The growing use of artificial intelligence (AI) to generate texts has introduced new challenges across society. Despite the development of detection tools, it remains difficult to determine whether a given text was written by a human or by an AI. Some companies now offer AI detection services, but their reliability is often unclear. Meanwhile, the European AI Act aims to increase transparency around AI-generated content, yet most users still assume such texts are authentic by default. AI-generated texts pose a unique problem because they do not fit neatly into traditional categories of truth or falsehood. They are neither clearly authentic nor clearly fabricated, and no authority is willing to vouch for their accuracy. Companies that create AI chatbots often include vague disclaimers like "May contain errors," similar to warnings found in industries like tobacco or food. This lack of accountability raises concerns about the reliability of AI content. In the literary world, the human author remains a valued concept. In 2024, Japanese novelist Rie Kudan won the prestigious Akutagawa Prize for a science fiction novel, but controversy arose when she admitted to using AI for 5% of the text. Her story, which explores the impact of AI on society, sparked debate. Although juries have since become more cautious, they sometimes face challenges in their own judgments. For example, after a lengthy review, writer Jamir Nazir was allowed to keep his Commonwealth Best Short Story Prize, and the award was even doubled as compensation for initial doubts. Despite these efforts to clarify AI-generated content, detection tools themselves are not always reliable. One of the most well-known companies, Pangram, has urged publishers to strictly control AI content and has even accused major media outlets of publishing AI-generated material. However, controversy arose when The Atlantic reported that the same articles received different AI detection scores at different times of the day. This inconsistency highlights the challenges in trusting these tools. AI detection software is often as unclear as the AI content it tries to identify. For instance, the unpublished work "Human Experience" by Thierry Crouzet, when tested with the tool Justdone, was said to be 61% AI-generated. The author questioned, "Would I only be 39% human?" When tested with other tools, the percentage varied, showing the lack of consistency in these evaluations. Meanwhile, AI tools also offer to "humanize" AI-generated content to avoid suspicion, even as they promote slogans like "Make your text 100% original." The confusion surrounding AI-generated texts is growing. LinkedIn, for example, allows users to label content they suspect is AI-generated as "AI slop," but this system is based on user guesses and is difficult to control. At the same time, LinkedIn offers its own AI text generator, and its parent company is a shareholder in OpenAI, the organization behind ChatGPT. This contradiction underscores the complexity of distinguishing between human and AI-generated content. Researchers are beginning to explore how AI-generated texts differ from human-written texts using techniques like stylometry, which examines patterns in language use. These studies show that AI-generated texts tend to have simpler sentence structures, fewer rare words, and more predictable patterns. However, as AI improves, it becomes harder to distinguish between human and AI writing, especially as writers increasingly use AI to refine their own texts. To address these issues, the European Union has introduced the AI Act, which requires AI-generated content to be clearly marked with metadata. This law, effective from August 2, 2026, aims to hold content creators accountable. However, enforcement remains a challenge, as individuals can still alter or hide metadata, and such information is often not accessible to the general public. Search engines like Google also continue to use AI-generated summaries without explicit labeling. As the line between human and AI-generated texts blurs, the issue of authenticity becomes more pressing. While AI-generated content can be factually accurate, and human texts can be misleading, the authenticity of any text must be questioned. As the 18th-century philosopher Friedrich Schlegel once warned, "It is useless to interpret inauthentic texts." This challenge reminds us that in an era of increasing AI influence, the need for transparency and clarity has never been more important.