Using AI tools in Research

If you cannot take AI-cited sources at face value and you (or the AI's programmers) cannot determine where the information is sourced from, how are you going to assess the validity of what AI is telling you? Here you should use the most important method of analysis available to you: lateral reading. Lateral reading is done when you apply fact-checking techniques by leaving the AI output and consulting other sources to evaluate what the AI has provided based on your prompt. You can think of this as “tabbed reading”, moving laterally away from the AI information to sources in other tabs rather than just proceeding “vertically” down the page based on the AI prompt alone.

• Watch: how to read laterally
• Watch: how lateral reading helps you sort fact from fiction

Lateral reading and AI

Lateral reading can (and should) be applied to all online sources, but you will find fewer pieces of information to assess through lateral reading when working with AI. While you can typically reach a consensus about online sources by searching for a source’s publication, funding organization, author or title, none of these bits of information are available to you when assessing AI output. As a result, it is critical that you read several sources outside the AI tool to determine whether credible, non-AI sources can confirm the information the tool returned. 

With AI, instead of asking “who’s behind this information?” we have to ask “who can confirm this information?” In the video above, lateral reading is applied to an online source with an organization name, logo, URL, and authors whose identities and motivations can be researched and fact checked from other sources. AI content has no identifiers and AI output is a composite of multiple unidentifiable sources. This means you must take a look at the factual claims in AI content and decide on the validity of the claims themselves rather than the source of the claims.

Instructions: tackle an AI fact-check

Here's how to fact-check something you got from ChatGPT or a similar tool:

1. Break down the information. Take a look at the response and see if you can isolate specific, searchable claims. This is called fractionation.
2. Then it’s lateral reading time! Open a new tab and look for supporting pieces of information. Here are some good sources to start with:
   • When searching for specific pieces of information: Google results or Wikipedia
   • When seeing if something exists: Google Scholar, Library Catalog, or Wikipedia
3. Next, think deeper about what assumptions are being made here
   • What did your prompt assume?
   • What did the AI assume?
   • Who would know things about this topic? Would they have a different perspective than what the AI is offering? Where could you check to find out?
4. Finally, make a judgment call. What here is true, what is misleading, and what is factually incorrect? Can you re-prompt the AI to try and fix some of these errors? Can you dive deeper into one of the sources you found while fact-checking? Remember, you’re repeating this process for each of the claims the AI made – go back to your list from the first step and keep going!

For an example of this in action, take a look at the video at the bottom of the page.

Check out the videos below to see these lateral reading strategies in action!

The first video has information on fact-checking AI-generated text and links:

And the second video has advice on fact-checking AI-generated citations and scholarly sources:

But just checking specific claims isn't all we need to do. Click the "next" button below to learn about critical thinking beyond fact-checking.

Information taken from the University Libraries at University of Maryland.