{"id":3121,"date":"2025-08-10T10:01:00","date_gmt":"2025-08-10T08:01:00","guid":{"rendered":"https:\/\/kraftscharling.dk\/?p=3121"},"modified":"2025-07-31T13:28:59","modified_gmt":"2025-07-31T11:28:59","slug":"does-ai-learn-from-ai-data","status":"publish","type":"post","link":"https:\/\/kraftscharling.dk\/en\/laerer-ai-fra-ai-data\/","title":{"rendered":"Does AI Learn from Data It Has Created Itself?"},"content":{"rendered":"

If AI learns from data it has created itself, there is a risk of self-reinforcing misinformation spirals. This makes it highly relevant to consider how we can safeguard democratic discourse in the age of AI. More and more people now receive their news through social media feeds. This shapes how they interpret reality. At the same time, a growing proportion of social media users are synthetic AI bots. Their purpose is often commercial, to promote specific products or to ensure users remain engaged on the platform. But AI bots also hold enormous political potential.<\/em><\/p>\n\n\n\n

This is the second post in the trilogy on how AI can influence our perception of reality. It explores how AI often learns from data it has created itself. The first post discussed whether AI, by getting to know us well enough to hyper-personalize communication, can also predict and manipulate us. The final post will address the fundamental dilemma of what is even real, for example, whether humans have free will, or if reality is fundamentally deterministic.<\/em><\/p>\n\n\n\n

Economic Growth Is Built on the Democratization of Knowledge<\/h2>\n\n\n\n

Since the Enlightenment in the 18th century, human innovation has increased by democratizing and distributing knowledge. This made possible the specialization and collaboration now seen as the key driver<\/a> behind economic growth and prosperity.<\/p>\n\n\n\n

In many ways, AI will reverse that decentralization of knowledge in a very short time. While a Google search returns thousands of relevant links to a question, LLMs like ChatGPT summarize the content of all those links into a single answer. That\u2019s convenient for the user, but it also raises the risk that the simplicity makes the user interpret the answer as THE truth. Over time, users may begin to suspend parts of their critical thinking<\/a>. Yet critical thinking is essential for development, including cognitive development.<\/p>\n\n\n\n


AI May Undermine That Foundation\u2014Partly Because It Becomes a Truth Filter \u2026<\/h2>\n\n\n\n

LLMs generate their answers through chain-of-thought reasoning applied to vast data sources. At the same time, the reasoning patterns themselves are learned from similarly vast data sources. This makes the choice of training data, the \"reality\" the model is exposed to, crucial. AI will only be as reliable as the reality it is allowed to learn from. Just like humans.<\/p>\n\n\n\n

Until 2024, AI providers were obligated to validate sources<\/a>, prioritize verified data, and implement audit mechanisms for their models. They also had to ensure some degree of transparency in how AI adjusted for bias and made decisions.<\/p>\n\n\n\n

\u2026 And Partly Because AI Is Now Trained on Data of Diminishing Quality<\/h2>\n\n\n\n

However, the efficiency of AI algorithms generally increases with the amount of data they are trained on. According to AI providers, we\u2019ve now reached the limit of how much verified, complete, and balanced data is available. As of early 2025, the major hyperscalers and LLM providers<\/a> are training their models on all available user data.\u00a0<\/p>\n\n\n\n

In practice, this means that Meta is training its AI on data from Instagram, Facebook, and WhatsApp, while Amazon is training on data from Amazon Web Services. At best, these datasets reflect society\u2019s average interpretations of facts. They do not represent objective truths, nor what might be worth aspiring to.<\/p>\n\n\n\n

It is therefore worth considering the quality of this data, and who created it. Because much of it is either created or amplified by AI itself.<\/p>\n\n\n\n

And Beyond That, AI May Be Feeding Itself with Data<\/h2>\n\n\n\n

One of the researchers most deeply engaged in how online data originates is Professor Filippo Menczer, an informatics expert at Indiana University. His work has focused especially on how to protect the foundations of democracy, namely democratic discourse. His research centers around two core areas:<\/p>\n\n\n\n