AI Tools within Databases
If you've recently used CMU Libraries databases, you may have noticed new features such as "Generate an AI Summary" or "Research Assistant." These tools are part of a growing wave of artificial intelligence (AI) technologies being integrated into academic research platforms such as ProQuest, EBSCO, JSTOR, and other databases available through CMU Libraries. As these third-party tools become increasingly common and powerful, it’s worthwhile to understand what they are, how to use them effectively, and the potential pitfalls of relying on them.
AI tools vary widely in their capabilities and intended uses. Some AI tools assist with searching by interpreting natural-language questions and retrieving relevant sources. Others help researchers discover related topics or refine their research questions. Summarization tools can generate concise overviews of articles or books, while question-answering tools allow users to ask specific questions about a text and receive responses based on its contents. For a more comprehensive list of database AI tools and their capabilities, view the AI in Academic Libraries and Archives Research Guide.
One immediate benefit of using these tools is that it becomes much easier to get started with your research. Summarization tools are useful for quickly determining an article's relevance, while providing additional context in a natural-language search can help retrieve more relevant results for complex queries. Furthermore, being able to ask specific questions about an article’s methodology or results provides immediate clarification, giving you a deeper understanding of your topic.
However, all these tools come with disclaimers, warning that AI tools are limited and may generate responses that are not accurate or lack important context. Users should independently verify AI-generated responses and consult the original source whenever possible. Additionally, since AI systems learn from existing data, they may reproduce biases present in their training materials.
To get the most value from these tools, consider using them to explore topics, identify relevant sources, or generate preliminary summaries. However, treat AI-generated content as a starting point rather than a final authority. Always consult the original source, review citations, and critically evaluate the information before incorporating it into your research. A time-saving way to verify an AI summary is to compare it with the abstract, the original analog article summary. Some research AI tools will provide in-text citations for their claims (or may be able to if requested), allowing you to jump directly to the relevant paragraph in an article. Of course, this approach is not foolproof, and if you’re unable to verify an AI’s claim, it’s best to not use it. Although AI-generated summaries help to quickly determine an article’s relevance, reading the full article for yourself is still highly recommended for the same reason as above: AI systems can oversimplify complex arguments, omit nuances, or occasionally misrepresent information. In general, AI should supplement research, not replace critical reading, analysis, and evaluation.
As AI tools continue to evolve and become more widely integrated into the research process, knowing how to use them can help you save time, increase efficiency, and produce higher-quality scholarly output. AI tools can function like a research assistant, but unlike a librarian or subject expert, AI cannot consistently evaluate authority, context, or accuracy. CMU librarians can help you evaluate sources, develop research strategies, and navigate emerging tools responsibly as part of the research process