When Seeing Isn’t Believing: Identifying Visual Health Misinformation

Can you tell which of these images are real people and which of them are AI-generated faces? Find the answer at the end of this article!

Portrait-style photos of three individuals

Deceptive visualizations are not only produced by bad actors hoping to confuse or mislead people. They can also be found in scientific publications, official health department communications, and news reports from generally trustworthy sources. These images are not always designed with malicious intent, but it can be extremely difficult to determine whether they are inaccurate. Of concern, evidence suggests that visual misinformation may be particularly persuasive and can impact viewers’ emotions, attitudes, and behaviors.

HSLS is offering a new online class, When Seeing Isn’t Believing: Identifying Visual Health Misinformation, on Tuesday, March 28, at 3 p.m. This one-hour interactive class will introduce attendees to visual health misinformation as a particular problem for the scientific community and explore the breadth and potential impact of the issue. Attendees will learn how to recognize common types of misleading data visualizations, image manipulation, and imagery with altered or missing context.

If you’ve previously attended the HSLS class Identifying and Combating Health Misinformation, you may recall learning how to identify and respond to health misinformation on social media and when interacting with patients, students, or colleagues. However, identifying deceptive visualizations and imagery is also a vital skill for navigating the current health information landscape in which scrutiny of allegedly manipulated images in scientific publications is increasing, artificial intelligence is becoming capable of generating highly convincing visuals and passing graduate-level exams, and low-tech forms of misinformation such as out-of-context photos and misleading graphs continue to proliferate.

We hope that you will join us on March 28 for When Seeing Isn’t Believing: Identifying Visual Health Misinformation and that this class will increase your confidence in analyzing visual information and empower you to pass that knowledge along to your communities.

~Kelsey Cowles, Rebekah Miller, and Rachel Suppok

Answer: All of the images above were AI-generated! Could you tell? If you couldn’t, don’t worry – you’ll learn some tips for recognizing AI-generated images in the class.