Katherine R. Garcia

Rice University

Author Statistics

Papers

Citation

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i-10 index

Research Field

How the Police and Armed Forces Construct Gender on Social Media: A Comparison of El Salvador and Honduras

Feminist Criminology (2024)

Anjuli Fahlberg Katherine R. Garcia Laura García J L Canova Perez Peter Nadel

Although social media is the new frontier for policing, little research has examined how state security forces construct gender online. To address this gap, we analyzed 315 TikTok videos posted by law enforcement agencies in El Salvador and Honduras. We find that gender is constructed by (1) showcasing (or not) female officers; (2) displaying masculinized and feminized policing practices; (3) advancing gendered ideas through editorial additions. We further find that gendered performances by police vary between the “iron-fist” regime of El Salvador and the “soft-touch” regime in Honduras, while the armed forces of both countries adopt more gender-neutral images.

Fist

Frontier

10.1177/15570851241268187

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Human-Automation Interaction for Semi-Autonomous Driving: Risk Communication and Trust

Automation, collaboration, and e-services (2022)

Jing Chen Scott Mishler Shelby K. Long Sarah Yahoodik Katherine R. Garcia

Covert

Situation Awareness

10.1007/978-3-031-10784-9_17

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Identifying Perturbed Roadway Signs: Perception of AI Capabilities

Proceedings of the Human Factors and Ergonomics Society Annual Meeting (2022)

Katherine R. Garcia Yanru Xiao Scott Mishler Cong Wang Bin Hu

10.1177/1071181322661225

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Drivers’ Understanding of Artificial Intelligence in Automated Driving Systems: A Study of a Malicious Stop Sign

Journal of Cognitive Engineering and Decision Making (2022)

Katherine R. Garcia Scott Mishler Yanru Xiao Cong Wang Bin Hu

Automated Driving Systems (ADS), like many other systems people use today, depend on successful Artificial Intelligence (AI) for safe roadway operations. In ADS, an essential function completed by AI is the computer vision techniques for detecting roadway signs by vehicles. The AI, though, is not always reliable and sometimes requires the human’s intelligence to complete a task. For the human to collaborate with the AI, it is critical to understand the human’s perception of AI. In the present study, we investigated how human drivers perceive the AI’s capabilities in a driving context where a stop sign is compromised and how knowledge, experience, and trust related to AI play a role. We found that participants with more knowledge of AI tended to trust AI more, and those who reported more experience with AI had a greater understanding of AI. Participants correctly deduced that a maliciously manipulated stop sign would be more difficult for AI to identify. Nevertheless, participants still overestimated the AI’s ability to recognize the malicious stop sign. Our findings suggest that the public do not yet have a sufficiently accurate understanding of specific AI systems, which leads them to over-trust the AI in certain conditions.

10.1177/15553434221117001

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Citations (6)

Investigating Training and Priming to Combat Phishing on Instagram Shop

Proceedings of the Human Factors and Ergonomics Society Annual Meeting (2024)

Katherine R. Garcia Jing Chen

Phishing attacks have been predominantly delivered through emails but have recently found new paths through social networking services (SNSs). Numerous methods to combat email phishing have been tested, but few have been tested to combat phishing on SNSs. The current study investigated the efficacy of in-app training and priming to combat phishing attacks on an SNS, the Instagram Shop. This study manipulated priming, training type, and advertisement type through a mixed experimental design. Participants were tasked to view Instagram Shop advertisements to rate how likely they would recommend the products to their boss along with their reasoning for their ratings. Results showed that the text-with-image training effectively enhanced the likelihood of recommending legitimate advertisements and not recommending phishing ones. Overall, this study shows that the training implemented aided Instagram users in appropriately recommending phishing and legitimate advertisements, although priming was not seen to have an effect toward this goal.

Phishing

Priming (agriculture)

Boss

10.1177/10711813241261384

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Predicting a Malicious Stop Sign: Knowledge, Exposure, Trust in AI

Proceedings of the Human Factors and Ergonomics Society Annual Meeting (2021)

Scott Mishler Katherine R. Garcia Erin Fuller-Jakaitis Cong Wang Bin Hu

10.1177/1071181321651239

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Detail Matters: Drivers’ Responses to Flood Warnings in Simulated Driving

Proceedings of the Human Factors and Ergonomics Society Annual Meeting (2024)

Katherine R. Garcia Jing Chen

Flood risk communication is imperative to aiding people’s decision making in flood situations. These warnings can be communicated through navigation applications on mobile devices. The current study investigated how flood-depth information affected drivers’ actions given flood warnings from a mobile navigation application in a driving simulator. This study manipulated the type of flood warning presented to the participants in the driving scenarios and measured their actions given a potentially flooded roadway. Participants experienced six drives with different flood warning conditions. Results indicated that providing flood depth information helped drivers accurately estimate the depth of the flood and their perceived risks; including more detailed information was helpful for drivers to make informed decisions regarding a flooded roadway. We suggest that designers include flood depth information to help drivers accurately perceive the depth and risk regarding a flooded roadway.

Flood warning

10.1177/10711813241261381

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Driver Decisions Based on Flood Warning Information

Proceedings of the Human Factors and Ergonomics Society Annual Meeting (2023)

Katherine R. Garcia Jing Chen

Flood warnings can be communicated through mobile devices and should convey enough information to keep the user safe during a flood situation. However, the amount of detail included in the warning, such as the depth of the flood, may vary. The purpose of this study was to investigate how to best inform drivers of floods to keep them protected. Participants were tasked to drive to a restaurant in a driving simulator after receiving instructions and a type of flood information warning during each scenario (flood, no flood, flood of 6 inches, flood of 6 inches maximum). We found that participants accepted the alternate route more when in a scenario with a flood present compared to the no-flood scenario. These results deepened the understanding of human decisionmaking and can guide future flood warning designs to keep drivers protected from flooded roadways

Flood warning

10.1177/21695067231192568

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Investigating User Photo Privacy Settings on Instagram

Proceedings of the Human Factors and Ergonomics Society Annual Meeting (2023)

Katherine R. Garcia Alexa Quesnel Na Li Jing Chen

Photo sharing has become increasingly easy with the rise of social media. Social networking sites (SNSs), such as Instagram and Facebook, are well known for their image-sharing capabilities. However, this brings the concern of photo privacy, such as who may see the images of a user who is included in a post. Photo privacy settings offer detailed and more secure ways to share a user’s photos, however, this would require SNS users to understand these settings. To better grasp users’ understanding of photo privacy settings, we conducted a structured interview with Instagram users. We found that users were aware of the majority of the privacy settings asked about and that they accurately perceived their photo privacy safety based on their knowledge of photo privacy settings.

Privacy software

Privacy Protection

10.1177/21695067231192286

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Protecting privacy while releasing data: Strategies to maximise benefits and mitigate risks

Joel Gurin Matt Rumsey Audrey Ariss Katherine R. Garcia

10.5281/zenodo.1117782

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