Medicare Plan Optimizer: A Tool for Society; The Implications of AI and Technology in Motorsports

This STS project addresses the integration of AI and technology within the world of motorsports, analyzing how it influences the cultural perception of skill and competition in racing. The rapid integration of new technologies has changed how drivers and teams interact with each other and raises questions about whether these new innovations hinder driver skill. The technical project focuses on the creation and development of a Medicare Plan Optimizer. This Optimizer takes in user preferences and recommends them a Medicare Plan that is best suited for their individual needs. It serves as a tool to improve access to these healthcare benefits, and provides users with knowledge about what plans might be best for them. The STS topic was chosen because the world of motorsports is rapidly evolving and new technologies such as AI are widely utilized within the sport. This provides an unique perspective on how these new rapidly developing technologies are utilized and to what extent they have an influence on performance. In my STS research, I examined the integration of AI and technology within the world of motorsports. In the last couple decades, motorsports has increasingly utilized new technologies to improve performance. Developments like data-driven algorithms, optimization techniques and AI models are being utilized by teams and have altered the culture and environment of motorsports. I investigated if these technologies diminished driver skill and hindered competition within the sport. However, my research concluded that these new technologies actually evolve the definition of driver skill and competition instead of diminishing it. Drivers are forced to learn different skills and knowledge to achieve maximum performance, while teams are constantly managing adjustments and innovating to construct the fastest possible vehicle. The integration of AI and newly developed innovations help redefine and expand the skillsets of the drivers and shows how human performance and machine learning can operate together to achieve even greater performance. The technical portion of my thesis focuses on the development of a Medicare Plan Optimizer. Medicare is a federal healthcare program for individuals that are aged 65+ or younger individuals with certain disabilities. It has a vast amount and variety of plans with each having an immense amount of details regarding medications and what it covers. This makes it difficult for users to find a plan that suits their needs and situation. Additionally, due to the requirements of Medicare, people who need to enroll in it are often elderly or have certain prohibiting circumstances which make it difficult for them to enroll themselves. This Optimizer aims to help solve that problem by providing a tool that is easy to navigate. It utilizes an individual's preference about healthcare plans, and optimizes plans based on that to provide users with a quick and easy recommendation. This helps provide access and knowledge about Medicare plans to these individuals who may have a hard time enrolling themselves. The distinguishing feature of this project is that it optimizes and recommends a plan based on a dataset of actual Medicare plans. This is obtained directly from the Medicare website and provides the user with actual plans around their area. This ensures that users are given accurate and up to date information regarding their Medicare plan. Considering the technical, organizational, and cultural elements of both motorsports and healthcare optimization, this project highlights the importance of having an STS perspective in engineering. Having an STS perspective allows engineers to foster a sense of ethical responsibility which is essential in the development and integration of new technologies. This perspective helps identify how new technologies such as algorithmic tools may be reshaping things like performance and decision-making. Additionally, it helps identify the environment and structure of an industry and how a new technology might influence it. This is essential for engineers, as understanding the impacts of a new innovation helps consider who benefits, who might be excluded, and how human values are shaped by design decisions. Integrating these perspectives ensures that all engineering solutions like the Medicare Plan Optimizer, are not only functional, but also equitable and culturally aware. I would like to express my sincere gratitude to my STS professors, William Davis and Coleen Carrigan, for their guidance and support throughout the STS portion of this project, and to my Capstone advisor, Rosanne Vrugtman, for her constructive feedback throughout the technical portion of this project.