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AI is a Team Sport for Humans Only


Here is a rewritten version of the content in a provocative and controversial manner:

"The AI Revolution: Why Humans are Still Necessary (And Why AI is Still a Slave to Human Error)"

"The notion that AI can replace humans is a myth perpetuated by AI enthusiasts and technocrats. The reality is that AI is still dependent on human intervention at every stage of its development. From data collection to model deployment, AI requires human expertise to navigate the complexities of the project lifecycle.

But what kind of humans are needed to make AI tick? The answer is not the so-called "AI experts" who claim to possess a deep understanding of machine learning. Rather, it’s the unsung heroes who toil behind the scenes to ensure that AI doesn’t fail. We’re talking about the data engineers, data analysts, software developers, testers, and domain experts who put in the grueling work to make AI a reality.

And what about ethics? Ah, the sacred cow of AI ethics. While AI enthusiasts claim that AI is unbiased and objective, the truth is that human bias is embedded in every stage of the AI development process. From data collection to model deployment, human judgment and decision-making are essential to ensuring that AI doesn’t perpetuate harmful biases.

So, who are the heroes of the AI world? They’re not the AI enthusiasts or technocrats who claim to be leading the AI revolution. They’re the human experts who work tirelessly behind the scenes to make AI a reality. And they’re the ones who will continue to be necessary as long as AI is dependent on human error.

Infographic: The skills required in an AI team – but let’s be real, AI is still a human endeavor.

Step 1: Problem identification – human judgment required

Step 2: Scope – human expertise necessary

Step 3: Data acquisition – human bias embedded

Step 4: Data exploration – human judgment and decision-making essential

Step 5: Develop, build, model – human error unavoidable

Step 6: Deploy – human testing and evaluation necessary

Step 7: Release – human monitoring and feedback required

Step 8: Continuous integration and delivery pipeline – human intervention essential

In conclusion, the AI revolution is not a revolution at all. It’s a human endeavor that requires human expertise, human judgment, and human error. And as long as AI is dependent on human error, we’ll need humans to navigate the complexities of the AI project lifecycle. So, let’s stop pretending that AI is the future and admit that humans are still necessary to make AI a reality."



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