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Generative AI: Between utility and disinformation

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Generative AI: Between utility and disinformation

Discover the duality of generative AI: a powerful tool for innovation and at the same time a potential source of disinformation.

Discover the duality of generative AI: a powerful tool for innovation and at the same time

Generative AI is at the heart of technological developments and carries the risk of serving as a source of disinformation. Adaptive use and regulation leverage their potential for information dissemination while protecting the integrity of the information. The challenge lies in the balance between innovation and security.

In today’s digital era, where the boundaries between reality and fiction are increasingly blurring, generative artificial intelligence (AI) is becoming the center of attention. This technology, originally developed to improve our ability to gather and process information, has the potential to serve as a source of disinformation. A striking example is the phenomenon of “chatbot hallucinations,” in which fictional information is generated by chatbots and presented as fact, according to a WIRED report. This highlights the danger that fictions quickly establish themselves as supposed facts.

Despite the obvious risks, it would be wrong to view generative AI exclusively negatively. The technology is not the problem, but rather how it is used and regulated. Filtering spam from the training data and adding human review significantly improves the quality and reliability of AI-generated content. Recent studies suggest that AI performance is significantly increased by repeatedly processing the same training data, suggesting that we are in a period of learning and adaptation.

The challenge is to find a balance between acknowledging the risks that generative AI poses and harnessing its potential to advance our knowledge. If used correctly, the technology is a valuable tool. It is critical that we explore the mysteries and challenges associated with generative AI and consider how we use this technology without ignoring its risks.

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A concrete example of the problem is the erroneous presentation of false information by Microsoft’s search engine Bing, which chatbots presented as facts. This highlights the challenge for web search reliability as generative AI creates content that is not present in its training data, thus disrupting web search processes. In particular, the case of a non-existent research paper by Claude Shannon shows how vulnerable search engines are to deception by generative AI. A user experiment revealed that when a new query was sent to Bing, the chatbots’ original incorrect answers were presented as established facts, highlighting the difficulty of automatically identifying AI-generated texts.

With the increasing use of generative AI to create SEO pages, social media posts, and blog posts, there is a chance that this problem will continue to worsen. This is reminiscent of an algorithmic Uroboros in which the AI ​​eats itself. It is critical to understand the risks and impact of generative AI on web search and take steps to protect the integrity of the information we use every day.

Generative AI – Summary

In summary, we are at a critical point where distinguishing between truth and fiction and between man and machine is becoming more difficult. Generative AI plays a central role and raises the question of whether it represents a helpful resource or a risk for misinformation. While technology has the potential to change the landscape of information dissemination, much depends on how we use and regulate it. It is essential to find a balance that both takes the risks seriously and harnesses the potential of this technology to expand our knowledge.

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Generative AI: Between benefit and disinformation – find out more here.

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