This episode of AI Goes to College discuss the practical applications of generative AI tools in academic research, focusing on how they can enhance the research process for higher education professionals. Hosts Craig Van Slyke and Robert E. Crossler discuss three key tools: Connected Papers, Research Rabbit, and Scite_, highlighting their functionalities and the importance of transparency in their use. They emphasize the need for human oversight in research, cautioning against over-reliance on AI-generated content, as it may lack the critical thought necessary for rigorous academic work. The conversation also touches on the emerging tool NotebookLM, which allows users to query research articles and create study guides, while raising ethical concerns about data usage and bias in AI outputs. Ultimately, Craig and Rob encourage listeners to explore these tools thoughtfully and integrate them into their research practices while maintaining a critical perspective on the information they generate.---The integration of generative AI tools into academic research is an evolving topic that Craig and Rob approach with both enthusiasm and caution. Their conversation centers around a recent Brown Bag series at Washington State University, where Rob's doctoral students showcased innovative AI tools designed to assist in academic research. The discussion focuses on three tools in particular: Connected Papers, Research Rabbit, and Scite_. Connected Papers stands out for its transparency, utilizing data from Semantic Scholar to create a visual map of related research, which aids users in finding relevant literature. This tool allows researchers to gauge the interconnectedness of papers and prioritize their reading based on citation frequency and relevance. In contrast, Research Rabbit's lack of clarity regarding its data sources and the meaning of its visual representations raises significant concerns about its reliability. Rob's critical assessment of Research Rabbit serves as a cautionary tale for researchers who might be tempted to rely solely on AI for literature discovery. He argues that while tools like Research Rabbit can provide useful starting points, they often fall short of the rigorous standards required for academic research. The hosts also discuss Cite, which generates literature reviews based on user input. Although Cite can save time for researchers, both Craig and Rob emphasize the necessity of critical engagement with the content, warning against over-reliance on AI-generated summaries that may lack depth and nuance. Throughout the episode, the overarching message is clear: while generative AI can enhance research efficiency, it cannot replace the need for critical thinking and human discernment in the research process. Craig and Rob encourage their listeners to embrace these tools as aides rather than crutches, fostering a mindset of skepticism and inquiry. They underscore the importance of maintaining academic integrity in the face of rapidly advancing technology, reminding researchers that their insights and interpretations are invaluable in shaping the future of scholarship. By the end of the episode, listeners are equipped with practical advice on how to navigate the intersection of AI and research, ensuring that they harness the power of these tools responsibly and effectively.Takeaways:<ul><li> Generative AI tools can help streamline academic research but should not replace critical thinking. </li><li> Connected Papers offers transparency in sourcing research papers, unlike some other tools. </li><li> Students must remain skeptical of AI outputs, ensuring they apply critical thought in research. </li><li> Tools like NotebookLM can assist in summarizing and querying research articles effectively. </li><li> Using AI can eliminate busy work, allowing researchers to focus on adding unique insights. </li><li> Educators need to guide students on how to leverage AI tools responsibly and ethically. </li></ul> Link to Craig's Notebook LM experiment description: <ul><li><a href="https://aigoestocollege.substack.com/p/is-notebook-lm-biased" rel="noopener noreferrer" target="_blank">https://aigoestocollege.substack.com/p/is-notebook-lm-biased</a></li></ul> Links referenced in this episode: <ul><li>Notebook LM: <a href="https://notebooklm.google.com" rel="noopener noreferrer" target="_blank">notebooklm.google.com</a></li><li>AI Goes to College: <a href="https://aigostocollege.com" rel="noopener noreferrer" target="_blank">aigostocollege.com</a></li><li>Google Learn About: <a href="https://learning.google.com" rel="noopener noreferrer" target="_blank">learning.google.com</a></li><li>Connected Papers: <a href="https://www.connectedpapers.com/" rel="noopener noreferrer" target="_blank">https://www.connectedpapers.com/</a></li><li>Scite_: <a href="https://scite.ai/" rel="noopener noreferrer" target="_blank">https://scite.ai/</a></li><li>Research Rabbit: <a href="https://www.researchrabbit.ai/" rel="noopener noreferrer" target="_blank">https://www.researchrabbit.ai/</a></li></ul> Mentioned in this episode:AI Goes to College Newsletter

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