Generative AI: Supporting AI Literacy, Research, and Publishing

Research and Creation with Generative AI Tools

In addition to the usual considerations for using Generative AI tools, for use in research, see th presentation links for more considerations specific to research. In general, remember that:

• These tools are often a black box and likely biased.  
• Large language models (LLMs) also are known to “hallucinate” (e.g. make things up); they are designed to give you the statistically most likely next words or output - prioritizing fluency over accuracy (the latest models are better but not perfect).
  • Research tools based on the research literature are more likely to use retrieval augmented generation, a process by which the chatbot bases its response on a defined set of papers (with actually existing references, unlike some of the more general chatbots like ChatGPT); this can reduce but doesn't eliminate hallucinations.
• And chatbots don't "know" about the real world. Remember, these are “stochastic parrots” (Bender et. al., 2021), not all-knowing magic beings or anything like a human intelligence no matter how fluent they are!

Generative AI Research Tools

In addition to general generative AI tools (probably based on data from the Internet amongst other sources) like ChatGPT (and products based on it), Microsoft Copilot, Google's Gemini (and products based on it like NotebookLM and Deep Research), Claude, Perplexity and others mentioned on the Generative AI guide, there are tools specifically for research, often based on the research literature, that incorporate generative AI. Here are just a few below. This space for higher education is changing rapidly so keep an eye on Ithaka S&R's Generative AI Product Tracker and check out Other Tools to Investigate below. 

Wondering which tools to use when? Consider your workflow (and whether you need GenAI at all), the task you are trying to accomplish, the level of accuracy and privacy you need, the policies for whatever task you're doing (for example, does your professor or the journal you're submitting to or your work have an AI policy). You might also want to look at librarian Nicole Hennig's guide, "Which generative AI tool for your task?".

Note: Many of these tools are experimental and are in beta (or alpha) so consider them pilots, not the last word for comprehensive searching and research. Nearly all of these are freely available or have a free tier. For more information on some of these see the presentation links. Also note that these lists for the most part don't include AI tools or capabilities that are built into or add ons to our existing subscription databases (such as Scopus AI, Science Direct AI, Primo Research Assistant, JSTOR Interactive Research Assistant, etc - which all require additional subsciptions fees that we have not added at this time). 

Apps

GPTs (apps built on top of ChatGPT) for research includes ones such as Scholar AI, Scholar GPT, Research Papers, and more

Other AI Discovery Tools

Not all AI research tools are generative AI tools like ChatGPT. Many of the tools below may be using some combination of machine learning, deep learning, natural language processing and more to find and visualize the research literature. Some, but not all, of these also incorporate generative AI. To review pros and cons of some of these tools, you can review this presentation and/or watch the associated talk on enhancing research conceptualization with AI. 

Visual Search and Visualization Tools

Other Discovery and Visualization Tools-Uses

Other AI-powered discovery and visualization tools can be:

Useful for:

• Finding relevant papers you might not ordinarily have found by means other than keyword matching, either by searching similar or seeding relevant papers. NOTE: systems that  work from seed papers are often better than those that ask you topics you’re interested in or work like recommender systems (e.g. Amazon “you might also like”), though none of them are perfect
• Visualizing networks of citations and researchers

Not recommended for:

• Comprehensive searches or those requiring exact replication. Uses these as a supplement to library databases and Google Scholar 
• Humanities and non-empirical social sciences may be much less well represented depending on corpus of text the search is based on and results vary by field and subfield
• Interdisciplinary research (except for Inciteful), especially for recommender-based systems

The landscape of tools is changing constantly. Here are some newer tools that I have not investigated yet.