Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Investigating AI languages’ ability to solve undergraduate finance problems
16
Zitationen
2
Autoren
2023
Jahr
Abstract
AbstractThe rapid advancement of artificial intelligence (AI) has given rise to sophisticated language models that excel in understanding and generating human-like text. With the capacity to process vast amounts of information, these models effectively tackle problems across diverse domains. In this paper, we present a comparative analysis of prominent AI language models—ChatGPT and Google Bard—focusing on their ability to solve undergraduate finance problems. We find that GPT-4 significantly outperforms Bard-1.0, excelling in easy problems but struggling with complex ones. The results suggest that it is crucial to handle AI with care in order to uphold academic integrity.Keywords: Artificial intelligenceChatGPTfinancial educationhigher educationundergraduate finance AcknowledgmentsThe authors would like to thank Shishir Paudel, Shiang Liu, and Taggert Brooks for their help.Disclosure statementThe authors report there are no competing interests to declare.Additional informationFundingThis work was supported by grants from the University of Wisconsin-La Crosse College of Business Administration and Menard Family Midwest Initiative for Economic Engagement and Research.
Ähnliche Arbeiten
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller
1999 · 5.632 Zit.
An experiment in linguistic synthesis with a fuzzy logic controller
1975 · 5.550 Zit.
A FRAMEWORK FOR REPRESENTING KNOWLEDGE
1988 · 4.548 Zit.
Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy
2023 · 3.310 Zit.