, devotion, and social benefits of a guide dog, there are scenarios in which a robot navigation assistant could be helpful for individuals with blindness or low vision (BLV). This case study investigated the potential for an industrial quadruped robot to perform guided navigation tasks based on a co-design model. The research was informed by a guide dog handler with over 30 years of experience of non-visual navigation. In order to communicate spatial information between the human-robot team, two interface prototypes were created and pilot tested: a voice-based app and a flexible, responsive guide handle. The pilot user study consisted of sighted participants and our BLV co-designer, who completed simple navigation tasks and a post-study survey about the prototype functionality and their trust in the robot. All participants successfully completed the navigation tasks and demonstrated that the interface prototypes were able to pass spatial information between the human and the robot. Findings of this exploratory study will help to inform human-robot teaming and collaboration. Future work will include expanding the voice-based app to allow the robot to directly communicate obstacles to the handler, adding haptic navigation signals to the handle design, and expanding the user study to include a larger sample of experienced guide dog handlers.

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.

We want to facilitate an interactive gathering of faculty from a variety of disciplines and institutions - including primary, secondary, and tertiary schools - who are interested in exchanging ideas related to the learning and teaching of ethical concepts and skills in a CS or related curriculum, and evaluating the success of those efforts. We understand "curriculum" broadly to include both course and lab instruction and out-of-class experiences. Participants will leave with a set of open-access teaching resources, guidance for how best to use those resources at their own institutions, and ideas for evaluating any courses, curriculum, or programs they develop as a result.

Data representations continue to be produced in predominantly visual forms within STEM disciplines. The disparity in access to these graphical representations between students who are blind or have low vision (BLV) and their sighted peers is exacerbated as the adoption of digital screens become more prevalent in educational settings. Standard accessibility solutions rely heavily on natural language processing, e.g., screen readers, for non-visual information access. But can other non-visual modalities, like touch, be effective for learning graphical content rendered on touchscreens? To investigate this question, we conducted a user study with a multimodal touchscreen learning system to assess the effectiveness of two non-visual graphical presentation modalities: 1) a vibro-audio condition, which used the device's embedded vibration motor plus an auditory content overview (a spatial and multimodal technique), and 2) a natural language condition that provided a complete description of the content (a cognitively mediated technique). BLV participants (N = 19) were presented with the learning system and asked to answer multiple-choice questions about three different graph types using both presentation modalities. Findings showed that the two presentation modalities were functionally equivalent for learning the graphical information presented, suggesting that for these stimuli, the presentation modality did not have a significant effect on participant graph learning accuracy. However, the type of graph being learned did have a reliable effect. Moreover, a majority of the participants stated a preference towards the natural language condition and, on average, learned graphs faster than with the vibro-audio condition. The similarity found between the two learning modalities is interpreted as supporting user learning preferences while providing redundancy in the information being communicated. This approach layers the various types of information found in graphical representations (text, numerical, spatial) for individuals with accessible learning needs, providing more control, independence, and responsive tools to optimize their own educational materials.

Recent news and national reports have significantly increased interest in new approaches for teaching responsible computing to help students understand, evaluate, and address the social impact of existing and emerging computing technologies. This 3-hour workshop will be offered in two workshop format sessions: in-person and online. The first part of each session will introduce responsible computing and its connections to RESPECT and Cultural Competence in Computing (3C). Next, we will provide a short overview of our own work in teaching responsible computing along with frameworks, tools, and best practices. We will showcase four different approaches to teaching responsible computing across institutional settings (high school, college, university), interdisciplinary partnerships (computing, philosophy, STS, digital humanities), and instructional formats (dedicated courses, embedded lessons, design challenges, bootcamps). The workshop presentations will focus on practical advice about how to get started, available resources, securing support from administration and colleagues, and other considerations for this work. In the second half of the workshop, participants will work in small groups to co-design potential lessons based on shared topical interests, institutional settings, and/or learning objectives. Facilitators will provide guidance, recommendations, and classroom examples to help the small groups to complete draft lessons that will be disseminated among workshop participants and on the workshop website. A laptop or internet connected device is needed to participate in the small group activity. Handouts/materials will be provided on the workshop website.

