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Fully autonomous or “self-driving” vehicles are an emerging mobility technology with a host of potential benefits over conventional motor vehicles. Proponents argue that widespread adoption of self-driving vehicles may save countless lives and millions of dollars annually by minimizing the likelihood of deadly vehicle crashes. However, for such benefits to be realized, widespread consumer adoption of self-driving technologies is a prerequisite. Prior research suggests that while consumers are broadly optimistic about the potential of vehicle automation, there are significant concerns that may undermine consumer adoption, such as the transparency of vehicle operation. There is insufficient research into consumers’ desire to understand a self-driving vehicle’s intent and decision-making process and its impact on their willingness to adopt. We conducted a study using a 63-question internet-based survey distributed in the United States to licensed drivers 18 years of age and older (n= 996) to examine consumer preferences of the information transparency of self-driving vehicles. Our findings suggest that middle-aged and older consumers of high household income were generally optimistic about the information sharing behavior and transparency of self-driving vehicles upon availability. 

Computing is not only a fundamental part of our daily lives — our national security depends on it. It is essential that members of the Reserve Officer Training Corps (ROTC) be well-versed in computing techniques designed to combat cyber-attacks that continually improve in sophistication and frequency levels. Through computer science education, prospective military leaders are being taught the critical and analytical thinking skills necessary to address these threats. This paper outlines and discusses how underrepresented minority Naval Reserve Officer Training Corps (NROTC) midshipmen, with the majority having little-to-no programming skills or background, were taught the foundational aspects of computer science and exposed to specific cybersecurity concepts in a 15-week program. The program produced many insightful outcomes, one being the development of a tool that collected and analyzed publicly available social media data through the application of data mining algorithms and techniques. Additionally, interviews, which were conducted upon the completion of the program, documented notable findings on the program’s effectiveness and on key concepts for teaching computer science to minority beginners.