LibGuides: Artificial Intelligence Literacy: Misinformation & Inaccuracy

Why is Generative AI Information Typically Flawed or Inaccurate?

Generative AI systems can produce inaccurate and biased content for several reasons:

Training Data Sources: Generative AI models are trained on vast amounts of internet data. This data, while rich in information, contains both accurate and inaccurate content, as well as societal and cultural biases. Since these models mimic patterns in their training data without discerning truth, they can reproduce any falsehoods or biases present in that data (Weise & Metz, 2023).
Limitations of Generative Models: Generative AI models function like advanced autocomplete tools: They’re designed to predict the next word or sequence based on observed patterns. Their goal is to generate plausible content, not to verify its truth. That means any accuracy in their outputs is often coincidental. As a result, they might produce content that sounds reasonable but is inaccurate (O’Brien, 2023).
Inherent Challenges in AI Design: The technology behind generative AI tools isn’t designed to differentiate between what’s true and what’s not true. Even if generative AI models were trained solely on accurate data, their generative nature would mean they could still produce new, potentially inaccurate content by combining patterns in unexpected ways (Weise & Metz, 2023).

Sources and Suggested Readings

When AI Gets It Wrong: Hallucinations and Bias (MIT)
The content of this page was adapted from MIT Management's AI Basics: Hallucinations and Bias site.
When AI Chatbots Hallucinate (NY Times)
If you encounter a paywall to read this article, BGSU students, faculty and staff have free access to the NYT Online: https://libguides.bgsu.edu/newspapers/nyt
Chatbots Sometimes Make Things Up (Associated Press)
Described as hallucination, confabulation or just plain making things up, it’s now a problem for every business, organization and high school student trying to get a generative AI system to compose documents and get work done. Some are using it on tasks with the potential for high-stakes consequences, from psychotherapy to researching and writing legal briefs.
AI Is Getting More Powerful but Its Hallucinations Are Getting Worse (NY Times)
If you encounter a paywall to read this article, BGSU students, faculty, and staff have a free account for NYT Online: https://libguides.bgsu.edu/newspapers/nyt
Foreign Hackers are Using Google's Gemini in Attacks on U.S. (Wired)

Watch this short video from Texas A&M Libraries to learn why Generative AI can provide false or "hallucinated" information and some tips to avoid it.

Artificial intelligence (AI) is creating more content than ever—articles, images, and even videos—but how can you tell the difference between human-made and AI-generated media? In this lesson, we’ll show you how to spot the subtle clues that reveal AI’s involvement. Learn to recognize strange repetition in text, inconsistent details in images, and off-timing in videos. By practicing these tricks, you’ll become a smarter media consumer and be better prepared to identify AI-generated content online.