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.

With the sudden shift to online learning during the global pandemic, there is an increased interest in earth science virtual field trips (VTFs). This work in progress poster describes a project to increase diversity and information access to introductory geology training through physically accessible VTFs. The pilot study investigates the effectiveness of an undergraduate introductory geology VFT in meeting the same real-world lab learning objectives in both desktop and immersive virtual formats.

The prevention of criminal activity has changed dramatically over the past two decades, largely due to the increased reliance on systems that provide crime data analysis. Created specifically for police, judicial sentencing, and prison applications, these systems conduct both predictive and retrospective analysis to aid decision making within the criminal justice system. Furthermore, these software platforms typically combine spatial informatics packages and advanced statistical features behind user-friendly interfaces. Recent studies have demonstrated problems with both the flawed logic within these systems' algorithms and the inherent biases in the underlying data. In this paper, we present a novel repository of computing ethics teaching modules across a variety of narrative areas. These modules and curated narratives help faculty to establish 'ethical laboratories' that can guide computer science students in improving their ethical reasoning skills as it relates to the creation of current and future technologies. First, we provide an overview of the Computing Ethics Narratives (CEN) project, its narrative repository and the module framework through a sample module on predictive policing algorithms. Furthermore, we share preliminary findings from a pilot of this module, which was implemented in an intermediate algorithms course. The preliminary student and faculty feedback suggest the predictive policing module was able to help students contextualize the ethical issues around the topic, however, students recommended devoting more class time to evaluating the technical complexities of these critical systems.

How do you design more responsible computing technologies? You start by training computer science (CS) students, the creators of tomorrow's tech, to think critically about their own action and responsibilities from the first day of their introductory programing course. The standard approach to the CS1 level curriculum needs evolve to make room for ethics instruction presenting students with difficult questions, provocative simulations, and time for personal reflection about ethics and the professional responsibilities of current and future computer scientists, software engineers and other technologists. This poster describes curriculum development work from the Computing Ethics Narratives (CEN) conducted by CS students and faculty engaged in critical thinking about ethical issues related to computing and technological innovation and its widespread influence on individuals and society. The presentation will provide examples of three computing ethics modules that have been piloted into CS1 and CS 2 level courses in both online and in-person settings. Early results of the pilot study are shared along with future work.

With the 2018 revision of the ACM Code of Ethics and Professional Conduct, there is a growing interest in how computer science faculty can integrate these principles into the education of future practitioners. This special session illustrates one approach by highlighting assignments that blend ethics and technology. These assignments can be used in a variety of courses, including CS1, CS2, and later courses. Presenters will provide an overview of each assignment and gather feedback from the audience. All materials, including descriptions, starter files, and guidelines for instructors, will be published at https://ethics.acm.org/SIGCSE2020.

It is not just K-12 students that have misconceptions about computer science. Undergraduate students entering into a post-secondary computer science major also have significant misconceptions about what a computer scientist actually does on a day-to-day basis, even at the end of their four-year undergraduate computer science program. While the Draw-A-Scientist Test (DAST) investigates student perceptions of scientists in general (Chambers, 1983) and the Draw-An- Engineer Test (DAET) examines student perceptions of engineers (Knight and Cunningham, 2004), there have been few adaptations investigating student perceptions of computer scientists (Martin, 2004). Based on previous research, our study assessed undergraduate computer science student perceptions of computer scientists at both a mid-size research university and a small liberal arts college. Students (n=120) were asked to describe computer scientists in both a visual format and a written format using an adaptation of the DAST. The authors share comparative results for computer science students (pre-test, post-test) perceptions when 1) exposed to an intentional but not explicit curriculum with diverse representation of computer scientist images and a broad range of computer science research areas, and 2) exposed to a regular curriculum without intentional messages about the diversity of computer scientists and the diversity of research areas within the discipline. The poster describes additional scoring measures introduced beyond those in previous instruments which help to better categorize and interpret perceptions of computer science students about their own discipline.