TPRC 2024: The 52nd Research Conference on Communications, Information and Inter

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Abstract:
This paper will analyze regulatory conflicts within American states that have passed laws restricting municipal or non-profit projects to build local broadband networks, and the requirements for receiving grants under the federal Broadband Equity, Access, and Deployment (BEAD) program.

This paper will conduct a state-by-state comparative policy analysis of the contradictions between anti-expansion/preemption laws and the desire of those states to partake of billions of dollars in BEAD funds. The analysis will include the strategies that lawmakers and lobbyists used when passing the restrictive statutes, and their more recent attempts to explain those contradictions in politicized ways.

Furthermore, federal interpretations of the regulatory contradictions, especially the federal government's demand for state restrictions to be waived, may evolve during 2024 as the U.S. Supreme Court reassesses federal regulatory procedures. Therefore, the paper will include the most up-to-date judicial developments, as the BEAD program may or may not be able to supersede state laws. The paper will ultimately reveal whether BEAD funding for needy communities is likely to be stalled by these regulatory conflicts.

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This paper investigates the impact of the Affordable Connectivity Program (ACP)the largest and most successful consumer broadband subsidy program in the U.S.on health outcomes. Using repeated cross-sectional survey data from the National Health Interview Survey (NHIS), four health outcomes are examined in this paper: 1) Use of telehealth services; 2) Looking up health information online; 3) Communication with doctor's office online; and 4) Retrieve test results online. A difference-indifference model is fitted to estimate the impact of ACP on telehealth use, finding no evidence. Logistic regression time fixed effects models were estimated to predict the health outcomes in ACP eligible and ineligible populations. The results indicate that ACP eligible adults have lower odds of using the internet for any of these health-related activities compared to the rest of the population. However, after controlling for demographic characteristics, no evidence of a difference in odds is seen for health information search, communicating with a medical provider, or retrieving test results. Adults with a bachelor's degree, women, those who live in a metro area, or have a higher income to poverty ratio, have higher odds of using the internet for all of these health-related activities. Increase in age, being of Hispanic origin or Black are associated with lower odds. Adults enrolled in Medicaid have higher odds for telehealth and communicating with a provider, but lower odds for health information search.

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The literature utilizes many terms to discuss people in society who are most likely to be at a higher risk of "death, property loss, and injury".[i] These groups of people are referred to as marginalized or vulnerable populations. Historically, vulnerable populations have been disproportionately affected by disasters. Some examples of vulnerable populations include the elderly and people with disabilities.[ii] The most significant challenge at the intersection of vulnerable populations and emergency information is receiving and accessing the messaging.[iii] As a result, emergency communication to the elderly and people with disabilities may be insufficient. Given this reality, with early messaging about COVID-19 focusing on its severity for older populations and those with underlying conditions, did those most vulnerable to COVID-19 receive timely and accessible emergency messaging?
Methods. Modifying an existing measure of the effectiveness and accessibility of emergency communications, we collected data from people with disabilities and older adults about their perceptions of COVID-19 as a threat, how and when respondents first heard of COVID-19, preferences for receiving COVID-19 information, barriers experienced in accessing COVID-19 information; protective actions taken in response to the COVID-19 information received; and demographics. We reported the frequencies of all variables and used Chi-Square tests to measure the statistical significance of relationships between variables.
Results. 77% of respondents indicated they first learned about COVID-19 before March 2020, with many reporting awareness as early as January 2020. While 72% of respondents indicated that they took protective actions based on the information received. Of the respondents who indicated that they did not take protective actions, 67% did not take protective actions (such as masking or quarantining) cited inadequate information as the reason not to act. The barriers to accessing COVID-19 information were the lack of sign language interpreters or poorly placed interpreters (37%), followed by the lack of or poor quality captions (33%), inaccessible websites and digital media (17%), and too complicated information (9%). Respondents <65 years old were 1.65 times more likely to become increasingly concerned with how COVID-19 could affect them compared to their counterparts >65. Respondents >65 years old were 1.81 times more likely to have expressed that they used digital formats than those <65 years old.
Conclusion. In answering the guiding research question, results revealed that the information was timely but not consistently accessible. Making digital media accessible to people with vision disabilities, using captions and interpreters on live and recorded video, is key to ensuring inclusive public health information dissemination. It is critical to evaluate these results with a policy lens to understand the broader implications of inaccessible messaging. The FCC and the Department of Justice have published laws and regulations concerning accessible emergency information. However, as the results show, they are not always heeded. These findings lend themselves to empirically supported regulatory input to advance inclusive practices.

