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Enterprise AI Analysis: Ethical Computing Education in the Age of Generative AI

Enterprise AI Analysis

Ethical Computing Education in the Age of Generative AI

Grace Barkhuff

Georgia Institute of Technology, Atlanta, Georgia, USA

grace.barkhuff@gatech.edu

Abstract: Educating computing students in ethical practices is challenging and vitally important. This goal is newly complicated by the rapid rise of generative AI (GenAI) and its use in higher education by students and instructors alike. Computing ethics education provides a unique opportunity for students and instructors to consider the ethical implications of GenAI. Through my research, I aim to understand the perspectives computing educators have toward ethical computing education, including their perspectives on computing ethics education generally, their perspectives on using GenAI as a teaching tool, and finally computing ethics educators' perspectives on integrating GenAI in the computing curriculum.

Key Insights at a Glance

This research highlights the critical importance of computing ethics education and the emerging role of generative AI. Here are the core findings that inform our approach to ethical AI integration.

57.1% Undergrad Ethics Support (Pre-GenAI)
72.2% Master's Ethics Requirement Support
~99% CS TAs Value Ethics in Curriculum

Deep Analysis & Enterprise Applications

Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.

1 Motivation, Literature Review, & Key Ideas

Computing ethics education (CEE), the instruction about computing's societal impact, is a critical component of the undergraduate computing curriculum. As such, it is substantially included in the updated ACM / IEEE-CS / AAAI Computer Science Curricula 2023 not only in its own section, but across every knowledge area [9]. Research into the most effective way to teach this content has increased in recent years, additionally indicating its importance to the CS Education research community [7].

At the same time, society is facing the rapid rise of generative AI (GenAI), which poses ethical questions both within the classroom and outside it. From a pedagogical perspective, the swift introduction of GenAI has led some computing instructors to consider how to prevent prohibited student use of the tool (i.e. [14, 15]) and others trying to figure out how to meaningfully incorporate it into courses (i.e. [8, 12]). Some have pointed out ethical concerns of incorporating GenAI in the classroom [6]. Outside the classroom, there is concern about the ethical implications of GenAI on society in general, such as copyright infringement on the data used to train GenAI models and the models' environmental impact [12].

CEE, whether in a standalone course or integrated into other courses [1], provides a unique opportunity to educate students on and encourage critical thinking about the societal impacts of GenAI. While doing so, CEE educators should consider their own policies regarding use of AI in their courses, both for their students and for themselves. Instructors could, for example, provide students with an AI-based "personal tutor" [11], use GenAI to assist the instructional team with grading [13], or ask students to critique GenAI sample responses to an assignment [10].

My research aims to understand how higher education computing programs can educate computing students both about computing ethics and in an ethical manner, with a focus on the impact GenAI has on this goal. Through my dissertation, I plan to explore the following research questions: (1) How do educators perceive the importance of CEE?, (2) How might we ethically use GenAI as a teaching tool in computing education, broadly speaking?, and (3) What unique perspective do CEE educators provide toward the use of GenAI in computing courses?

CCS Concepts

  • Social and professional topics → Computing profession.

Keywords

  • Computing ethics education, CS ethics, Computing education, AI, GenAI, generative AI, ChatGPT

2 Research Approach and Progress

I use a mixed-methods approach to research, including surveys, research through design (RtD), and interview studies.

My early research works to understand how educators perceive CEE, which provides a basis for discussing the importance of CEE as a central topic in the computing curriculum. I studied the opinions of undergraduate computing educators, computing teaching assistants (CTAs), and administrators for master's computing programs through a series of surveys. All surveys showed a strong support for CEE. In my survey of U.S.-based undergraduate computing educators, 57.1% (n=153) of those surveyed stated that ethics should be included in the undergraduate curriculum in both standalone and integrated formats. Importantly, this survey was conducted largely before GenAI became commonplace in higher education contexts, providing a snapshot of educators' perceptions of CEE before GenAI and an opportunity for comparison to the groups' perceptions today [2]. A survey of master's level computing program administrators found that 72.2% (n=52) of those surveyed agrees ethics should be required at the master's level [5]. And, in a survey of CS TAs, all but one TA respondent felt that ethics is an important topic in the computing curriculum [3].

Through my ongoing work, I seek to understand CTAs' perceptions on AI and the role it could play as a teaching tool. CTAs' perspectives are notable due to their dual role as both students and educators, thereby understanding some of the challenges and benefits for both stakeholders. Thus far, we have found that CTAs are highly invested in the "humanistic" elements of their job, such as inspiring students directly [4]. Following these findings, my work in progress includes speculative design workshops with CTAs, asking them to consider how they might use GenAI as a teaching tool to give them more time to focus on those "human" elements of their role and what ethical concerns doing so may pose.

Future work may focus on the unique perspective CEE educators have at the intersection of computing and ethics education. I want to understand their perspective on GenAI tools in higher education, including how to use it as a teaching tool, how to educate computing students about the ethical implications of the tool, and how the introduction of GenAI tools to higher education may impact the importance of CEE. I plan to do so first through a survey, to understand how perspectives on CEE may have changed since the data in my early work ([2]) was collected, then through a series of design workshops where CEE educators will create sample syllabi and modules relating to the ethics of GenAI. Through the doctoral consortium, I hope to receive feedback on the research direction of this phase.

Research Methodology Overview

Surveys
Research through Design (RtD)
Interview Studies
~3RQ Primary Research Questions Guiding the Dissertation

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