6 research outputs found
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Essays on the Discretion of Prosecutors in the Legal Realm
This dissertation contains three chapters that describe the discretion of prosecutors in different ways. The first is a quantitative study that measures how many different interpretations a statute has and how that affects conviction rate. The second is an experiment that has mock prosecutors act out a courtroom situation to see if they select a law that is more just or one that gives them a higher economic pay-off. The third is a qualitative article that uses interviews with prosecutors and a survey to answer questions that are not addressed in the other two chapters. All of the chapters complement each other
Recommended from our members
Essays on the Discretion of Prosecutors in the Legal Realm
This dissertation contains three chapters that describe the discretion of prosecutors in different ways. The first is a quantitative study that measures how many different interpretations a statute has and how that affects conviction rate. The second is an experiment that has mock prosecutors act out a courtroom situation to see if they select a law that is more just or one that gives them a higher economic pay-off. The third is a qualitative article that uses interviews with prosecutors and a survey to answer questions that are not addressed in the other two chapters. All of the chapters complement each other
Perception, performance, and detectability of conversational artificial intelligence across 32 university courses
Abstract The emergence of large language models has led to the development of powerful tools such as ChatGPT that can produce text indistinguishable from human-generated work. With the increasing accessibility of such technology, students across the globe may utilize it to help with their school work—a possibility that has sparked ample discussion on the integrity of student evaluation processes in the age of artificial intelligence (AI). To date, it is unclear how such tools perform compared to students on university-level courses across various disciplines. Further, students’ perspectives regarding the use of such tools in school work, and educators’ perspectives on treating their use as plagiarism, remain unknown. Here, we compare the performance of the state-of-the-art tool, ChatGPT, against that of students on 32 university-level courses. We also assess the degree to which its use can be detected by two classifiers designed specifically for this purpose. Additionally, we conduct a global survey across five countries, as well as a more in-depth survey at the authors’ institution, to discern students’ and educators’ perceptions of ChatGPT’s use in school work. We find that ChatGPT’s performance is comparable, if not superior, to that of students in a multitude of courses. Moreover, current AI-text classifiers cannot reliably detect ChatGPT’s use in school work, due to both their propensity to classify human-written answers as AI-generated, as well as the relative ease with which AI-generated text can be edited to evade detection. Finally, there seems to be an emerging consensus among students to use the tool, and among educators to treat its use as plagiarism. Our findings offer insights that could guide policy discussions addressing the integration of artificial intelligence into educational frameworks