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2. Cover

Author

Davis, Jenny L.

Published
2018

3. Index

Author

Davis, Jenny L.

Published
2018

5. Notes

Author

Davis, Jenny L.

Published
2018

14. Smallset Timelines: A Visual Representation of Data Preprocessing Decisions

Author

Lucchesi, Lydia R., Kuhnert, Petra M., Davis, Jenny L., and Xie, Lexing

Subjects
Computer Science - Human-Computer Interaction
Abstract

Data preprocessing is a crucial stage in the data analysis pipeline, with both technical and social aspects to consider. Yet, the attention it receives is often lacking in research practice and dissemination. We present the Smallset Timeline, a visualisation to help reflect on and communicate data preprocessing decisions. A "Smallset" is a small selection of rows from the original dataset containing instances of dataset alterations. The Timeline is comprised of Smallset snapshots representing different points in the preprocessing stage and captions to describe the alterations visualised at each point. Edits, additions, and deletions to the dataset are highlighted with colour. We develop the R software package, smallsets, that can create Smallset Timelines from R and Python data preprocessing scripts. Constructing the figure asks practitioners to reflect on and revise decisions as necessary, while sharing it aims to make the process accessible to a diverse range of audiences. We present two case studies to illustrate use of the Smallset Timeline for visualising preprocessing decisions. Case studies include software defect data and income survey benchmark data, in which preprocessing affects levels of data loss and group fairness in prediction tasks, respectively. We envision Smallset Timelines as a go-to data provenance tool, enabling better documentation and communication of preprocessing tasks at large., Comment: In 2022 ACM Conference on Fairness, Accountability, and Transparency (FAccT '22), June 21-24, 2022, Seoul, Republic of Korea

Published
2022

15. Artificial Intelligence, Social Responsibility, and the Roles of the University.

Author

Loui, Michael C., Bosch, Nigel, Chan, Anita Say, Davis, Jenny L., Gutiérrez, Rochelle, He, Jingrui, Karahalios, Karrie, Koyejo, Sanmi, Mendenhall, Ruby, Sanfilippo, Madelyn Rose, Tong, Hanghang, Varshney, Lav R., and Wang, Yang

Subjects
UNIVERSITIES & colleges, ARTIFICIAL intelligence, SOCIAL responsibility, DISCRIMINATION (Sociology), NETWORK governance
Abstract

This article details how universities could actively influence both the development and use of artificial intelligence (AI) with an emphasis on social responsibility. The articles explores four university missions—education, research, community collaboration, and public service—that can serve as areas of influence for the social responsibility of AI development and use.

Published
2024
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23. Elevating humanism in high-stakes automation: experts-in-the-loop and resort-to-force decision making.

Author

Davis, Jenny L.

Subjects
*PROMISES, *DECISION making, *ARTIFICIAL intelligence, *AUTOMATION, *HUMANISM, *EXPERTISE
Abstract

Artificial intelligence (AI) technologies pervade myriad decision systems, mobilising data at a scale, speed, and scope that far exceed human capacities. Although it may be tempting to displace humans with these automated decision systems, doing so in high-stakes settings would be a mistake. Anchored by the example of states' resort to force, I argue that human expertise should be elevated—not relegated—within high-stakes decision contexts that incorporate AI tools. This argument builds from an empirical reality in which defence institutions increasingly rely on and invest in AI capabilities, an active debate about how (and if) humans should figure into automated decision loops, and a socio-technical landscape marked by both promise and peril. The argument proceeds through a primary claim about the amplified relevance of expert humans in light of AI, underpinned by the assumed risks of omitting human experts, together motivating a tripartite call to action. The position presented herein speaks directly to the military domain, but also generalises to a broader worldbuilding project that preserves humanism amidst suffusive AI. [ABSTRACT FROM AUTHOR]

Published
2024
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37. Community partnerships are fundamental to ethical ancient DNA research

Author

Kowal, Emma, primary, Weyrich, Laura S., additional, Argüelles, Juan Manuel, additional, Bader, Alyssa C., additional, Colwell, Chip, additional, Cortez, Amanda Daniela, additional, Davis, Jenny L., additional, Figueiro, Gonzalo, additional, Fox, Keolu, additional, Malhi, Ripan S., additional, Matisoo-Smith, Elizabeth, additional, Nayak, Ayushi, additional, Nelson, Elizabeth A., additional, Nicholas, George, additional, Nieves-Colón, Maria A., additional, Russell, Lynette, additional, Ulm, Sean, additional, Vergara-Silva, Francisco, additional, Villanea, Fernando A., additional, Wagner, Jennifer K., additional, Yracheta, Joseph M., additional, and Tsosie, Krystal S., additional

Published
2023
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40. Implementing and Analyzing Social Media in Higher Education

Author

Davis, Jenny L., Compton, D'Lane, Farris, D. Nicole, and Love, Tony P.

Abstract

This article examines how social media can incorporate into the higher education setting in meaningful ways using optional participation, active content production, and active moderation. The authors use two authoethnographic case studies. The first case pertains to pedagogical use through a student created and maintained Facebook group for a Sociology of Gender course. The second case pertains to the construction and maintenance of a participatory learning culture through a departmental Facebook page. The article includes accounts from each case and an analysis of the successful components.

Published
2015

47. Intersecting matters: #GeorgeFloyd and #COVID19

Author

Davis, Jenny L. and Love, Tony P.

Subjects
Human-Computer Interaction, Computer Networks and Communications
Abstract

In the late spring of 2020 amid a global pandemic, George Floyd was killed by police in Minneapolis, Minnesota, triggering mass protests under the banner of the Black Lives Matter movement. We take this moment of coinciding crises as our point of analysis observed through the lens of concurrent hashtags on Twitter. Social media content both reflect and construct the social meanings of topics and events. We thus draw from social media to understand how George Floyd and COVID-19 inform and inflect each other, building a dataset from ∼20,000 tweets that unite prevalent hashtags associated with each. Analyses reveal a repeating set of symbolic hooks — death, breath, masks, and voice — encompassing dense and competing narratives about justice and injustice, systemic inequality, degrading trust in institutions, and the changing identity of a nation. These narratives are anchored in the events under study and indexed through co-occurring social media registers. In addition to substantive findings, the study introduces and applies hashtag convergence, a novel methodological approach based on user-generated indexical pairings.

Published
2022

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