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Public debate has long focused on the challenges and flaws of commercial content moderation, which operates as a top-down mechanism on large-scale social media platforms, utilizing algorithms and human moderators to achieve platform-centralized content moderation goals. This approach has been criticized for its potential lack of democracy and legitimacy. This paper examines a community-reliant content moderation model, the digital juror system, which involves user juries blind-voting on content moderation cases. It explores the potential of this model to address existing content moderation issues. Focusing on two major Chinese social media platforms, Douyin and Sina Weibo as sites, this study employs semi-structured interviews with 15 public jurors working for these platforms. The research investigates these digital jurors’ intentions, experiences, and how they are influenced by their communal content moderation practices. The findings reveal that the digital juror system prompts community self-moderation driven by users’ sense of civic duty, but it also, to some extent, transforms content moderation into a form of entertainment or a microtask associated with hope labor. Additionally, although the digital juror model is designed to resemble the legal jury trial system, its democratic legitimacy is limited due to the omission of important procedural elements such as deliberation.

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When in early 2024 nonconsensual pornographic deepfakes of international pop superstar Taylor Swift were circulated on the social media platform X, fans quickly started to report them so that they would be taken down. They also flooded the platform and corresponding hashtags with media to drown out the deepfakes and make them harder to find. X ultimately temporarily blocked all searches for Taylor Swift. Drawing on in-depth semi-structured interviews with fans of Taylor Swift – so-called Swifties – this paper presents a case study of the incident. We discuss the case, individual reporting experiences, concerns around deepfakes, and the question of platform vs. user responsibility for addressing online harms. We provide empirical evidence on the impactful role that fans can play in platform governance when they coordinate and unleash collective online action. Outside of fandom, our findings have implications for reporting and flagging as a form of civic responsibility online.

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The presence of deepfakes, highly realistic artificial media, has begun to rapidly increase with the growth of accessible tools that allow novice users to build lifelike images and videos. These can be used for training artificial intelligence (AI) models to recognize diseases when there is a shortage of images. These Generative Adversarial Nets, or GANs, utilize two neural networks that work opposingly to construct further refined and more realistic deepfake images. Although these images can be used for training AI models, they can also end up being used by attackers to corrupt images that are seen by medical professionals as real. Consequently, these forms of falsified information have begun to percolate through numerous fields and generated an increased concern in the protections that exist against the dissemination of deepfake images, and the privacy of individuals pictured. Going beyond general harassment or misinformation, these deepfakes could be used in various fields to cause new methods of harm. In particular, the medical industry has begun to consider the implications that could result from the progression of generative image technology and question the data security present in medical imaging storage technologies, commonly known as picture archiving and communication systems, or PACS. It is possible to deepfake medical images that inject or remove portions of the image and potentially alter patient diagnoses. Accordingly, the protection against the production and dissemination of deepfake images within the medical field is necessary to uphold the integrity of medical imaging. Without proper identification of diseases through medical imaging, patients may be at risk for incredibly costly misdiagnoses that may also lead to complications or even cost them their life. To inform the potential policy and legal implementations that are necessary for the medical field to combat threats of cybersecurity with regard to deepfake medical images, the objective of this research is to conduct a systematic literature review across the previously conducted work on deepfake imaging and its relationship to the field of medical images to identify areas of concern, such as PACS, in which additional policy regulations may further secure the data of patients in the medical industry and develop protections for medical institutions against the rapidly evolving threat of deepfake medical images. Even though deepfake medical images are used in positive ways to train AI driven medical diagnosis, serious harm and wasted resources are potentially caused by deepfake medical images. This research calls for policy to proactively call for reasonable measures to ensure validity of medical imaging. Moreover, this research will assess previously identified security implementations, such as digital watermarking, blockchain technology, or other solutions. Instead of waiting until harm is widespread, and trust is further eroded from medicine, this research calls for potential steps implemented by policy and legal mandates to ensure more discrete measures that allow for the protection against and identification of deepfake images in medicine.