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Using AI for Lateral Reading

💡 Core Idea: AI can help you read laterally faster—but you still have to decide what you’re noticing.



In this learning module, you will learn how to:

  • Gather background context about a source, author, or organization
  • Decide when to verify a source elsewhere

Lateral Reading, Briefly

Lateral reading means leaving a source to understand it better. Instead of staying on one page, you open new tabs to learn:

  • Who created the source
  • What their goals might be 
  • How others describe or evaluate them

Lateral reading isn’t about suspicion; it’s about context.

AI's Role in Lateral Reading

AI can help you start lateral reading, but you have to finish the process yourself.

âś… AI is useful for:

  • Quick orientation 
  • Naming organizations, movements, or terms 
  • Identifying possible perspectives or controversies 

đźš« AI is not reliable for:

  • Declaring credibility 
  • Making final judgments 
  • Replacing cross‑checking

The Process

You’re reading an article from a website or organization you don’t recognize. Before trusting or dismissing it, you decide to read laterally.

Copy and paste the link to the web page into an AI tool, and try some prompts:

  • What is this organization, and what is it known for? 
  • What are this group’s stated goals or mission? 
  • How is this website generally described by others?

Make sure your prompts are neutral and not already assuming that the source is credible/not credible.

For example, let’s say I am studying the effects of birdwatching on the environment, and I can’t help but do a Google search. I come across a web page on Substack that looks legit, but I honestly have not heard of the author or his organization.

I paste the article link into an AI tool with this prompt:

Who is Bryan Pfeiffer, and what are his credentials?

I get the following response:

Bryan Pfeiffer is an accomplished American writer, field biologist, entomologist, and educator based in Vermont. He specializes in public communication, natural history journalism, and field research focused primarily on flying things—specifically birds, butterflies, and dragonflies. A summary of his professional background and credentials includes:


Academic & Teaching Credentials
  • Graduate Faculty & Lecturer: Since 2012, he has served on the graduate faculty at the University of Vermont, where he teaches practical and professional writing to graduate students in the renowned Field Naturalist and Ecological Planning programs.
  • Educational Background: He holds a degree in Chemistry, which initially led to early-career work as an air-quality chemist monitoring industrial pollutants before transitioning full-time into journalism and field biology.
Scientific & Field Biology Credentials
  • Research Associate: He is a long-standing Research Associate with the Vermont Center for Ecostudies.
  • State Committee Member: He is a member of the Vermont Endangered Species Committee.
  • Atlas Leadership & Citizen Science: He co-designed and managed the Vermont Butterfly Survey (2001–2007) as its Chief Field Lepidopterist. He is heavily involved in ongoing ecological data projects, including the Vermont Dragonfly and Damselfly Atlas and the Vermont Atlas of Life.
  • Notable Discoveries: He is recognized for his persistent field research; notably, in 2023, after two decades of targeted searching, he discovered the first-ever documented Bog Elfin butterfly in Vermont, a major milestone for the state's biodiversity mapping.
Journalism & Writing Background
  • Recovering Journalist: Pfeiffer spent over a decade (1986–1999) as an award-winning beat reporter, editor, and staff writer covering environmental policy and government for The Times Argus and Rutland Herald.
  • Freelance Essayist & Author: His literary and natural history essays explore the intersection of human nature and the wild. His writing has appeared in major publications including The New York Times, Orion, Aeon Magazine, Audubon Magazine, Field & Stream, and Northern Woodlands.
  • Media & Broadcasting: He co-authored the book Birdwatching in Vermont, co-hosted an award-winning radio program about birds, and wrote/hosted a public television special titled Birding in Vermont. He is also a regular contributor to the nature audio program BirdNote. Currently, he writes the online newsletter Chasing Nature, where he publishes deep-dive dispatches exploring climate, conservation, and the human condition.

âť—WARNING: AI responses usually sound confident. Remember that they are summaries, not verdicts.



This is a lot of information! I have more context now to decide whether to use this web page in my paper. It’s clear that Pfeiffer has relevant credentials for my topic, and I could share some of this information for my reader by writing something like, “According to Bryan Pfeiffer, a field biologist and journalist,…” That way, my reader immediately knows why I chose this source.

But what if my assignment asks for only peer-reviewed or scholarly sources? The author has scholarly credentials, but I can’t tell if this particular web page is considered scholarly or not.

Let’s ask the AI tool:

Is this page scholarly?

The response:

No, this page is not considered a scholarly source.

While Bryan Pfeiffer is a highly credible field biologist and educator, this specific publication comes from his personal Substack newsletter, Chasing Nature, which falls under the category of popular media or natural history journalism rather than peer-reviewed academic literature.

Well, now I know it does not meet the definition of a scholarly source, and I decide not to use it in my paper. It’s not a bad source, but it does not meet the requirements for my assignment.