Using AI Tools for Research: AI-Based Research Discovery & Workflow Tools (part2)
In the second part of our two-part series, we will cover AI-integrated research discovery and workflow tools. This sub-category of AI tool is growing exponentially in number and can be a valuable addition to any serious researcher’s toolkit. Promoting research effectiveness and workflows, leveraged by AI models that work with large datasets of scholarly information, they can help conduct literature reviews, generate literature maps or visualizations, summarize or analyze scholarly papers and more! We will explore a mix of free and freemium tools that range from the well-established to newly emerging and experimental.
This workshop will also compare and contrast the above with library research tools, which themselves are beginning to integrate AI features. The strengths and limitations of these research discovery and workflow tools will be outlined and pointers on ethical and academic integrity guidelines that apply at York University will be explained. Finally, we will describe how to effectively use AI tools in tandem with the Library’s discovery tool, OMNI, and its many databases to yield best results
For a workshop that delves deeper into how to cite AI tools, and the ethical and academic integrity considerations associated with them, check out our sister workshop titled “Navigating Academic Integrity: Citing and Ethnical Considerations in the Age of ChatGPT”.
