In my previous blog post, I introduced the topic I will be exploring this semester and discussed the growing difficulty of distinguishing between authentic and AI-generated images. One question kept coming up during my research: are people really able to tell the difference?
Many people seem confident that they can spot an AI-generated image immediately. Common clues that are often mentioned include unrealistic hands, strange facial features, or unusual details in the background. However, image generation technology is improving rapidly, and many of these obvious signs are becoming less common. This made me wonder whether people are actually as good at identifying AI-generated images as they think they are.
To explore this question, I am planning a small experiment.
The experiment will consist of two different parts. The first part focuses on fully AI-generated images and authentic photographs. Participants will be shown a collection of images from different contexts, including everyday situations, animals, scientific topics, and news-related content. For each image, they will be asked to decide whether they believe it is authentic or generated by artificial intelligence.
I deliberately want to include different types of content because context may influence how people judge an image. A portrait of a person might be evaluated differently than an image of a rare animal or a news event. By using a variety of subjects, I hope to gain a broader understanding of how people make these decisions.
The second part of the experiment is the one I find particularly interesting. Instead of showing completely different images, participants will be presented with two almost identical versions of the same image. One will be the original photograph, while the other will contain a modification created with AI. This modification could involve adding an object, removing a person, or changing certain elements within the scene.
Participants will then be asked a simple question: Which image is the authentic one?
This part of the experiment is designed to investigate whether people find it easier to identify AI when they can directly compare an original image with a manipulated version. While fully generated images receive a lot of attention, AI is increasingly being used to alter existing photographs rather than create entirely new ones. Because of this, understanding how people perceive manipulated images may be just as important as understanding how they perceive generated ones.
Another aspect I would like to explore is the role of age. In addition to their answers, participants will be asked to indicate their age group. This will allow me to compare the results of different generations and examine whether younger participants are better at recognizing AI-generated or AI-manipulated content.
A common assumption is that younger people may perform better because they are more familiar with digital technologies and encounter AI-generated content more frequently. However, it is also possible that the differences between age groups are smaller than expected. The experiment may reveal whether this assumption is actually true.
Of course, this will only be a small-scale experiment and cannot provide definitive answers. Nevertheless, I hope it will offer an interesting insight into how people currently interact with AI-generated imagery and whether our confidence in recognizing artificial content matches reality.
The next step will be selecting and preparing the images that will be used in the survey. Only then will it become clear how difficult this challenge really is.
