{"id":2342,"date":"2025-09-11T12:45:39","date_gmt":"2025-09-11T16:45:39","guid":{"rendered":"https:\/\/sites.miamioh.edu\/mu-regional-pulse\/?p=2342"},"modified":"2025-09-11T12:47:47","modified_gmt":"2025-09-11T16:47:47","slug":"are-ai-images-becoming-more-difficult-to-identify","status":"publish","type":"post","link":"https:\/\/sites.miamioh.edu\/mu-regional-pulse\/2025\/09\/are-ai-images-becoming-more-difficult-to-identify\/","title":{"rendered":"Are AI Images Becoming More Difficult to Identify?"},"content":{"rendered":"\n
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By Maureen Wilson —<\/p>\n<\/blockquote>\n\n\n\n

AI-generated images have existed as long as there\u2019s been computers to generate them. However, in recent years, its accessibility and popularity have bubbled them to the surface of mainstream culture. Some find the technology fun, while others think it’s a dangerous form of misinformation infiltrating our concept of reality. But, is the line really that blurred? In a new series introducing the capabilities of AI, Outreach & Instruction Librarian Jennifer Hicks recently hosted a presentation about identifying and creating AI images.<\/p>\n\n\n\n

Jennifer Hicks first defined an AI image as a “visual, created or modified using artificial intelligence, often generated from text prompts or by altering existing pictures.” She initially tested the participants on what they considered real versus AI-generated through showing a couple of short-form videos. From there, she explained the mistakes AI-generated images of humans have that separate them from the real thing, such as inconsistent limbs and asymmetry in the body, in the form of distortion or merged proportions. For objects and backgrounds, viewers should look for discrepancies in lighting or shadows, textures, and patterns. Images created by AI usually have an overexposed look that doesn\u2019t reflect real-life physics, or a plasticky texture that feels too smooth. Blurry backgrounds that seem to start and end in completely different places are also a good indication that the image may be AI-generated, along with incomprehensible or difficult-to-read text. Even text that at first appears normal can be formatted or worded in a way that\u2019s awkward for a human to write.<\/p>\n\n\n\n

Finally, it\u2019s important to look at the overall concept of the image. Asking questions such as, “Why does it exist and what purpose does it serve?” is a good way to deduct how individual elements may interact strangely with each other. Other resources to identify AI include reverse searching them on Google (to find the original image), sites like AI or Not, and TinEye. Due to how quickly AI has been improving and adapting, Hicks remarked between slides that she had to update these guidelines to reflect the decreasing ways one can identify them.<\/p>\n\n\n\n

The presentation then segued into how real-life photos can be edited and manipulated with AI. For example, by using a similar prompt over an array of different sites (Microsoft Copilot, Chat GPT, and FreePik), Hicks was able to generate multiple unique iterations of Johnston Hall\u2019s exterior with dinosaurs. A couple more tests were presented as participants explained their reasoning behind believing what was real or not. One exclaimed, “That woman isn’t even holding her sign!” after being shown a replicated picture of woman suffragettes. After learning the basics of how AI interprets reality differently from us, the audience had plenty of \u201ca-ha\u201d moments, much to the delight of Gardner-Harvey\u2019s library staff.<\/p>\n\n\n\n

Hicks pointed out some more inconsistencies in AI videos: “AI doesn\u2019t know how to count, it fluctuates,” referring to a clip where the time didn\u2019t match up with generated gameplay. It was partly interesting and partly unsettling, as participants started to become wary that any of the clips were actually real.<\/p>\n\n\n\n

Nearing the end of the talk, attendees shared the images they were able to create using generative sites. “The prompt is the key to getting what you want out of AI,” Hicks explained. A final point was then made about the environmental impact of using those sites. Statistics ranging from the energy it takes (one HD image equivalent to charging 50% of your phone, asking a question taking 23 times the amount of Googling it) and the water it wastes in the process (comparable to the water demand of a small city of 50,000 people).<\/p>\n\n\n\n

Ms. Hicks ended on a high note, though. “If we can\u2019t escape AI, we can at least identify it.”<\/p>\n\n\n\n

The next AI-related event, “Your AI Toolkit: Using AI in Your Research,” is hosted at Gardner-Harvey Library on Wednesday, September 17, at 12 p.m.<\/p>\n","protected":false},"excerpt":{"rendered":"

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