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Session Overview
Session
Paper Session 03: The intersection of AI, LIS, and Ethics
Time:
Sunday, 31/Oct/2021:
11:00am - 12:30pm

Session Chair: Dania Bilal, University of Tennessee, Knoxville, USA
Location: Salon J, Lobby Level, Marriott


External Resource:
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Presentations
11:00am - 11:30am
ID: 165 / PS-03: 1
Long Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.
Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.
Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/
Topics: Library and Information Science
Keywords: libraries, surveillance, technology, liberation, critical

The Library/Surveillance Interface

Diana Floegel1, Philip Doty2

1Rutgers, the State University of New Jersey, USA; 2The University of Texas at Austin, USA

Few topics are more often discussed than surveillance, particularly in the context of surveillance technologies that reflect structural inequities. There is space, however, to bring more discussion of surveillance tech into the library literature. At the same time, literature on digital surveillance and associated systems such as Big Data, surveillance capitalism, and platform capitalism often discuss these phenomena as if they are novel rather than iterations of long-standing inequitable circumstances. We propose that a dialogue between surveillance literature and critical library literature will benefit both areas: theories from the surveillance domain can strengthen examinations of structural oppression in libraries while theories from critical library literature can strengthen acknowledgment of surveillance techs’ historical roots. Moreover, overlap exists between concepts used in surveillance and library literature, including concerns about neutrality and classification practices. Therefore, after reviewing surveillance theories and their applicability to libraries, we demonstrate how these scholarly areas may strengthen each other, with three major consequences: (a) moving library literature beyond considerations of the panopticon in favor of the surveillant assemblage; (b) recognizing that surveillance tech is a hyper-visible form of historical oppression; and (c) acknowledging that the library ethos is critical to any fight for justice within information science.



11:30am - 11:45am
ID: 167 / PS-03: 2
Short Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.
Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.
Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/
Topics: Library and Information Science
Keywords: AI literacy, AI learning and teaching, AI in education, AI ethics, AI literacy questionnaire

AI Literacy: Definition, Teaching, Evaluation, and Ethical Issues

Davy Tsz Kit Ng, Jac Ka Lok Leung, Kai Wah Samuel Chu, Maggie Shen Qiao

University of Hong Kong, Hong Kong

Artificial Intelligence (AI) is at the top of the agenda for education leaders today in educating the next generation across the globe. However, public understanding of AI technologies and how to define AI literacy is under-explored. This vision poses upcoming challenges for our next generation to learn about AI. On this note, an exploratory review was conducted to conceptualize the newly emerging concept “AI literacy”, in search for a sound theoretical foundation to define, teach and evaluate AI literacy. Grounded in literature on 18 existing peer-reviewed articles, this review proposed four aspects (i.e, know and understand, use, evaluate, and ethical issues) for fostering AI literacy based on the adaptation of classic literacies. This study sheds light on the consolidated definition, teaching, and ethical concerns on AI literacy, establishing the groundwork for future research such as competency development and assessment criteria on AI literacy.



11:45am - 12:15pm
ID: 204 / PS-03: 3
Long Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.
Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.
Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/
Topics: Library and Information Science
Keywords: library and information science; artificial intelligence; foundations of information science; research methods

Not Quite ‘Ask a Librarian’: AI on the Nature, Value, and Future of LIS

Jesse Dinneen, Helen Bubinger

Humboldt-Universität zu Berlin, Germany

AI language models trained on Web data generate prose that reflects human knowledge and public sentiments, but can also contain novel insights and predictions. We asked the world’s best language model, GPT-3, fifteen difficult questions about the nature, value, and future of library and information science (LIS), topics that receive perennial attention from LIS scholars. We present highlights from its 45 different responses, which range from platitudes and caricatures to interesting perspectives and worrisome visions of the future, thus providing an LIS-tailored demonstration of the current performance of AI language models. We also reflect on the viability of using AI to forecast or generate research ideas in this way today. Finally, we have shared the full response log online for readers to consider and evaluate for themselves.



12:15pm - 12:30pm
ID: 110 / PS-03: 4
Short Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.
Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.
Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/
Topics: Technology; Culture; and Society
Keywords: Artificial Intelligence Education; Artificial Intelligence Ethics; Ethics Education; Pedagogy; Thematic Analysis

Five Motivating Concerns for AI Ethics Instruction

Mariah Knowles

University of Wisconsin-Madison, USA

Artificial Intelligence (AI) systems are embedded in institutions that are not diverse, that are inequitable, unjust, and exclusionary. How do we address the interface between AI systems and an unjust world, in service to human flourishing? One mechanism for addressing AI Ethics is AI Ethics Education: training those who will build, use, and/or be subject to AI systems to have clear moral reasoning, make responsible decisions, and take right actions. This paper presents, as part of a larger project, work on what AI Ethics instructors currently do and how they describe their motivating concerns. I find that although AI Ethics content and pedagogy is varied, there are some common motivating concerns particular to this kind of teaching, which may be useful in structuring future guidance for new AI Ethics teachers, evaluating existing pedagogy, guiding research on new pedagogies, and promoting discussion with the AI Ethics community.