Asger Risom
A prominent technology expert warns that people are using ChatGPT completely wrong by treating conversational platforms like traditional search engines.
Millions of internet users are fundamentally misunderstanding artificial intelligence by treating chatbots as direct replacements for traditional search engines. According to a recent report from El Economista, this widespread behavioral shift is leading people to consume fabricated information as established fact. Technology experts are now warning that this reliance on language models for factual discovery completely wastes the true potential of the software.
The hallucination trap
For over two decades, digital navigation relied on search algorithms indexing established encyclopedias, news outlets, and academic databases. The explosive rise of generative algorithms has severely disrupted this traditional information architecture in a remarkably short timeframe. Instead of browsing verified sources, millions of users now demand immediate, synthesized answers directly from conversational interfaces.
AI specialist Jon Hernández argues that this shift represents the single biggest error in modern technology adoption. Speaking on the Roca Project podcast, Hernández explained that users mistakenly equate the authoritative tone of a chatbot with factual accuracy. Because these models are designed to predict language rather than verify data, they frequently hypothesize and confidently invent entirely fictitious information.
This fundamental design flaw makes generative models incredibly dangerous when used as primary sources of objective knowledge. Relying on a system prone to hallucinations for historical facts, medical advice, or technical specifications guarantees the spread of severe misinformation. Hernández stresses that treating a language model like a definitive digital encyclopedia is a dangerous misuse of the underlying architecture.
A collaborative workflow
Rather than functioning as a flawless repository of human knowledge, artificial intelligence is built to serve as an interactive processor. Hernández points out that the true power of this technology lies in dynamic, real-time collaboration between the human and the machine. The software excels at manipulating existing data, generating creative frameworks, and accelerating complex workflows when guided by an informed operator.
Treating the software as a passive search engine strips away its most powerful analytical capabilities. Users achieve the best results when they view the program as a dedicated work partner rather than a simple query box. By actively iterating on prompts and refining outputs together, the human operator ensures the final product remains grounded in reality.
This collaborative approach requires users to bring their own foundational knowledge to the interaction to spot potential errors. “Four eyes see more than two,” Hernández noted, emphasizing that the human must always remain the ultimate editor and fact-checker. When properly integrated, the machine handles the structural heavy lifting while the human operator secures the factual integrity of the task.
The delegation disaster
Beyond the search engine misconception, a secondary crisis is emerging as workers attempt to completely outsource their daily responsibilities. Many professionals blindly delegate entire projects to these platforms to avoid doing the actual labor themselves. This hands-off approach inevitably leads to substandard deliverables riddled with structural inconsistencies and factual blind spots.
Automated systems are highly efficient at generating volume, but they completely lack contextual judgment and critical thinking skills. When users abdicate their oversight responsibilities, they expose their organizations to significant operational risks and embarrassing public failures. The technology simply cannot function as an autonomous employee capable of executing complex, multi-step professional duties without strict human supervision.
The modern workforce must fundamentally unlearn its current approach to digital assistants to actually benefit from the ongoing technological revolution. Integrating these models successfully requires more human engagement, not less, as workers must constantly guide and correct the digital output. Moving forward, the most successful professionals will be those who master this collaborative partnership rather than those who try to automate their jobs away.
