Generative AI: The Hidden Dangers of Blind Trust

The Importance of an Appropriate Balance of Automation and Human Oversight

Vijay
3 min readJust now
This image is generated using Leonardo AI

Imagine this.

You’re under the gun for a big presentation. Out of desperation, you ask a generative AI tool for assistance. It churns out polished slides and crisp talking points in minutes. Problem solved, right? But near the end of the meeting, someone spots a glaring error — a fake statistic that sounded plausible on the surface.

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Your credibility suffers, and you think: You trusted the AI, and didn’t question its output.

This scenario is not an unusual one in the AI-powered world we inhabit today. Generative AI is a lifesaver, especially on the job, but blind dependence on it can put you in hot water. Let’s examine those hidden risks and how to navigate them responsibly.

1. Misinformation and Hallucination

Generative AI frequently spits out content that has the ring of truth but may be completely false. This problem — known as AI hallucination — has arisen because the models craft text based on patterns, not the truth.

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Vijay
Vijay

Written by Vijay

Python Developer | Flask, Django, AWS | Expert in Microservices & RESTful APIs | Sharing tutorials, tips, and insights to help developers build scalable apps.

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