Below are a selection of presentations, papers, and other projects from LIS 4934 and previous classes
In the past decade, artificial intelligence (AI) has expanded tremendously. AI can be found in every major career sector, including healthcare, entertainment, agriculture, customer service, and more (Research Trends, 2023). The education system is no exception, as AI has started to be integrated into the classroom. Homework resources, such as Chegg and Quizlet, for example, now offer generative AI assistance to students to streamline the tutoring process. However, the use of generative AI in education has raised ethical questions from students and educators alike. Some argue that overreliance in generative AI (or GenAI) can lead to a reduction in assignment quality, as more students start to utilize AI to complete assignments for them entirely, versus putting effort into the assignment themselves. However, researchers have begun to propose solutions that can aid in finding a middle ground in GenAI usage. This can be used to mitigate some of the ethical concerns that arise with GenAI usage and allow for students and educators to use GenAI in a constructive way. One of the major concerns that has arisen with the development of GenAI is bias. More specifically, large language models (LLMs) such as ChatGPT, DeepSeek, and Google Gemini, all gather their reservoir of information from the Internet. The databases that are used to source information for these LLMs are feed by web pages that can be discriminatory in nature (Furze, 2023). These instances of unsavory information can mainly be found on social media platforms such as Facebook and Twitter, where users may make posts that are intentionally misleading or otherwise not well-regulated. As a result, users of LLMs may get output that is incorrect or extremely biased (Furze, 2023). To combat this, studying the current AI algorithms and reshaping them to include less-harmful content would be appropriate. Along with biased information, another ethical concern is user and data privacy. While using GenAI, questions arise about LLMs and other AI resources collecting user information and using it to fuel advertisements that are seen by the user. This raises concerns, since collecting user data in such a large scale can be violating to the user’s privacy and civil rights (Furze, 2023). In the case of a data breach, users who have sent information to GenAI may be at risk. While there are laws in place, such as General Data Protection Regulation (GDPR) within the European Union, the United States does not have one major law that regulates data protection for citizens (but rather multiple regulations that may vary per state; IT Governance USA, 2024). Plagiarism, copyright infringement, job exploitation, and global power imbalances are other concerns that arise with the usage of GenAI, and all of these concerns point to the question: what ethical guidelines can be put in place to address these concerns in the context of academics? (Furze, 2023). Perkins et al. (2024) have created the AI Assessment Scale (AIAS) to aid in resolving this dilemma. The AIAS can be used to help educators determine when AI usage is appropriate for their instructional material, while also being transparent with both students and teachers on how AI may be used to complete certain assignments. The AIAS is a step in the right direction, as it embraces AI, while still giving educators the space to dictate when AI regulation is necessary in the classroom. Information professionals must also be cognizant of GenAI and its application in the information science sector. GenAI may be used in the future to speed up the information-seeking process, for example. While this would increase efficiency, the aforementioned ethical considerations should be taken into account as well. When analyzed critically, it can be concluded that GenAI can be used within the educational realm to aid students with everyday assignments. For example, students can use AI to help them lay the groundwork for an essay, or determine the basics for solving an unknown math equation. Generative AI is a force that has grown exponentially, and it has been interwoven into our everyday lives. When used ethically, GenAI is a great tool to be used as a foundation for one’s academic endeavors. However, regulations must be utilized to ensure that GenAI is used ethically and constructively. Otherwise, this can lead to overreliance in AI, and a reduction of human innovation.
