That is a challenge that is going to increase its difficulty progressively in the incoming years. As the generative AI will be trained more and better and the models will improve, the small signs of AI generated content are going to become almost impossible to distinguish. So I would recommend, as the first measure to be sure of the content’s origins, to not trust any content we can find online without a proper human signature. And even if that firm is there, maybe it would be healthy to still doubt its source. We are, sadly, entering a time in human history where a text or photography is not a proof of facts anymore. For the most empirical approach I would point out some signs that have helped me make a distinction between AI generated content and the human one. Text-wise, language models usually go for short enunciative sentences with not much rhetorical figures and self-explanatory points of view. Either if they are supporting or criticizing any point, they won’t mix different povs. Talking about images or videos, usually they have some problems filling pixels in complex structures, so if the observer is able to magnify the image it would be easy to spot some inconsistency. As I say, most of these issues are being fixed by many models right now, so it’s a problem every part of society will need to attend to at some point with no clear outcome.
This distinction has become harder as AI tools have improved during the past few years, and it will likely only become even harder in the future. As of right now text is almost impossible to detect for being AI made just by looking at it. Image and video content have also improved significantly in recent years, but video still looks to be the most challenging to generate with AI. Especially video content including humans or animals can be more easily detected due to all the mistakes that can occur with these categories. However, to answer the question “How can we distinguish”, the true answer probably is that we can’t. Especially when video generation improves further. We can hope that AI generated content will be marked as AI generated, but it will definitely be an easy way to spread misinformation. Therefore, the only thing we can really do is to try seeking trustworthy sources and not believe everything we see on a random video on the internet.
I believe that, with experience, you start to notice certain patterns. Sometimes, content generated by artificial intelligence can have a style that is too structured, very uniform, or even slightly impersonal, and these characteristics can serve as clues that it was AI-generated. Recognizing these subtle hints can help users develop a better sense of when AI might be involved. However, beyond these indicators, it is not always easy to distinguish AI-generated content, to be honest. For this reason, it may be most useful to rely on more sophisticated or specialized tools designed specifically to detect AI-generated material. Even with these tools, though, the task is becoming increasingly complex, and I believe that over time it will be even more difficult to differentiate between human-produced and AI-generated content. As AI technology continues to advance, the lines are likely to blur further, making critical assessment and verification even more essential.
The distinction between human and AI-created content is becoming increasingly difficult as the quality of AI continues to improve. Nevertheless, there are some characteristics and strategies that can help to identify differences – both in texts and in images and videos. With texts, you can pay attention to style and structure. AI texts are often very clear, grammatically correct and logically structured, but sometimes seem a bit "smooth" or neutral. Human texts, on the other hand, more often contain personal opinions, small mistakes, emotional nuances or individual expressions. Another indication can be whether the text provides a lot of information very quickly, but contains little personal experience or concrete examples. There are also typical hints for pictures. While AI-generated images can be realistic, they sometimes have small inconsistencies – such as unusual finger positions, distorted details, or inconsistent lighting conditions. Texts in images are also often incorrect or difficult to read. Human-made photos, on the other hand, tend to look more natural and consistent. In the case of videos, the distinction becomes even more complex. Here you should pay particular attention to facial expressions, lip movements and transitions. AI-generated videos (e.g., deepfakes) may have slight delays between sound and lip movement, or may show unnatural facial features. Atypical movements or too perfect smoothness can also be an indication. In addition to these observations, there are also technical tools such as AI detectors or metadata analyses. Nevertheless, these are not always reliable. That's why it's important to think critically, check sources and question content. Overall, a combination of attention, experience, and skepticism is the best way to distinguish between human and AI-created content.
The clear distinction between human-created and AI-generated content is becoming increasingly difficult. Characteristics that were once considered reliable indicators—such as typical image artifacts or certain writing patterns—are often already outdated. A well-known example is the use of em dashes in text, which for a time were seen as a sign of AI-generated writing. Today, however, many people intentionally use such stylistic elements themselves. As a result, these kinds of markers are no longer sufficient for identifying AI-generated content. From a regulatory perspective, initial measures are emerging. The EU AI Act includes transparency and labeling requirements for AI-generated content in certain contexts. Technical solutions such as invisible watermarking systems like SynthID may also help. However, they do not provide complete protection or a foolproof method of detection. This raises a more fundamental question: does every form of AI-generated content need to be clearly distinguishable from human-created work? In many situations, what matters most is the quality of the outcome. When someone performs a mathematical calculation, for example, few people ask whether it was completed by hand or with a calculator. What matters first and foremost is whether the result is correct. At the same time, these developments are likely to have significant societal consequences. Creative professions, media production, education, and copyright law will all be affected and, in some cases, may need to be redefined. As with previous waves of industrial and technological change, tasks often do not disappear entirely but instead evolve and shift in nature. The key question, therefore, is not whether this transformation will occur, but how we choose to shape and manage it as a society.
It’s going to get harder and harder. We need technical standards for content provenance—transparency and basic media literacy.
Ai avatars are to perfect, the atmosphere is to harmonious
