Responsible AI Research Needs Impact Statements Too

All types of research, development, and policy work can have unintended, adverse consequences - work in responsible artificial intelligence (RAI), ethical AI, or ethics in AI is no exception

Thought crimes and profanities whilst programming

Where should we draw the line of inappropriate conduct on a course that is given freely to anyone? If an individual starts profusely swearing on a lecture, they are most likely expelled from the class or even from the course. But what if they do it outside the lecture amongst their classmates, amongst a group of anonymous individuals - or by themselves? In this article, we study how students use profanities in source code when they are completing programming assignments on a massive open online course (MOOC). We examine how common it is to curse in source code as well as whether specific assignments incite more cursing than others. Additionally, we investigate differences between participants with regards to cursing. Our results indicate that a considerable amount of participants write curse words whilst programming, but most clean their code for the final submission. The data also shows that there are different degrees of profanity in use, ranging from quite inoffensive words to offensive racial slurs. Finally, we discuss options that one may take when individuals who swear are identified, starting from rescinding their right to study.Peer reviewe

Experiential AI: A transdisciplinary framework for legibility and agency in AI

Experiential AI is presented as a research agenda in which scientists and artists come together to investigate the entanglements between humans and machines, and an approach to human-machine learning and development where knowledge is created through the transformation of experience. The paper discusses advances and limitations in the field of explainable AI; the contribution the arts can offer to address those limitations; and methods to bring creative practice together with emerging technology to create rich experiences that shed light on novel socio-technical systems, changing the way that publics, scientists and practitioners think about AI.Comment: 10 pages, 3 appendice

Deconstructing the Veneer of Simplicity: Co-Designing Introductory Generative AI Workshops with Local Entrepreneurs

Generative AI platforms and features are permeating many aspects of work. Entrepreneurs from lean economies in particular are well positioned to outsource tasks to generative AI given limited resources. In this paper, we work to address a growing disparity in use of these technologies by building on a four-year partnership with a local entrepreneurial hub dedicated to equity in tech and entrepreneurship. Together, we co-designed an interactive workshops series aimed to onboard local entrepreneurs to generative AI platforms. Alongside four community-driven and iterative workshops with entrepreneurs across five months, we conducted interviews with 15 local entrepreneurs and community providers. We detail the importance of communal and supportive exposure to generative AI tools for local entrepreneurs, scaffolding actionable use (and supporting non-use), demystifying generative AI technologies by emphasizing entrepreneurial power, while simultaneously deconstructing the veneer of simplicity to address the many operational skills needed for successful application

Conceptualizing Approaches to Critical Computing Education: Inquiry, Design and Reimagination

As several critical issues in computing such as algorithmic bias, discriminatory practices, and techno-solutionism have become more visible, numerous efforts are being proposed to integrate criticality in K-16 computing education. Yet, how exactly these efforts address criticality and translate it into classroom practice is not clear. In this conceptual paper, we first historicize how current efforts in critical computing education draw on previous work which has promoted learner empowerment through critical analysis and production. We then identify three emergent approaches: (1) inquiry, (2) design and (3) reimagination that build on and expand these critical traditions in computing education. Finally, we discuss how these approaches highlight issues to be addressed and provide directions for further computing education research

Understanding Ethical Concerns in the Design, Application, and Documentation of Learning Analytics in Post-secondary Education

University of Minnesota Ph.D. dissertation. August 2015. Major: Rhetoric and Scientific and Technical Communication. Advisor: Ann Hill Duin. 1 computer file (PDF); ix, 138 pages.The practice of predicting a student's level of success in order to provide targeted assistance, termed "learning analytics,"� emerged from a well-established business intelligence model popularly called "Big Data"�. The ethical impact of Big Data on business practices has been undeniable, however, the ethical concerns of Big Data methodology in academia have yet to be explored, as research in this emerging discipline is relatively new. Thus, the overarching question for this study is as follows: How can we use rhetorical, scientific, and technical communication perspectives to understand ethical concerns in the design, application, and documentation of learning analytics in post-secondary education? To investigate this question, I conducted a five-stage study using a cross-disciplinary perspective based on existing frameworks in rhetoric and scientific and technical communication, united by their ethical lens, from genre, persuasion, human-computer interaction, social power, semiotics, visual design, new media literacy, and pedagogy to create a matrix for understanding ethical concerns in learning analytics in post-secondary education. During this study, the inability of students to provide input into the learning analytics process was the concern most often revealed, followed by a lack of context for interpreting the data by both institutional users and students, and the potential inaccuracies in the predictive model caused by inaccurate or incomplete data. Secondary concerns included an undefined institutional responsibility to act on data, which could put the institution at risk for legal action, as well as the possibility for discrimination to occur during the learning analytics process. I provide strategies and responses to address ethical concerns in the design and documentation of learning analytics that should constitute a minimum level of ethical action. This minimal implementation would ensure that students are shown goodwill by the institution (design), and that institutions are properly implementing learning analytics in terms of transparency of process and equality of benefit to the student (documentation). The strategies and responses to address ethical concerns in the application of learning analytics would be more complex for each situation and type of learning analytics used, but should always consider student engagement and success as the priority

Understanding the Work of Designated Healthcare Interpreters

Interpreters who work regularly with a deaf health professional are often referred to, in the U.S., as designated healthcare interpreters (DHIs). To date, there have not been any systematic studies that specifically investigate the work of DHIs, yet the number of deaf people pursuing careers in the health professions continues to grow (Zazove et al., 2016), and the number of qualified DHIs to work with these professionals is insufficient (Gallaudet University, 2011). Before educational programming can be effectively developed, we need to know more about the work of DHIs. Using a job analysis approach (Brannick, Levine, & Morgeson, 2007), we surveyed DHIs, asking them to rate the importance and frequency of their job tasks. The results indicated that the following task categories are relatively more important: fosters positive and professional reputation, impression management; demonstrates openness to unpredictability; and builds and maintains long-term relationships with others. Tasks rated as more frequently performed included: dresses appropriately; decides when and what information to share from the environment; uses healthcare-specific knowledge; and demonstrates interpersonal adaptability. We discuss the results of the importance and frequency of the tasks of DHIs and consider the implications for education and future research

Organised lying and professional legitimacy: public relations’ accountability in the disinformation debate

The role of the public relations industry in the disinformation debate has been largely overlooked, while an emphasis has been put on the responsibilities of platforms, media organisations and audiences to monitor content and eliminate fake news. In contrast, this article argues that disinformation and fake news are well-established tools in public relations work and are implicated in the current crisis. Drawing on an exploratory study of UK industry publications about fake news and disinformation, the article shows that public relations has addressed disinformation as a commercial opportunity and a platform for demonstrating professional legitimacy. Industry narratives position professional practice as ethical, trustworthy and true, while simultaneously ‘othering’ dubious practices and normalising ‘organised lying’. The article concludes by arguing that the fight against disinformation must take seriously the impact of public relations, if it is to be effective