How AI makes the internet worse and worse

The contribution how AI makes the internet worse and worse first appeared at the online magazine Basic Thinking. You can start the day well every morning via our newsletter update.

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Artificial intelligence is fundamentally changing the Internet – and not just for the positive. Because: content becomes more superficial, from scratch and therefore less truthful. What started as a technological revolution is increasingly becoming a problem for information quality and user skills.

Background: Why AI makes the internet worse

  • According to a study of the TOW Center for Digital Journalism deliver AI search engines in over 60 percent of cases inaccurate or false sources. For example, the source was assigned incorrectly at Deepseek in 115 out of 200 cases.
  • The Foundation Model Transparency Index evaluates the transparency Leading AI developer such as Openai, Google and Meta. No model achieved more than 54 percent of the maximum possible transparency points. It remains particularly unclear how training data is selected and bias are controlled.
  • AI systems often fall back on already distorted or incorrect content, which are then spread. Users assume these errors, which increases the problem. The result: echo chambers and blisters, the Propagate selective information.

Classification: AI bruts the information landscape

The increasing spread of AI systems on the Internet leads to a brutalization of the information landscape. Contents are not evaluated according to relevance or truth, but according to visibility and attention. This postpones the focus of knowledge transfer to engagement optimization, and undermines trust in digital sources in the long term.

The Mechanisms of AI are non -transparent: users cannot see why a system provides a certain answer. This makes the review of facts more complex and the risk of misinformation greater. Those who rely on AI are increasingly caught in a self -reinforcing information bubble.

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In addition, errors and distortions are hardly controlled in AI models. Even well -intentioned answers can strengthen false narratives and influence political, scientific or social debates. The responsibility is not only with the systems, but with developers, platforms and users who have to reflect critically.

In order to counteract this, ethical standards, transparency obligations and stronger user competence must be promoted. AI must not only be a question of technical feasibility, but also always has to include social responsibility in order to ensure the quality of the information landscape.

Voices

  • Analysts of the TOW Center for Digital Journalism remind: “In over 60 percent of cases, AI search engines provide inaccurate or false sources, which significantly affects the credibility of the information provided.”
  • The Foundation Model Transparency Index comes to one similar conclusion: “Not a single AI model achieved more than 54 percent of the maximum possible transparency points, which indicates significant defects in the disclosure of training data and model architecture.”
  • “Users adopt systematic errors of an biased AI, which leads to an increase in these distortions and affects the quality of the information provided,” says one Conclusion of the University of Deusto.

Outlook: media literacy decisive

The development of AI systems will continue to progress rapidly, which should shape the information landscape even more. Regulatory authorities worldwide could legally anchor transparency obligations, disclosure of training data and labeling obligations for AI content.

At the same time, technical solutions could arise that mark AI answers as unsafe or Use users to point out possible errors. Combined with human curating, this could help limit the spread of incorrect information.

On the user side is Media literacy decisive: Anyone who uses AI -generated content must learn to question critically, to examine sources and to leave their own information bubble. This is the only way to prevent society from suffering the quality of knowledge permanently.

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In the long term, the success of these measures also depends on the willingness of the developers to prioritize ethical guidelines, transparency and responsibility instead of maximizing short -term attention. The balance between technological progress and information quality will be crucial.

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The contribution how AI makes the internet worse and worse first appeared on basic thinking. Follow us too Google News and Flipboard Or subscribe to our update newsletter.


As a tech industry expert, I believe that while AI has undoubtedly brought many benefits to the internet, it has also contributed to making it worse in some aspects. One of the main ways in which AI has negatively impacted the internet is through the proliferation of fake news and misinformation. AI-powered algorithms are often used to spread false information and manipulate users’ online experiences, leading to a decline in trust and credibility on the internet.

Additionally, AI has also been used to create sophisticated spam and phishing campaigns, making it increasingly difficult for users to discern legitimate content from harmful ones. This has resulted in a rise in cyber threats and online scams, further eroding the overall quality of the internet.

Furthermore, AI has also been criticized for perpetuating biases and discrimination in online platforms. Algorithms that power AI systems have been found to exhibit biases against certain groups, leading to discriminatory outcomes in areas such as hiring, advertising, and content recommendation.

Overall, while AI has undoubtedly transformed the internet in many positive ways, it is important to be aware of its negative impacts and work towards mitigating them to ensure a safer and more trustworthy online environment for all users.

Credits

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