Self-driving, or autonomous cars have been a cause of contention over the past decade. According to the National Highway Traffic Safety Administration (NHTSA), self-driving cars are held to a high standard on the road and are currently deemed safe for consumers to use. However, due to their large growth in popularity, many have begun to raise questions about their safety on the road. Some argue that self-driving cars do not have the same moral judgement that a human driver would have when it comes to car accidents (i.e. the car might run a red light that a human driver would have stopped at). Others argument that more safety regulations are needed to ensure autonomous cars and other self-driving vehicles are properly managed on the road. According to ACM TechNews, there has been a surge of Waymo robotaxis being spotted in major cities, such as San Francisco, Los Angelos, and Phoenix. Waymo is a robotaxi company that usually offers driverless car services in smaller areas, but has recently expanded to start driving on freeways with increased speed limits (Elias and Kolodny, 2025). While searching through previous legislation that governs autonomous cars on the road, the most current legislation that appears to govern this policy is the One Big Beautiful Bill Act, that was recently passed earlier this year. It discusses plans to further asses pollution and transportation equity in the United States. Stakeholders, such as the driverless car manufacturers, government regulators, and insurance companies should all be involved with future policy decisions. Autonomous vehicles are a controversial topic, since there is a stigma associated with cars being allowed to make potentially dangerous decisions (such as navigating a car crash) without driver input. Driver-less cars are far from perfect, but they have come a long way in the past few years. Self-driving cars have been tested across the country, and current highway laws support their usage, as they are consistently being upgraded to better manage ever-changing traffic patterns on the road. To aid information professionals in the policy process, it would be beneficial for automakers to be transparent about the algorithms they are using to generate their automated driving mechanisms. There also needs to be safeguards put in place to ensure that this algorithm is not tampered with by malware or other cyberattacks.
The Bachelors of Science in Information Science (BSIS) program at the University of South Florida is one of the most unique programs offered at the institution. Being a fully-online degree, this major offers a level of flexibility that is not often seen within other Bachelor’s programs. The discipline of Information Science combines several fields, such as Computer Science, Psychology, and more. The interdisciplinary nature of Information Science allows for it to be applied in a wide variety of careers, such has Librarianship, data analytics, health informatics, and more. I have been a part of the BSIS program for about two years. When I initially started at USF, I was a Biomedical Sciences major only. At the end of my freshman year, I found out about the Information Science program through a post on LinkedIn. I did more research on the program through the official USF website, and gained an interest in the Health Informatics concentration due to its relevance to my future career aspiration (as a physician). I am now dual majoring in Biomedical Sciences and Information Science, with a concentration in Health Informatics. The Health Informatics concentration has several courses students are required to take to prepare them for a career in this career sector, such as: • LIS4482: Networks and Communication • LIS4777: Clinical Decision Support Systems (CDSS) • LIS4776: Health Information Technology • LIS4779: Health Information Security • LIS4785: Introduction to Health Informatics • LIS4930: Electronic Health Records All of the courses listed above contribute to the education of future information professionals in different ways. Networks and Communication, for example, discussed the fundamentals of IT infrastructure and cybersecurity. This is essential because it creates a foundation for other technical courses in the concentration, such as CDSS. CDSS delves into the role of tools used in a healthcare system (such as EHRs, digital alert systems, medication error trackers, etc.). In order to ensure that these systems work in healthcare clinics efficiently, the IT network within the clinic needs to be operating properly. A proper cybersecurity strategy (such as a firewall, secure passwords for hospital equipment, etc.) is needed to protect patient data from malicious attacks. Outside of the Health Informatics concentration, the core courses of the Information Science major have also taught me a lot about information behaviors and how information professionals can work with other stakeholders to create change in governmental policy. These courses include: • LIS4204: Information Behaviors • LIS2780: Database Concepts • LIS4414: Information Policy and Ethics • LIS3261: Introduction to Information Science • LIS3353: IT Concepts for Information Professionals Out of all of the assignments I have taken as a BSIS major, two assignments that really stuck out to me were from my Health Information Technology course, and Information Behaviors course respectively. For LIS 4776, we were required to work in groups of 5 to create a presentation for a new health technology to be implemented within a healthcare system. My team and I pitched the idea of a mobile monitoring application for elderly patients with cardiovascular disease (CVD). With this mobile monitoring application, elderly patients do not have to worry about traveling to their cardiologist appointments as often, as telehealth can be administered at home. The process of identifying stakeholders, cost of equipment implementation, and determining the Agency for Healthcare Research and Quality (AHRQ) standards that the application met taught me all of the work that goes into implementing technologies into a healthcare setting. In LIS4204, one of our major assignments for the semester was to conduct a literature search within USF’s library database. This assignment was a great tutorial on how to refine one’s search to narrow down the types of articles one wants to find. This is especially important when conducting literature reviews for research, as it allows the researchers to swiftly collect all of the articles they need for further analysis. To conclude, the Information Science major’s versatility cannot be overemphasized. While information professionals are mostly found within the library science and data science career sector, there is also a need for information professionals in healthcare. The Health Informatics concentration has demonstrated how information technology and healthcare intersect to create better health outcomes for patients and staff alike.